diff --git a/mobile/globe/API.md b/mobile/globe/API.md
new file mode 100644
index 000000000..17bd73085
--- /dev/null
+++ b/mobile/globe/API.md
@@ -0,0 +1,103 @@
+# Globe API: round-two additions
+
+These additions extend DESIGN.md §10 and change no existing signature. Import them from `mobile/globe/index.js`. The doc comment at the top of that file repeats this contract.
+
+## Viewer position
+
+```js
+globe.setViewer({ lon, lat } | null)   // where the person is: sets distanceKm and the ISS/Starlink "over you" cards
+globe.viewer() → { lon, lat } | null
+```
+
+## Situations (extended)
+
+```js
+globe.situations({ observer? }) → Promise<Situation[]>
+globe.omitted()  → [{ genre, reason }]   // genres the last call left out, and why
+globe.timings()  → { [genre]: ms }       // per-genre build time of the last call
+```
+
+`Situation` keeps every field from round one (`id, kind, family, section, title, subtitle, place, lon, lat, camera, layers, time?, metrics, thumbnail, live, updatedAt, source, severity`) and adds these:
+
+| Field          | Type                                                                        | Notes                                                                                                                                                                                                                            |
+| -------------- | --------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `band`         | `'orbit' \| 'sky' \| 'ground' \| 'inside'`                                  | The altitude band of the sensor. The engine never emits `inside`, because only the shell's own witness and room cards are inside.                                                                                                |
+| `archetype`    | `'sensor' \| 'eye' \| 'track' \| 'number'`                                  | The card layout. The shell adds `witness` and `room` cards itself.                                                                                                                                                               |
+| `telemetry`    | `string`                                                                    | A short uppercase strip, for example `SKY · FL206 · 332 KT · SQ 7700 · EZY58XM`, `GROUND · CAM 07450 · PICCADILLY CIRCUS · 02:16:14Z` or `ORBIT · ISS · 433 KM · 7.65 KM/S`. Draw it in HTML in a monospace face.                |
+| `media?`       | `{ kind:'image', url, refreshMs, cameraId, headingDeg?, provider?, city? }` | Eye cards only. `url` is a same-origin frame from `/api/cctv/frame/…` that was checked to be a real upstream image, not the proxy's synthetic fallback. For a fresh frame, call `globe.eyeFrameUrl(cameraId)` every `refreshMs`. |
+| `series?`      | `[{ t, v }]`                                                                | Real history for number cards, and for some sensor cards. `t` is epoch ms.                                                                                                                                                       |
+| `seriesLabel?` | `string`                                                                    | The quantity `v` measures, for example `'lightning-active area (km²) per 15 min'`.                                                                                                                                               |
+| `headline?`    | `{ value, unit, label }`                                                    | The one big number on a track or number card.                                                                                                                                                                                    |
+| `distanceKm?`  | `number`                                                                    | The great-circle distance from the viewer. It is present only once `setViewer` has been called, or when `observer` is passed.                                                                                                    |
+
+The `thumbnail` field is still a plain Esri still, so older code keeps working. New code calls `globe.thumbnail(situation)` instead.
+
+The engine orders the cards by severity, then interleaves them so neighbouring cards differ in band and archetype where possible.
+
+## Card compositor
+
+```js
+globe.thumbnail(situation, { width = 360, height = 480, dpr = 2 } = {}) → Promise<string /* blob: object URL */>
+```
+
+The compositor builds each thumbnail as a JPEG in an offscreen 2D canvas, never in the Cesium viewer. It works in three layers:
+
+1. **Base imagery.** Esri World Imagery tiles, which are CORS-clean, or NASA GIBS Black Marble for orbit cards.
+2. **Real overlays.** The data that describes the situation. Examples include NOAA IR with a cold-top enhancement, MRMS radar, lightning density dots by age, the NHC cone with the forecast track and 34/50/64-kt wind radii, aircraft with 2-minute velocity leaders, quake rings, fires with a smoke plume along the observed wind, and SGP4 ground tracks.
+3. **Grade.** A tint for the altitude band (orbit violet night, sky cool, ground amber) and a vignette.
+
+The compositor draws no text and no brackets.
+
+Eye cards return the camera frame itself, lightly graded. Results are cached in memory and, when the page is a secure context, in the Cache API, keyed by id, size and an update bucket. Eye cards refresh every 30 s; other cards follow `updatedAt` in 5-minute buckets. Tiles are shared across cards, and at most 3 cards render at once.
+
+If an overlay fails, the card still gets its base picture. The promise rejects only when the base imagery or the camera frame fails. In that case, fall back to `situation.thumbnail` or to the shell's own placeholder.
+
+## Pins (discourse and capture)
+
+```js
+globe.addPin({ id, lon, lat, kind, headingDeg?, fovDeg = 60, rangeM = 350, color?, label?, altM? }) → id
+  // kind: 'post' | 'witness' | 'eye' | 'live' | 'hologram'
+  // 'live' and 'eye' pins draw a view-frustum wedge on the ground along headingDeg
+globe.removePin(id) → boolean
+globe.pins() → [{ id, lon, lat, kind, headingDeg, fovDeg, rangeM, color, label, altM }]
+```
+
+- Picking a pin emits `'pick'` with `{ kind: 'pin', pinKind, id, title, subtitle, lon, lat, meta: { layer: 'pins', headingDeg, fovDeg, label } }`.
+- Pins appear in `globe.labels()` with `layer: 'pins'` and `pinKind`.
+- Live pins breathe at 1 Hz.
+
+## Labels
+
+Each entry from `globe.labels(max)` can now carry an optional `detail`, a short intensity tag:
+
+- Cyclones: `CAT 2 · 85 KT · 974 HPA`
+- Emergency squawks: `SQ 7700`
+- Air quality: `AQI 152`
+
+## Nearest public camera
+
+```js
+globe.nearestEye(lon, lat, km = 50)
+  → Promise<{ id, title, lon, lat, distanceKm, headingDeg, fovDeg, imageUrl, city, provider } | null>
+globe.eyeFrameUrl(cameraId) → string | null   // a fresh same-origin frame URL
+```
+
+`nearestEye` reads the CCTV catalog at `/api/cctv/sources`, which serves about 4,000 cameras across London, Toronto, Sydney, Seattle, the Bay Area, Los Angeles, Helsinki/Finland, Tallinn, Barcelona, Calgary, Norway and other places. It does not check the frame. A camera can still answer with the proxy's synthetic image when its upstream is down.
+
+## Weather and storm layers (now available in `globe.layers()`)
+
+| id            | Family  | Source                                                                                                                                                                                           | Time                                              |
+| ------------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------- |
+| `radar`       | Weather | NOAA MRMS base reflectivity through nowCOAST (`/api/weather`), CONUS                                                                                                                             | Scrubbing replays about 50 min of 4-minute frames |
+| `clouds`      | Weather | NOAA global longwave IR mosaic through nowCOAST, drawn as an unlit cloud layer (the alpha-keyed IR)                                                                                              | 6 h of hourly frames                              |
+| `lightning`   | Weather | NOAA nowCOAST lightning density, 15 min (Americas and Pacific), with a flickering glow per active 0.5° cell                                                                                      | 3 h of 15-minute frames                           |
+| `wind`        | Weather | 10 m wind, drawn with the desktop app's GPU streamline renderer. Uses `/api/wind` GFS when the server can decode GRIB, otherwise a 12° Open-Meteo grid                                           | Live                                              |
+| `jet`         | Weather | Jet stream at 250 hPa from Open-Meteo, same renderer                                                                                                                                             | Live                                              |
+| `cyclones`    | Hazards | Now also draws the filled NHC cone and 34/50/64-kt wind radii, parsed from the NHC TCM text at api.weather.gov                                                                                   | Forecast scrubbing, as before                     |
+| `air-quality` | Hazards | Open-Meteo Air Quality (CAMS model), PM2.5 AQI for 40 major cities                                                                                                                               | Live                                              |
+| `gnss`        | Infra   | `/api/gnss-integrity` (adsb.lol NIC/NACp), shown as 0.5° cells in gpsjam.org bands. From orbit it samples the Baltic, Black Sea, Levant, Gulf and Gulf of Finland; close in, it samples the view | Live                                              |
+| `transit`     | Ground  | `/api/transit` GTFS-realtime vehicles from the open feed nearest the view                                                                                                                        | Live, 20 s                                        |
+
+Rasters are drawn a few kilometres above the ground and unlit, so storms stay visible on the night side. When an upstream is down, the layer reports `status: 'error'` with a `message`.
+
+When a weather layer is on, `layers()` entries can also carry `frames` (the number of frames available) and a `message` that gives the product title and the frame age.
diff --git a/mobile/globe/compositor.js b/mobile/globe/compositor.js
new file mode 100644
index 000000000..62ef1981b
--- /dev/null
+++ b/mobile/globe/compositor.js
@@ -0,0 +1,1601 @@
+/**
+ * The card compositor (DESIGN.md §11.2 sensor cards): thumbnail(situation)
+ * renders a still in an offscreen 2D canvas, never the Cesium viewer.
+ *
+ *   base imagery  → Esri World Imagery tiles (CORS-clean) or NASA GIBS
+ *                   Black Marble for orbit cards; camera frame for eye cards
+ *   real overlays → the data that describes the situation (NOAA IR with a
+ *                   cold-top enhancement, radar, lightning by age, NHC cone,
+ *                   track and wind radii, aircraft with velocity leaders,
+ *                   quake rings, fire + wind-blown smoke, SGP4 ground tracks,
+ *                   jet-stream streamlines, transit vehicles, GNSS hex heat)
+ *   grade         → per altitude band (orbit violet night, sky cool, ground
+ *                   warm amber) and a vignette. No text, no brackets: the
+ *                   shell draws framing in HTML so it stays crisp.
+ *
+ * Results are object URLs, cached in memory and (when available) the Cache
+ * API; tiles are shared across cards; at most three cards render at once.
+ */
+import { twoline2satrec } from 'satellite.js';
+import { satPosition } from './layers/orbit.js';
+import { radiiRing, RADII_COLORS } from './layers/hazards.js';
+import { SCENES, EYE_FRAMES, dbzOf } from './situations.js';
+import { cctvFrameUrl } from './feeds.js';
+import { aqiColor, sampleField } from './feedsWeather.js';
+import { strikeLevel } from './layers/weather.js';
+import { BLACK_MARBLE_URL } from './imagery.js';
+
+const D2R = Math.PI / 180;
+const ESRI_TILE = (z, x, y) =>
+  `https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/${z}/${y}/${x}`;
+const BLACK_MARBLE_TILE = (z, x, y) =>
+  BLACK_MARBLE_URL.replace('{z}', z).replace('{y}', y).replace('{x}', x);
+const GIBS_TILE = (layer, day, ext, level) => (z, x, y) =>
+  `https://gibs.earthdata.nasa.gov/wmts/epsg3857/best/${layer}/default/${day}/GoogleMapsCompatible_Level${level}/${z}/${y}/${x}.${ext}`;
+const CACHE_NAME = 'gev-thumbs-v2';
+const VERSION = 'v2';
+
+/* ───────────────────────── Projection ───────────────────────── */
+
+function mercY(lat) {
+  const s = Math.sin(Math.max(-85.05, Math.min(85.05, lat)) * D2R);
+  return 0.5 - Math.log((1 + s) / (1 - s)) / (4 * Math.PI);
+}
+
+/** A Web Mercator view of `spanKm` across the card's shorter side. */
+export function makeView(lon, lat, spanKm, W, H) {
+  const mpp = (spanKm * 1000) / Math.min(W, H);
+  const zf = Math.max(
+    0.6,
+    Math.min(19, Math.log2((156543.03392 * Math.cos(lat * D2R)) / mpp)),
+  );
+  const scale = 256 * 2 ** zf;
+  const cx = ((lon + 180) / 360) * scale;
+  const cy = mercY(lat) * scale;
+  const view = {
+    lon,
+    lat,
+    W,
+    H,
+    zf,
+    scale,
+    cx,
+    cy,
+    /** Canvas px for lon/lat, wrapping longitude toward the centre. */
+    project(lo, la) {
+      let x = ((lo + 180) / 360) * scale - cx;
+      if (x > scale / 2) x -= scale;
+      if (x < -scale / 2) x += scale;
+      return [x + W / 2, mercY(la) * scale - cy + H / 2];
+    },
+    unproject(x, y) {
+      const wx = x - W / 2 + cx;
+      const wy = y - H / 2 + cy;
+      const lo = (wx / scale) * 360 - 180;
+      const n = Math.PI - (2 * Math.PI * wy) / scale;
+      return [
+        ((lo + 540) % 360) - 180,
+        (Math.atan(Math.sinh(n)) * 180) / Math.PI,
+      ];
+    },
+    /** Pixels per km at the view centre. */
+    pxPerKm: Math.min(W, H) / spanKm,
+  };
+  return view;
+}
+
+/* ───────────────────────── Fetching ───────────────────────── */
+
+const tileCache = new Map();
+const TILE_CACHE_MAX = 400;
+
+function loadImage(url, { cors = true } = {}) {
+  let p = tileCache.get(url);
+  if (p) {
+    tileCache.delete(url);
+    tileCache.set(url, p);
+    return p;
+  }
+  p = fetch(url, { mode: cors ? 'cors' : 'same-origin' })
+    .then((r) => (r.ok ? r.blob() : null))
+    .then((b) => (b && b.size > 0 ? createImageBitmap(b) : null))
+    .catch(() => null);
+  tileCache.set(url, p);
+  while (tileCache.size > TILE_CACHE_MAX)
+    tileCache.delete(tileCache.keys().next().value);
+  return p;
+}
+
+/** Draw slippy-map tiles for the view. Returns how many tiles drew. */
+async function drawTiles(g, view, urlFor, { maxZ = 18, minZ = 0 } = {}) {
+  const z = Math.max(minZ, Math.min(maxZ, Math.round(view.zf)));
+  const k = 2 ** (view.zf - z);
+  const n = 2 ** z;
+  const cxz = view.cx / k;
+  const cyz = view.cy / k;
+  const x0 = Math.floor((cxz - view.W / 2 / k) / 256);
+  const x1 = Math.floor((cxz + view.W / 2 / k) / 256);
+  const y0 = Math.max(0, Math.floor((cyz - view.H / 2 / k) / 256));
+  const y1 = Math.min(n - 1, Math.floor((cyz + view.H / 2 / k) / 256));
+  const jobs = [];
+  for (let ty = y0; ty <= y1; ty++)
+    for (let tx = x0; tx <= x1; tx++) {
+      const wx = ((tx % n) + n) % n;
+      jobs.push(loadImage(urlFor(z, wx, ty)).then((img) => ({ img, tx, ty })));
+    }
+  let drawn = 0;
+  for (const { img, tx, ty } of await Promise.all(jobs)) {
+    if (!img) continue;
+    const dx = (tx * 256 - cxz) * k + view.W / 2;
+    const dy = (ty * 256 - cyz) * k + view.H / 2;
+    g.drawImage(img, dx, dy, 256 * k + 0.6, 256 * k + 0.6);
+    drawn++;
+  }
+  return drawn;
+}
+
+/** Weather detail window (2:1, 0.25° grid) around the view, inside bounds. */
+function detailBbox(view, bounds, minWidthDeg = 1) {
+  const [w0, n0] = view.unproject(0, 0);
+  const [e0, s0] = view.unproject(view.W, view.H);
+  const lonSpan = (e0 - w0 + 360) % 360 || 360;
+  let width = Math.max(minWidthDeg, lonSpan * 1.05, (n0 - s0) * 2 * 1.05);
+  width = Math.ceil(width / 0.5) * 0.5;
+  const height = width / 2;
+  if (width > bounds.east - bounds.west || height > bounds.north - bounds.south)
+    return null;
+  const snap = (v) => Math.round(v / 0.25) * 0.25;
+  let west = snap(view.lon - width / 2);
+  let south = snap(view.lat - height / 2);
+  west = Math.max(
+    Math.ceil(bounds.west / 0.25) * 0.25,
+    Math.min(west, Math.floor((bounds.east - width) / 0.25) * 0.25),
+  );
+  south = Math.max(
+    Math.ceil(bounds.south / 0.25) * 0.25,
+    Math.min(south, Math.floor((bounds.north - height) / 0.25) * 0.25),
+  );
+  return { west, south, east: west + width, north: south + height };
+}
+
+async function weatherDetail(product, time, bbox, size = 1024) {
+  const url = `/api/weather/image?product=${product}&time=${encodeURIComponent(time)}&bbox=${bbox.west},${bbox.south},${bbox.east},${bbox.north}&size=${size}x${size / 2}`;
+  return loadImage(url, { cors: false });
+}
+
+async function weatherWhole(product, time, width = 2048) {
+  const size = width === 4096 ? '' : `&size=${width}x${width / 2}`;
+  return loadImage(
+    `/api/weather/image?product=${product}&time=${encodeURIComponent(time)}${size}`,
+    { cors: false },
+  );
+}
+
+/** A geographic (plate carrée) raster reprojected into the Mercator view. */
+function drawGeoRaster(g, view, src, b, { step = 2 } = {}) {
+  if (!src) return;
+  const sw = src.width;
+  const sh = src.height;
+  const [lonL] = view.unproject(0, 0);
+  const [lonR] = view.unproject(view.W, 0);
+  let left = lonL;
+  let right = lonR;
+  if (right <= left) right += 360;
+  const geoW = b.east - b.west;
+  const clampL = Math.max(left, b.west);
+  const clampR = Math.min(right, b.east);
+  if (clampR <= clampL) return;
+  const dx0 = ((clampL - left) / (right - left)) * view.W;
+  const dx1 = ((clampR - left) / (right - left)) * view.W;
+  const sx0 = ((clampL - b.west) / geoW) * sw;
+  const sx1 = ((clampR - b.west) / geoW) * sw;
+  for (let y = 0; y < view.H; y += step) {
+    const [, lat] = view.unproject(view.W / 2, y + step / 2);
+    if (lat > b.north || lat < b.south) continue;
+    const sy = ((b.north - lat) / (b.north - b.south)) * sh;
+    g.drawImage(
+      src,
+      sx0,
+      Math.max(0, sy - 0.5),
+      sx1 - sx0,
+      1,
+      dx0,
+      y,
+      dx1 - dx0,
+      step + 0.3,
+    );
+  }
+}
+
+/** Pixels of an image (ImageBitmap/canvas) as RGBA. */
+function pixelsOf(img) {
+  const c = document.createElement('canvas');
+  c.width = img.width;
+  c.height = img.height;
+  const g = c.getContext('2d', { willReadFrequently: true });
+  g.drawImage(img, 0, 0);
+  return { canvas: c, g, data: g.getImageData(0, 0, c.width, c.height) };
+}
+
+/* ───────────────────────── Colour helpers ───────────────────────── */
+
+const IR_STOPS = [
+  [0, [0, 0, 0, 0]],
+  [120, [0, 0, 0, 0]],
+  [150, [170, 180, 195, 110]],
+  [172, [235, 240, 248, 200]],
+  [186, [90, 215, 255, 225]],
+  [198, [40, 110, 255, 235]],
+  [208, [60, 220, 130, 240]],
+  [218, [255, 228, 77, 245]],
+  [228, [255, 140, 50, 250]],
+  [236, [255, 45, 70, 255]],
+  [244, [255, 110, 235, 255]],
+  [252, [255, 255, 255, 255]],
+];
+
+/** Classic cold-cloud-top enhancement for an IR brightness value. */
+function irColor(l) {
+  for (let i = 1; i < IR_STOPS.length; i++) {
+    const [b, cb] = IR_STOPS[i];
+    if (l <= b) {
+      const [a, ca] = IR_STOPS[i - 1];
+      const t = (l - a) / Math.max(1, b - a);
+      return ca.map((v, k) => v + (cb[k] - v) * t);
+    }
+  }
+  return IR_STOPS.at(-1)[1];
+}
+
+function enhanceIr(img, { cool = false } = {}) {
+  const { canvas, g, data } = pixelsOf(img);
+  const px = data.data;
+  for (let i = 0; i < px.length; i += 4) {
+    const a = px[i + 3];
+    if (a < 10) {
+      px[i + 3] = 0;
+      continue;
+    }
+    const c = cool
+      ? [150, 175, 215, Math.max(0, Math.min(220, (px[i] - 140) * 2))]
+      : irColor(px[i]);
+    px[i] = c[0];
+    px[i + 1] = c[1];
+    px[i + 2] = c[2];
+    px[i + 3] = (c[3] * a) / 255;
+  }
+  g.putImageData(data, 0, 0);
+  return canvas;
+}
+
+const SPEED_RAMP = [
+  [0, [40, 90, 200]],
+  [15, [40, 190, 255]],
+  [35, [120, 255, 220]],
+  [55, [255, 255, 255]],
+  [75, [255, 120, 230]],
+  [100, [255, 60, 120]],
+];
+function speedRgb(mps) {
+  for (let i = 1; i < SPEED_RAMP.length; i++) {
+    const [b, cb] = SPEED_RAMP[i];
+    if (mps <= b) {
+      const [a, ca] = SPEED_RAMP[i - 1];
+      const t = (mps - a) / (b - a);
+      return ca.map((v, k) => Math.round(v + (cb[k] - v) * t));
+    }
+  }
+  return SPEED_RAMP.at(-1)[1];
+}
+
+const DBZ_RAMP = [
+  [5, [70, 110, 255]],
+  [18, [40, 200, 255]],
+  [28, [60, 240, 130]],
+  [38, [255, 232, 70]],
+  [48, [255, 110, 50]],
+  [56, [255, 40, 90]],
+  [64, [255, 70, 230]],
+  [72, [255, 255, 255]],
+];
+function dbzRgb(z) {
+  if (z <= DBZ_RAMP[0][0]) return DBZ_RAMP[0][1];
+  for (let i = 1; i < DBZ_RAMP.length; i++) {
+    const [b, cb] = DBZ_RAMP[i];
+    if (z <= b) {
+      const [a, ca] = DBZ_RAMP[i - 1];
+      const t = (z - a) / (b - a);
+      return ca.map((v, k) => Math.round(v + (cb[k] - v) * t));
+    }
+  }
+  return DBZ_RAMP.at(-1)[1];
+}
+
+function mulberry32(seed) {
+  let a = seed >>> 0;
+  return () => {
+    a = (a + 0x6d2b79f5) >>> 0;
+    let t = a;
+    t = Math.imul(t ^ (t >>> 15), t | 1);
+    t ^= t + Math.imul(t ^ (t >>> 7), t | 61);
+    return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
+  };
+}
+
+function hashStr(s) {
+  let h = 2166136261;
+  for (const ch of String(s)) h = Math.imul(h ^ ch.charCodeAt(0), 16777619);
+  return h >>> 0;
+}
+
+const glowCache = new Map();
+/** A soft round sprite in a colour (for additive glows). */
+function glowSprite(css, size = 64) {
+  const key = `${css}:${size}`;
+  let c = glowCache.get(key);
+  if (c) return c;
+  c = document.createElement('canvas');
+  c.width = c.height = size;
+  const g = c.getContext('2d');
+  const r = g.createRadialGradient(
+    size / 2,
+    size / 2,
+    0,
+    size / 2,
+    size / 2,
+    size / 2,
+  );
+  r.addColorStop(0, css);
+  r.addColorStop(
+    0.25,
+    css.replace(/[\d.]+\)$/, (m) => `${parseFloat(m) * 0.6})`),
+  );
+  r.addColorStop(1, 'rgba(0,0,0,0)');
+  g.fillStyle = r;
+  g.fillRect(0, 0, size, size);
+  glowCache.set(key, c);
+  return c;
+}
+
+/* ───────────────────────── Grade ───────────────────────── */
+
+const BASE_FILTER = {
+  orbit: 'saturate(0.85) contrast(1.18) brightness(0.78)',
+  sky: 'saturate(0.55) contrast(1.15) brightness(0.68)',
+  ground: 'saturate(0.9) contrast(1.12) brightness(0.86) sepia(0.12)',
+  inside: 'saturate(0.9) contrast(1.1) brightness(0.9)',
+};
+const BAND_TINT = {
+  orbit: '#6A4CFF',
+  sky: '#3F8CFF',
+  ground: '#FF9C42',
+  inside: '#FFC857',
+};
+
+function tint(g, W, H, band, alpha = 0.32) {
+  g.save();
+  g.globalCompositeOperation = 'soft-light';
+  g.globalAlpha = alpha;
+  g.fillStyle = BAND_TINT[band] || BAND_TINT.ground;
+  g.fillRect(0, 0, W, H);
+  g.restore();
+}
+
+function vignette(g, W, H, strength = 0.62) {
+  g.save();
+  const r = g.createRadialGradient(
+    W / 2,
+    H * 0.46,
+    Math.min(W, H) * 0.32,
+    W / 2,
+    H / 2,
+    Math.hypot(W, H) * 0.62,
+  );
+  r.addColorStop(0, 'rgba(0,0,0,0)');
+  r.addColorStop(1, `rgba(2,4,8,${strength})`);
+  g.fillStyle = r;
+  g.fillRect(0, 0, W, H);
+  // A whisper of top/bottom falloff for the shell's text.
+  const lin = g.createLinearGradient(0, 0, 0, H);
+  lin.addColorStop(0, 'rgba(2,4,8,0.28)');
+  lin.addColorStop(0.18, 'rgba(2,4,8,0)');
+  lin.addColorStop(0.72, 'rgba(2,4,8,0)');
+  lin.addColorStop(1, 'rgba(2,4,8,0.42)');
+  g.fillStyle = lin;
+  g.fillRect(0, 0, W, H);
+  g.restore();
+}
+
+async function base(g, view, band, { night = false, filter } = {}) {
+  g.fillStyle = '#05070B';
+  g.fillRect(0, 0, view.W, view.H);
+  g.save();
+  g.filter = filter || BASE_FILTER[band] || 'none';
+  const drawn = night
+    ? await drawTiles(g, view, BLACK_MARBLE_TILE, { maxZ: 8 })
+    : await drawTiles(g, view, ESRI_TILE, { maxZ: 18 });
+  g.restore();
+  if (!drawn) throw new Error('base imagery unavailable');
+}
+
+/* ───────────────────────── Overlay primitives ───────────────────────── */
+
+function pathLonLat(g, view, pts) {
+  let prev = null;
+  g.beginPath();
+  for (const [lo, la] of pts) {
+    const [x, y] = view.project(lo, la);
+    if (!prev || Math.abs(x - prev[0]) > view.W * 1.5) g.moveTo(x, y);
+    else g.lineTo(x, y);
+    prev = [x, y];
+  }
+}
+
+function glowStroke(g, css, width, blur) {
+  g.save();
+  g.shadowColor = css;
+  g.shadowBlur = blur;
+  g.strokeStyle = css;
+  g.lineWidth = width;
+  g.lineJoin = 'round';
+  g.lineCap = 'round';
+  g.stroke();
+  g.restore();
+}
+
+function planeGlyph(g, x, y, headingDeg, size, css, { ring = false } = {}) {
+  g.save();
+  g.translate(x, y);
+  g.rotate(headingDeg * D2R);
+  g.beginPath();
+  const s = size / 24;
+  g.moveTo(0, -12 * s);
+  g.lineTo(2 * s, -5 * s);
+  g.lineTo(11 * s, 1 * s);
+  g.lineTo(11 * s, 3.5 * s);
+  g.lineTo(2 * s, 1 * s);
+  g.lineTo(1.6 * s, 7 * s);
+  g.lineTo(4.5 * s, 10 * s);
+  g.lineTo(4.5 * s, 11.5 * s);
+  g.lineTo(0, 10.2 * s);
+  g.lineTo(-4.5 * s, 11.5 * s);
+  g.lineTo(-4.5 * s, 10 * s);
+  g.lineTo(-1.6 * s, 7 * s);
+  g.lineTo(-2 * s, 1 * s);
+  g.lineTo(-11 * s, 3.5 * s);
+  g.lineTo(-11 * s, 1 * s);
+  g.lineTo(-2 * s, -5 * s);
+  g.closePath();
+  g.shadowColor = css;
+  g.shadowBlur = size * 0.6;
+  g.fillStyle = css;
+  g.fill();
+  g.restore();
+  if (ring) {
+    for (const [r, a] of [
+      [size * 1.3, 0.9],
+      [size * 2.2, 0.5],
+      [size * 3.3, 0.25],
+    ]) {
+      g.beginPath();
+      g.arc(x, y, r, 0, Math.PI * 2);
+      g.strokeStyle = css.replace(/[\d.]+\)$/, `${a})`);
+      g.lineWidth = size * 0.09;
+      g.stroke();
+    }
+  }
+}
+
+function heliGlyph(g, x, y, size, css) {
+  g.save();
+  g.translate(x, y);
+  g.shadowColor = css;
+  g.shadowBlur = size * 0.6;
+  g.strokeStyle = css;
+  g.fillStyle = css;
+  g.lineWidth = size * 0.1;
+  g.beginPath();
+  g.arc(0, 0, size * 0.22, 0, Math.PI * 2);
+  g.fill();
+  g.beginPath();
+  g.moveTo(-size * 0.55, -size * 0.55);
+  g.lineTo(size * 0.55, size * 0.55);
+  g.moveTo(size * 0.55, -size * 0.55);
+  g.lineTo(-size * 0.55, size * 0.55);
+  g.stroke();
+  g.restore();
+}
+
+/** Destination point (deg) from lon/lat along a bearing for km. */
+function dest(lon, lat, bearingDeg, km) {
+  const d = km / 6371;
+  const b = bearingDeg * D2R;
+  const p1 = lat * D2R;
+  const l1 = lon * D2R;
+  const p2 = Math.asin(
+    Math.sin(p1) * Math.cos(d) + Math.cos(p1) * Math.sin(d) * Math.cos(b),
+  );
+  const l2 =
+    l1 +
+    Math.atan2(
+      Math.sin(b) * Math.sin(d) * Math.cos(p1),
+      Math.cos(d) - Math.sin(p1) * Math.sin(p2),
+    );
+  return [((l2 / D2R + 540) % 360) - 180, p2 / D2R];
+}
+
+function circleLonLat(lon, lat, km, step = 4) {
+  const pts = [];
+  for (let a = 0; a <= 360; a += step) pts.push(dest(lon, lat, a, km));
+  return pts;
+}
+
+/* ───────────────────────── Scenes ───────────────────────── */
+
+const SCENE_DRAW = {
+  async cyclone(g, view, sc, dpr) {
+    await base(g, view, 'orbit', {
+      filter: 'saturate(0.6) contrast(1.2) brightness(0.5)',
+    });
+    tint(g, view.W, view.H, 'orbit', 0.28);
+    // IR: a detail window when it fits, else the global mosaic.
+    if (sc.irTime && sc.irBounds) {
+      const bb = detailBbox(view, sc.irBounds, 4);
+      const img = bb
+        ? await weatherDetail('clouds', sc.irTime, bb, 1024)
+        : await weatherWhole('clouds', sc.irTime, 2048);
+      if (img) drawGeoRaster(g, view, enhanceIr(img), bb || sc.irBounds);
+    }
+    const s = sc.storm;
+    const lw = 1.6 * dpr;
+    // Cone of uncertainty.
+    const cone =
+      s.cone?.type === 'Polygon'
+        ? s.cone.coordinates[0]
+        : s.cone?.type === 'MultiPolygon'
+          ? s.cone.coordinates[0][0]
+          : null;
+    if (cone) {
+      pathLonLat(g, view, cone);
+      g.closePath();
+      g.fillStyle = 'rgba(255,255,255,0.13)';
+      g.fill();
+      g.setLineDash([6 * dpr, 5 * dpr]);
+      glowStroke(g, 'rgba(255,255,255,0.85)', lw, 6 * dpr);
+      g.setLineDash([]);
+    }
+    // Wind radii (34/50/64 kt quadrants).
+    for (const r of [...(s.radii || [])].sort((a, b) => a.kt - b.kt)) {
+      if (!r.quadrantsKm.some((k) => k > 0)) continue;
+      pathLonLat(g, view, radiiRing(s.lon, s.lat, r.quadrantsKm, 4));
+      g.closePath();
+      const col = RADII_COLORS[r.kt] || '#FFD84D';
+      g.globalAlpha = r.kt === 64 ? 0.42 : r.kt === 50 ? 0.32 : 0.22;
+      g.fillStyle = col;
+      g.fill();
+      g.globalAlpha = 0.9;
+      g.strokeStyle = col;
+      g.lineWidth = 1.2 * dpr;
+      g.stroke();
+      g.globalAlpha = 1;
+    }
+    // Past track (EONET) and forecast track with intensity dots.
+    if (s.pastTrack?.length > 1) {
+      pathLonLat(
+        g,
+        view,
+        s.pastTrack.map((p) => [p.lon, p.lat]),
+      );
+      glowStroke(g, 'rgba(255,255,255,0.8)', lw, 4 * dpr);
+    }
+    const fc = [{ lon: s.lon, lat: s.lat, windKt: s.windKt }, ...s.forecast];
+    if (fc.length > 1) {
+      pathLonLat(
+        g,
+        view,
+        fc.map((p) => [p.lon, p.lat]),
+      );
+      glowStroke(g, 'rgba(255,255,255,0.95)', lw * 1.2, 8 * dpr);
+      for (const p of fc.slice(1)) {
+        const [x, y] = view.project(p.lon, p.lat);
+        const kt = p.windKt || 0;
+        const col =
+          kt >= 96
+            ? '#FF4FD8'
+            : kt >= 64
+              ? '#FF4D4D'
+              : kt >= 34
+                ? '#FFD84D'
+                : '#7CC4FF';
+        g.beginPath();
+        g.arc(x, y, (3 + Math.min(5, kt / 25)) * dpr, 0, Math.PI * 2);
+        g.fillStyle = col;
+        g.shadowColor = col;
+        g.shadowBlur = 8 * dpr;
+        g.fill();
+        g.shadowBlur = 0;
+        g.lineWidth = 1 * dpr;
+        g.strokeStyle = 'rgba(0,0,0,0.6)';
+        g.stroke();
+      }
+    }
+    // The storm symbol.
+    const [cx, cy] = view.project(s.lon, s.lat);
+    g.save();
+    g.translate(cx, cy);
+    g.strokeStyle = '#fff';
+    g.shadowColor = '#fff';
+    g.shadowBlur = 10 * dpr;
+    g.lineWidth = 2.6 * dpr;
+    const R = 11 * dpr;
+    g.beginPath();
+    g.arc(0, 0, R * 0.45, 0, Math.PI * 2);
+    g.stroke();
+    for (const sgn of [1, -1]) {
+      g.beginPath();
+      g.arc(
+        sgn * R * 0.45,
+        0,
+        R,
+        sgn > 0 ? Math.PI : 0,
+        sgn > 0 ? Math.PI * 1.55 : Math.PI * 0.55,
+      );
+      g.stroke();
+    }
+    g.restore();
+    vignette(g, view.W, view.H, 0.55);
+  },
+
+  async lightning(g, view, sc, dpr) {
+    await base(g, view, 'sky', {
+      filter: 'saturate(0.45) contrast(1.15) brightness(0.45)',
+    });
+    tint(g, view.W, view.H, 'sky', 0.4);
+    if (sc.irTime && sc.irBounds) {
+      const bb = detailBbox(view, sc.irBounds, 2);
+      const img = bb
+        ? await weatherDetail('clouds', sc.irTime, bb, 1024)
+        : null;
+      if (img) {
+        g.globalAlpha = 0.32;
+        drawGeoRaster(g, view, enhanceIr(img, { cool: true }), bb);
+        g.globalAlpha = 1;
+      }
+    }
+    if (sc.radar) {
+      const bb = detailBbox(view, sc.radar.bounds, 1);
+      const img = bb
+        ? await weatherDetail('radar', sc.radar.time, bb, 1024)
+        : null;
+      if (img) {
+        g.globalAlpha = 0.75;
+        drawGeoRaster(g, view, img, bb);
+        g.globalAlpha = 1;
+      }
+    }
+    // Strikes by age: oldest violet and faint → newest white-hot.
+    const bb = detailBbox(view, sc.bounds, 1);
+    const times = sc.times.slice(-6);
+    const frames = await Promise.all(
+      times.map((t) =>
+        bb
+          ? weatherDetail('lightning', t, bb, 1024)
+          : weatherWhole('lightning', t, 2048),
+      ),
+    );
+    const box = bb || sc.bounds;
+    const colors = [
+      'rgba(255,250,225,1)',
+      'rgba(255,214,120,0.85)',
+      'rgba(255,150,80,0.7)',
+      'rgba(240,90,160,0.55)',
+      'rgba(170,90,255,0.45)',
+      'rgba(110,90,255,0.35)',
+    ];
+    // Sample at the product's native ~8 km grid, one dot per cell.
+    const kmPerPx =
+      ((box.east - box.west) * 111.32 * Math.cos(view.lat * D2R)) / 1024;
+    const step = Math.max(1, Math.round(8 / kmPerPx));
+    const spacing = 8 * view.pxPerKm;
+    const dotR = Math.max(1.4 * dpr, Math.min(4.5 * dpr, spacing * 0.42));
+    g.save();
+    frames.forEach((img, i) => {
+      if (!img) return;
+      const age = frames.length - 1 - i; // 0 = newest
+      g.globalCompositeOperation = age === 0 ? 'lighter' : 'source-over';
+      const { data } = pixelsOf(img);
+      const px = data.data;
+      const w = img.width;
+      const h = img.height;
+      const sprite = glowSprite(colors[Math.min(colors.length - 1, age)], 48);
+      const jitter = mulberry32(hashStr(times[i]));
+      for (let y = 0; y < h; y += step)
+        for (let x = 0; x < w; x += step) {
+          const k = (y * w + x) * 4;
+          if (px[k + 3] < 40) continue;
+          const lon =
+            box.west + ((x + jitter() * step) / w) * (box.east - box.west);
+          const lat =
+            box.north - ((y + jitter() * step) / h) * (box.north - box.south);
+          const [sx, sy] = view.project(lon, lat);
+          if (sx < -20 || sy < -20 || sx > view.W + 20 || sy > view.H + 20)
+            continue;
+          const lvl = strikeLevel(px[k], px[k + 1], px[k + 2]);
+          const r =
+            dotR * (age === 0 ? 1.9 : 1.1 - age * 0.08) * (0.7 + lvl * 0.3);
+          g.drawImage(sprite, sx - r, sy - r, r * 2, r * 2);
+        }
+    });
+    g.restore();
+    vignette(g, view.W, view.H, 0.6);
+  },
+
+  async radar(g, view, sc, dpr) {
+    await base(g, view, 'sky');
+    tint(g, view.W, view.H, 'sky', 0.38);
+    const bb = detailBbox(view, sc.bounds, 1);
+    const img = bb
+      ? await weatherDetail('radar', sc.time, bb, 1024)
+      : await weatherWhole('radar', sc.time, 4096);
+    if (img) {
+      // A soft bloom under crisp echoes; heavier echoes glow hotter.
+      const { canvas, g: rg, data } = pixelsOf(img);
+      const px = data.data;
+      for (let i = 0; i < px.length; i += 4) {
+        const z = dbzOf(px[i], px[i + 1], px[i + 2], px[i + 3]);
+        if (z == null) {
+          px[i + 3] = 0;
+          continue;
+        }
+        const [r, gg, b] = dbzRgb(z);
+        px[i] = r;
+        px[i + 1] = gg;
+        px[i + 2] = b;
+        px[i + 3] = Math.min(255, 110 + z * 2.8);
+      }
+      rg.putImageData(data, 0, 0);
+      g.save();
+      g.filter = `blur(${4 * dpr}px)`;
+      g.globalAlpha = 0.55;
+      drawGeoRaster(g, view, canvas, bb || sc.bounds);
+      g.restore();
+      g.globalAlpha = 0.92;
+      drawGeoRaster(g, view, canvas, bb || sc.bounds, { step: 1 });
+      g.globalAlpha = 1;
+    }
+    // City reticle: a hairline 45 km radius ring (the analysis radius).
+    pathLonLat(g, view, circleLonLat(sc.lon, sc.lat, 45));
+    g.setLineDash([3 * dpr, 4 * dpr]);
+    g.strokeStyle = 'rgba(200,230,255,0.55)';
+    g.lineWidth = 1 * dpr;
+    g.stroke();
+    g.setLineDash([]);
+    vignette(g, view.W, view.H);
+  },
+
+  async jet(g, view, sc, dpr, feeds) {
+    await base(g, view, 'orbit', {
+      night: true,
+      filter: 'brightness(1.1) contrast(1.15) saturate(0.8)',
+    });
+    tint(g, view.W, view.H, 'sky', 0.3);
+    const field = feeds.jet.data?.field;
+    if (!field) throw new Error('jet grid unavailable');
+    const rnd = mulberry32(7);
+    const spacing = 11 * dpr;
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    g.lineCap = 'round';
+    for (let y0 = spacing / 2; y0 < view.H; y0 += spacing)
+      for (let x0 = spacing / 2; x0 < view.W; x0 += spacing) {
+        let x = x0 + (rnd() - 0.5) * spacing;
+        let y = y0 + (rnd() - 0.5) * spacing;
+        let [lon, lat] = view.unproject(x, y);
+        if (Math.abs(lat) > 68) continue; // beyond the grid: no data
+        let { u, v } = sampleField(field, lon, lat);
+        let sp = Math.hypot(u, v);
+        if (sp < 12) continue;
+        const [r, gg, b] = speedRgb(sp);
+        const steps = 10 + Math.round(sp / 6);
+        g.beginPath();
+        g.moveTo(x, y);
+        for (let k = 0; k < steps; k++) {
+          // Pixel step along the wind, normalised so long streaks = fast.
+          const dpx = (sp / 40) * 2.2 * dpr;
+          const norm = Math.hypot(u, v) || 1;
+          x += (u / norm) * dpx;
+          y -= (v / norm) * dpx;
+          g.lineTo(x, y);
+          [lon, lat] = view.unproject(x, y);
+          ({ u, v } = sampleField(field, lon, lat));
+          sp = Math.hypot(u, v);
+        }
+        const a = Math.min(0.85, 0.15 + sp / 90);
+        g.strokeStyle = `rgba(${r},${gg},${b},${a})`;
+        g.lineWidth = (0.6 + Math.min(1.6, sp / 40)) * dpr;
+        g.stroke();
+      }
+    g.restore();
+    vignette(g, view.W, view.H, 0.5);
+  },
+
+  async quake(g, view, sc, dpr) {
+    await base(g, view, 'ground');
+    tint(g, view.W, view.H, 'ground', 0.3);
+    const q = sc.quake;
+    const [cx, cy] = view.project(q.lon, q.lat);
+    // Shaking falls off with distance: rings at 10–200 km, hotter inside.
+    const rings = [
+      [200, 'rgba(255,214,90,0.30)'],
+      [120, 'rgba(255,170,60,0.38)'],
+      [70, 'rgba(255,120,50,0.48)'],
+      [35, 'rgba(255,70,50,0.6)'],
+      [15, 'rgba(255,40,60,0.75)'],
+    ];
+    const grad = g.createRadialGradient(
+      cx,
+      cy,
+      0,
+      cx,
+      cy,
+      view.pxPerKm * 60 * Math.max(1, q.mag - 3),
+    );
+    grad.addColorStop(0, 'rgba(255,60,50,0.45)');
+    grad.addColorStop(1, 'rgba(255,60,50,0)');
+    g.fillStyle = grad;
+    g.fillRect(0, 0, view.W, view.H);
+    for (const [km, css] of rings) {
+      pathLonLat(g, view, circleLonLat(q.lon, q.lat, km));
+      glowStroke(g, css, 1.6 * dpr, 6 * dpr);
+    }
+    for (const n of sc.nearby || []) {
+      const [x, y] = view.project(n.lon, n.lat);
+      g.beginPath();
+      g.arc(x, y, (1.5 + Math.max(0, n.mag - 2.5) * 1.6) * dpr, 0, Math.PI * 2);
+      g.strokeStyle = 'rgba(255,220,150,0.85)';
+      g.lineWidth = 1.2 * dpr;
+      g.stroke();
+    }
+    g.drawImage(
+      glowSprite('rgba(255,250,240,1)', 64),
+      cx - 14 * dpr,
+      cy - 14 * dpr,
+      28 * dpr,
+      28 * dpr,
+    );
+    g.beginPath();
+    g.moveTo(cx - 18 * dpr, cy);
+    g.lineTo(cx + 18 * dpr, cy);
+    g.moveTo(cx, cy - 18 * dpr);
+    g.lineTo(cx, cy + 18 * dpr);
+    g.strokeStyle = 'rgba(255,255,255,0.8)';
+    g.lineWidth = 1 * dpr;
+    g.stroke();
+    vignette(g, view.W, view.H);
+  },
+
+  async 'quake-world'(g, view, sc, dpr) {
+    await base(g, view, 'ground', {
+      filter: 'saturate(0.35) contrast(1.25) brightness(0.42)',
+    });
+    tint(g, view.W, view.H, 'ground', 0.4);
+    const now = Date.now();
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    for (const q of sc.quakes.slice().sort((a, b) => a.mag - b.mag)) {
+      const [x, y] = view.project(q.lon, q.lat);
+      if (x < -30 || y < -30 || x > view.W + 30 || y > view.H + 30) continue;
+      const fresh = Math.max(0.25, 1 - (now - q.time) / 86_400_000);
+      const r = (6 + Math.max(0, q.mag - 2.5) * 9) * dpr;
+      const col =
+        q.mag >= 5
+          ? `rgba(255,70,60,${fresh})`
+          : q.mag >= 4
+            ? `rgba(255,150,60,${fresh})`
+            : `rgba(255,215,120,${fresh})`;
+      g.drawImage(glowSprite(col, 64), x - r, y - r, r * 2, r * 2);
+      if (q.mag >= 4.5) {
+        g.beginPath();
+        g.arc(x, y, r * 0.9, 0, Math.PI * 2);
+        g.strokeStyle = col;
+        g.lineWidth = 1.2 * dpr;
+        g.stroke();
+      }
+    }
+    g.restore();
+    vignette(g, view.W, view.H, 0.5);
+  },
+
+  async fire(g, view, sc, dpr) {
+    await base(g, view, 'ground');
+    tint(g, view.W, view.H, 'ground', 0.36);
+    const rnd = mulberry32(hashStr(`${sc.lon},${sc.lat}`));
+    const f0 = sc.fires[0] || { lon: sc.lon, lat: sc.lat };
+    if (sc.wind) {
+      // Smoke plume: downwind of the fire for ~2 h of travel at the
+      // reported wind, widening with distance (direction is real; the
+      // plume's texture is drawn).
+      const lenKm = Math.min(
+        view.W / view.pxPerKm,
+        Math.max(12, sc.wind.speedKmh * 2),
+      );
+      g.save();
+      for (let i = 0; i < 70; i++) {
+        const t = i / 70;
+        const wobble = Math.sin(t * 7 + rnd() * 2) * 6 * t;
+        const [lon, lat] = dest(
+          f0.lon,
+          f0.lat,
+          sc.wind.toDeg + wobble,
+          lenKm * t,
+        );
+        const [x, y] = view.project(lon, lat);
+        const r = (6 + t * lenKm * 0.35 * view.pxPerKm) * (0.7 + rnd() * 0.6);
+        const a = 0.11 * (1 - t) + 0.025;
+        const grad = g.createRadialGradient(x, y, 0, x, y, r);
+        grad.addColorStop(0, `rgba(215,205,190,${a})`);
+        grad.addColorStop(1, 'rgba(215,205,190,0)');
+        g.fillStyle = grad;
+        g.fillRect(x - r, y - r, r * 2, r * 2);
+      }
+      g.restore();
+    }
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    for (const f of sc.fires) {
+      const [x, y] = view.project(f.lon, f.lat);
+      const big = (f.frp ?? 0) > 50 || (f.acres ?? 0) > 5000;
+      const r = (big ? 26 : 16) * dpr;
+      g.drawImage(
+        glowSprite('rgba(255,110,30,1)', 64),
+        x - r,
+        y - r,
+        r * 2,
+        r * 2,
+      );
+      g.drawImage(
+        glowSprite('rgba(255,230,160,1)', 64),
+        x - r / 3,
+        y - r / 3,
+        (r * 2) / 3,
+        (r * 2) / 3,
+      );
+    }
+    g.restore();
+    vignette(g, view.W, view.H);
+  },
+
+  async aircraft(g, view, sc, dpr) {
+    await base(g, view, 'sky');
+    tint(g, view.W, view.H, 'sky', 0.4);
+    if (sc.airport) {
+      const [x, y] = view.project(sc.airport.lon, sc.airport.lat);
+      for (const km of [10, 25, 50]) {
+        g.beginPath();
+        g.arc(x, y, km * view.pxPerKm, 0, Math.PI * 2);
+        g.strokeStyle = 'rgba(160,210,255,0.35)';
+        g.setLineDash([2 * dpr, 5 * dpr]);
+        g.lineWidth = 1 * dpr;
+        g.stroke();
+      }
+      g.setLineDash([]);
+    }
+    const list = sc.aircraft || [];
+    const glyph =
+      Math.max(9, Math.min(16, 4200 / Math.max(60, view.W / view.pxPerKm))) *
+      dpr;
+    for (const a of list) {
+      if (!a.speed || a.onGround) continue;
+      const [x, y] = view.project(a.lon, a.lat);
+      // Velocity leader: where the aircraft will be in 2 minutes.
+      const [lo, la] = dest(
+        a.lon,
+        a.lat,
+        a.heading || 0,
+        (a.speed * 120) / 1000,
+      );
+      const [x2, y2] = view.project(lo, la);
+      g.beginPath();
+      g.moveTo(x, y);
+      g.lineTo(x2, y2);
+      g.strokeStyle = a.emergency
+        ? 'rgba(255,80,90,0.9)'
+        : 'rgba(140,210,255,0.55)';
+      g.lineWidth = 1.1 * dpr;
+      g.stroke();
+    }
+    for (const a of list) {
+      const [x, y] = view.project(a.lon, a.lat);
+      if (x < -20 || y < -20 || x > view.W + 20 || y > view.H + 20) continue;
+      const css = a.military
+        ? 'rgba(255,209,102,1)'
+        : a.helicopter
+          ? 'rgba(155,225,93,1)'
+          : a.onGround
+            ? 'rgba(160,190,220,0.6)'
+            : 'rgba(190,230,255,1)';
+      if (a.helicopter) heliGlyph(g, x, y, glyph * 1.1, css);
+      else planeGlyph(g, x, y, a.heading || 0, glyph, css);
+    }
+    if (sc.focus) {
+      const [x, y] = view.project(sc.focus.lon, sc.focus.lat);
+      const [lo, la] = dest(
+        sc.focus.lon,
+        sc.focus.lat,
+        sc.focus.heading || 0,
+        ((sc.focus.speed || 0) * 600) / 1000,
+      );
+      const [x2, y2] = view.project(lo, la);
+      g.beginPath();
+      g.moveTo(x, y);
+      g.lineTo(x2, y2);
+      g.setLineDash([5 * dpr, 4 * dpr]);
+      glowStroke(g, 'rgba(255,70,80,0.95)', 2 * dpr, 8 * dpr);
+      g.setLineDash([]);
+      planeGlyph(
+        g,
+        x,
+        y,
+        sc.focus.heading || 0,
+        26 * dpr,
+        'rgba(255,72,82,1)',
+        { ring: true },
+      );
+    }
+    vignette(g, view.W, view.H);
+  },
+
+  async orbit(g, view, sc, dpr) {
+    await base(g, view, 'orbit', {
+      night: true,
+      filter: 'brightness(1.15) contrast(1.2) saturate(0.9)',
+    });
+    tint(g, view.W, view.H, 'orbit', 0.34);
+    const at = sc.at || Date.now();
+    const sats = sc.sats.map((s) => ({
+      ...s,
+      rec: twoline2satrec(s.line1, s.line2),
+    }));
+    const main = sats.find((s) => s.main) || sats[0];
+    // Ground track of the main satellite: −50 → +50 min.
+    const track = [];
+    for (let m = -50; m <= 50; m += 1) {
+      const p = satPosition(main.rec, at + m * 60_000);
+      if (p) track.push([p.lon, p.lat, m]);
+    }
+    const past = track.filter((p) => p[2] <= 0);
+    const future = track.filter((p) => p[2] >= 0);
+    pathLonLat(g, view, past);
+    glowStroke(g, 'rgba(201,167,255,0.85)', 2 * dpr, 10 * dpr);
+    pathLonLat(g, view, future);
+    g.setLineDash([6 * dpr, 6 * dpr]);
+    glowStroke(g, 'rgba(201,167,255,0.6)', 1.6 * dpr, 6 * dpr);
+    g.setLineDash([]);
+    if (sc.train) {
+      g.save();
+      g.globalCompositeOperation = 'lighter';
+      for (const s of sats) {
+        const p = satPosition(s.rec, at);
+        if (!p) continue;
+        const [x, y] = view.project(p.lon, p.lat);
+        const r = 7 * dpr;
+        g.drawImage(
+          glowSprite('rgba(235,225,255,1)', 48),
+          x - r,
+          y - r,
+          r * 2,
+          r * 2,
+        );
+      }
+      g.restore();
+    }
+    const p = satPosition(main.rec, at);
+    if (p) {
+      const [x, y] = view.project(p.lon, p.lat);
+      // Visibility footprint (horizon circle).
+      const footKm = Math.acos(6371 / (6371 + p.altM / 1000)) * 6371;
+      pathLonLat(g, view, circleLonLat(p.lon, p.lat, footKm, 3));
+      g.fillStyle = 'rgba(160,120,255,0.08)';
+      g.fill();
+      g.setLineDash([3 * dpr, 5 * dpr]);
+      g.strokeStyle = 'rgba(201,167,255,0.6)';
+      g.lineWidth = 1 * dpr;
+      g.stroke();
+      g.setLineDash([]);
+      if (!sc.train) {
+        g.drawImage(
+          glowSprite('rgba(255,255,255,1)', 64),
+          x - 18 * dpr,
+          y - 18 * dpr,
+          36 * dpr,
+          36 * dpr,
+        );
+        g.save();
+        g.translate(x, y);
+        g.fillStyle = '#fff';
+        g.fillRect(-11 * dpr, -2.2 * dpr, 22 * dpr, 4.4 * dpr);
+        g.fillRect(-1.6 * dpr, -6 * dpr, 3.2 * dpr, 12 * dpr);
+        g.restore();
+      }
+    }
+    if (sc.observer) {
+      const [x, y] = view.project(sc.observer.lon, sc.observer.lat);
+      g.beginPath();
+      g.arc(x, y, 4 * dpr, 0, Math.PI * 2);
+      g.fillStyle = '#FFC857';
+      g.fill();
+    }
+    vignette(g, view.W, view.H, 0.45);
+  },
+
+  async constellation(g, view, sc, dpr) {
+    await base(g, view, 'orbit', {
+      night: true,
+      filter: 'brightness(1.1) contrast(1.2) saturate(0.85)',
+    });
+    tint(g, view.W, view.H, 'orbit', 0.34);
+    const at = sc.at || Date.now();
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    const dot = glowSprite('rgba(220,205,255,0.95)', 32);
+    const head = glowSprite('rgba(255,255,255,1)', 32);
+    for (const s of sc.sats) {
+      let rec;
+      try {
+        rec = twoline2satrec(s.line1, s.line2);
+      } catch {
+        continue;
+      }
+      const p = satPosition(rec, at);
+      if (!p) continue;
+      const [x, y] = view.project(p.lon, p.lat);
+      if (x < -10 || y < -10 || x > view.W + 10 || y > view.H + 10) continue;
+      // A 90-second streak behind each satellite shows the shells' motion.
+      const q = satPosition(rec, at - 90_000);
+      if (q) {
+        const [x0, y0] = view.project(q.lon, q.lat);
+        if (Math.abs(x0 - x) < view.W / 3) {
+          g.beginPath();
+          g.moveTo(x0, y0);
+          g.lineTo(x, y);
+          g.strokeStyle = 'rgba(170,140,255,0.35)';
+          g.lineWidth = 0.8 * dpr;
+          g.stroke();
+        }
+      }
+      const r = 2.6 * dpr;
+      g.drawImage(
+        hashStr(s.line1) % 50 === 0 ? head : dot,
+        x - r,
+        y - r,
+        r * 2,
+        r * 2,
+      );
+    }
+    g.restore();
+    vignette(g, view.W, view.H, 0.45);
+  },
+
+  async launch(g, view, sc, dpr) {
+    await base(g, view, 'orbit', {
+      filter: 'saturate(0.7) contrast(1.15) brightness(0.62)',
+    });
+    tint(g, view.W, view.H, 'orbit', 0.42);
+    const pad = sc.pad;
+    const orbit = String(sc.orbit || '').toUpperCase();
+    // Indicative ascent azimuth from the pad and target orbit.
+    let az = 90;
+    if (/SSO|POLAR|PO\b/.test(orbit))
+      az = pad.lat > 0 ? (pad.lon < -100 ? 190 : 160) : 200;
+    else if (/ISS|LEO/.test(orbit) && pad.lon > -82 && pad.lon < -79) az = 44;
+    else if (/GTO|GEO|MEO|HEO/.test(orbit)) az = 95;
+    const pts = [];
+    for (let km = 0; km <= 600; km += 10) {
+      const bend = Math.min(1, km / 600) ** 2 * 6;
+      pts.push(dest(pad.lon, pad.lat, az + bend, km));
+    }
+    pathLonLat(g, view, pts);
+    glowStroke(g, 'rgba(255,240,255,0.95)', 2.4 * dpr, 14 * dpr);
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    for (const km of [100, 200, 300, 400]) {
+      const [x, y] = view.project(
+        ...dest(pad.lon, pad.lat, az + (km / 600) ** 2 * 6, km),
+      );
+      g.drawImage(
+        glowSprite('rgba(201,167,255,1)', 48),
+        x - 8 * dpr,
+        y - 8 * dpr,
+        16 * dpr,
+        16 * dpr,
+      );
+    }
+    const [px, py] = view.project(pad.lon, pad.lat);
+    g.drawImage(
+      glowSprite('rgba(255,200,120,1)', 64),
+      px - 22 * dpr,
+      py - 22 * dpr,
+      44 * dpr,
+      44 * dpr,
+    );
+    g.restore();
+    vignette(g, view.W, view.H);
+  },
+
+  async gnss(g, view, sc, dpr) {
+    await base(g, view, 'sky', {
+      filter: 'saturate(0.3) contrast(1.2) brightness(0.42)',
+    });
+    tint(g, view.W, view.H, 'sky', 0.35);
+    // Hex heat: percentage of aircraft with degraded integrity per hex.
+    const R = 26 * dpr;
+    const hexW = Math.sqrt(3) * R;
+    const bins = new Map();
+    for (const r of sc.rows) {
+      const [x, y] = view.project(r.lon, r.lat);
+      const row = Math.round(y / (1.5 * R));
+      const col = Math.round((x - (row % 2) * (hexW / 2)) / hexW);
+      const key = `${row}:${col}`;
+      let b = bins.get(key);
+      if (!b) bins.set(key, (b = { row, col, n: 0, bad: 0 }));
+      b.n++;
+      if (r.degraded || r.gpsLost) b.bad++;
+    }
+    for (const b of bins.values()) {
+      if (b.n < 2) continue;
+      const frac = Math.max(0, b.bad - 1) / b.n;
+      const x = b.col * hexW + (b.row % 2) * (hexW / 2);
+      const y = b.row * 1.5 * R;
+      const col =
+        frac >= 0.1
+          ? [255, 59, 107]
+          : frac >= 0.02
+            ? [255, 177, 61]
+            : [74, 222, 128];
+      g.beginPath();
+      for (let k = 0; k < 6; k++) {
+        const a = (Math.PI / 3) * k + Math.PI / 6;
+        g.lineTo(x + R * 0.94 * Math.cos(a), y + R * 0.94 * Math.sin(a));
+      }
+      g.closePath();
+      g.fillStyle = `rgba(${col},${0.18 + Math.min(0.5, frac * 1.2)})`;
+      g.fill();
+      g.strokeStyle = `rgba(${col},0.6)`;
+      g.lineWidth = 1 * dpr;
+      g.stroke();
+    }
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    for (const r of sc.rows) {
+      const [x, y] = view.project(r.lon, r.lat);
+      const bad = r.degraded || r.gpsLost;
+      const rr = (bad ? 6 : 3.5) * dpr;
+      g.drawImage(
+        glowSprite(bad ? 'rgba(255,70,130,1)' : 'rgba(140,220,255,0.9)', 32),
+        x - rr,
+        y - rr,
+        rr * 2,
+        rr * 2,
+      );
+    }
+    g.restore();
+    vignette(g, view.W, view.H);
+  },
+
+  async transit(g, view, sc, dpr) {
+    await base(g, view, 'ground', {
+      filter: 'saturate(0.7) contrast(1.15) brightness(0.62) sepia(0.1)',
+    });
+    tint(g, view.W, view.H, 'ground', 0.34);
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    for (const v of sc.vehicles) {
+      const [x, y] = view.project(v.lon, v.lat);
+      if (x < -10 || y < -10 || x > view.W + 10 || y > view.H + 10) continue;
+      const h = hashStr(v.routeId) % 360;
+      const moving = (v.speedMps ?? 0) > 1;
+      const r = (moving ? 7 : 5) * dpr;
+      g.drawImage(
+        glowSprite(`hsla(${h},90%,65%,1)`, 32),
+        x - r,
+        y - r,
+        r * 2,
+        r * 2,
+      );
+      if (moving && v.bearing != null) {
+        const [x2, y2] = view.project(
+          ...dest(v.lon, v.lat, v.bearing, (v.speedMps * 60) / 1000),
+        );
+        g.beginPath();
+        g.moveTo(x, y);
+        g.lineTo(x2, y2);
+        g.strokeStyle = `hsla(${h},90%,70%,0.8)`;
+        g.lineWidth = 1.4 * dpr;
+        g.stroke();
+      }
+    }
+    g.restore();
+    vignette(g, view.W, view.H);
+  },
+
+  async aq(g, view, sc, dpr) {
+    // Yesterday's VIIRS true colour (dust and smoke are visible in it) with
+    // MODIS aerosol optical depth over it: observed aerosol, not the model.
+    const day = new Date(Date.now() - 86_400_000).toISOString().slice(0, 10);
+    g.fillStyle = '#05070B';
+    g.fillRect(0, 0, view.W, view.H);
+    g.save();
+    g.filter = 'contrast(1.12) saturate(1.05) brightness(0.92)';
+    const drawn = await drawTiles(
+      g,
+      view,
+      GIBS_TILE('VIIRS_NOAA20_CorrectedReflectance_TrueColor', day, 'jpg', 9),
+      { maxZ: 9 },
+    );
+    g.restore();
+    if (!drawn) await base(g, view, 'ground');
+    tint(g, view.W, view.H, 'ground', 0.22);
+    const aod = document.createElement('canvas');
+    aod.width = view.W;
+    aod.height = view.H;
+    const ag = aod.getContext('2d');
+    if (
+      await drawTiles(
+        ag,
+        view,
+        GIBS_TILE('MODIS_Terra_Aerosol_Optical_Depth_3km', day, 'png', 6),
+        { maxZ: 6 },
+      )
+    ) {
+      g.save();
+      g.globalAlpha = 0.5;
+      g.filter = `blur(${2 * dpr}px)`;
+      g.drawImage(aod, 0, 0);
+      g.restore();
+    }
+    const [x, y] = view.project(sc.lon, sc.lat);
+    const css = aqiColor(sc.aqi);
+    for (const [r, a] of [
+      [10, 1],
+      [22, 0.55],
+      [38, 0.25],
+    ]) {
+      g.beginPath();
+      g.arc(x, y, r * dpr, 0, Math.PI * 2);
+      g.globalAlpha = a;
+      g.strokeStyle = css;
+      g.lineWidth = 1.6 * dpr;
+      g.stroke();
+    }
+    g.globalAlpha = 1;
+    g.drawImage(
+      glowSprite('rgba(255,255,255,1)', 32),
+      x - 5 * dpr,
+      y - 5 * dpr,
+      10 * dpr,
+      10 * dpr,
+    );
+    vignette(g, view.W, view.H);
+  },
+
+  async volcano(g, view, sc, dpr) {
+    await base(g, view, 'ground');
+    tint(g, view.W, view.H, 'ground', 0.36);
+    const [x, y] = view.project(sc.lon, sc.lat);
+    g.save();
+    g.globalCompositeOperation = 'lighter';
+    g.drawImage(
+      glowSprite('rgba(255,80,30,0.9)', 64),
+      x - 40 * dpr,
+      y - 40 * dpr,
+      80 * dpr,
+      80 * dpr,
+    );
+    g.drawImage(
+      glowSprite('rgba(255,220,150,1)', 64),
+      x - 10 * dpr,
+      y - 10 * dpr,
+      20 * dpr,
+      20 * dpr,
+    );
+    g.restore();
+    vignette(g, view.W, view.H);
+  },
+
+  async flood(g, view, sc, dpr) {
+    await base(g, view, 'ground');
+    tint(g, view.W, view.H, 'ground', 0.3);
+    if (sc.path?.length > 1) {
+      pathLonLat(g, view, sc.path);
+      glowStroke(g, 'rgba(94,200,255,0.9)', 3 * dpr, 12 * dpr);
+    }
+    if (sc.corridor?.length > 1) {
+      pathLonLat(
+        g,
+        view,
+        sc.corridor.map((c) => [c[0], c[1]]),
+      );
+      glowStroke(g, 'rgba(190,240,255,1)', 4 * dpr, 16 * dpr);
+    }
+    for (const a of sc.anchors || []) {
+      const [x, y] = view.project(a.lon, a.lat);
+      g.drawImage(
+        glowSprite('rgba(255,200,87,1)', 32),
+        x - 8 * dpr,
+        y - 8 * dpr,
+        16 * dpr,
+        16 * dpr,
+      );
+    }
+    vignette(g, view.W, view.H);
+  },
+
+  async vessels(g, view, sc, dpr) {
+    await base(g, view, 'ground', {
+      filter: 'saturate(0.6) contrast(1.15) brightness(0.6)',
+    });
+    tint(g, view.W, view.H, 'ground', 0.25);
+    for (const v of sc.vessels) {
+      const [x, y] = view.project(v.lon, v.lat);
+      planeGlyph(g, x, y, v.heading || 0, 8 * dpr, 'rgba(56,225,198,1)');
+    }
+    vignette(g, view.W, view.H);
+  },
+
+  async eye(g, view, sc, dpr, feeds) {
+    let blob = EYE_FRAMES.get(sc.cameraId);
+    if (!blob || Date.now() - blob.at > 60_000) {
+      const cam = feeds.cctv.data?.records.find((c) => c.id === sc.cameraId);
+      if (!cam) throw new Error('camera not in catalog');
+      const r = await fetch(cctvFrameUrl(cam), { cache: 'no-store' });
+      if (!r.ok || r.headers.get('x-cctv-source') !== 'upstream-image')
+        throw new Error('no live frame');
+      blob = { blob: await r.blob(), at: Date.now() };
+      EYE_FRAMES.set(sc.cameraId, blob);
+    }
+    const img = await createImageBitmap(blob.blob);
+    const { W, H } = view;
+    const s = Math.max(W / img.width, H / img.height);
+    const w = img.width * s;
+    const h = img.height * s;
+    g.fillStyle = '#05070B';
+    g.fillRect(0, 0, W, H);
+    g.save();
+    g.filter = 'contrast(1.12) saturate(1.05) brightness(0.95)';
+    g.drawImage(img, (W - w) / 2, (H - h) / 2, w, h);
+    g.restore();
+    img.close?.();
+    tint(g, W, H, 'ground', 0.18);
+    vignette(g, W, H, 0.5);
+  },
+
+  async plain(g, view, sc) {
+    await base(g, view, sc.band || 'ground');
+    tint(g, view.W, view.H, sc.band || 'ground');
+    vignette(g, view.W, view.H);
+  },
+};
+
+/* ───────────────────────── Compositor ───────────────────────── */
+
+function semaphore(n) {
+  let active = 0;
+  const queue = [];
+  const next = () => {
+    if (active >= n || !queue.length) return;
+    active++;
+    const { fn, resolve, reject } = queue.shift();
+    fn()
+      .then(resolve, reject)
+      .finally(() => {
+        active--;
+        next();
+      });
+  };
+  return (fn) =>
+    new Promise((resolve, reject) => {
+      queue.push({ fn, resolve, reject });
+      next();
+    });
+}
+
+export function createCompositor({ feeds }) {
+  const mem = new Map();
+  const urls = new Set();
+  const run = semaphore(3);
+  const cacheApi = typeof caches !== 'undefined' && globalThis.isSecureContext;
+
+  function keyFor(situation, W, H, dpr) {
+    const bucket =
+      situation.archetype === 'eye'
+        ? Math.floor(Date.now() / 30_000)
+        : Math.floor((situation.updatedAt || 0) / 300_000);
+    return `${VERSION}/${encodeURIComponent(situation.id)}/${W}x${H}@${dpr}/${bucket}`;
+  }
+
+  async function render(situation, W, H, dpr) {
+    const scene = SCENES.get(situation.id) || { band: situation.band };
+    const type = scene.type && SCENE_DRAW[scene.type] ? scene.type : 'plain';
+    const spanKm =
+      scene.spanKm ||
+      (situation.camera?.height ? situation.camera.height / 1500 : 120);
+    const view = makeView(
+      Number.isFinite(scene.lon) ? scene.lon : situation.lon,
+      Number.isFinite(scene.lat) ? scene.lat : situation.lat,
+      spanKm,
+      W,
+      H,
+    );
+    const canvas = document.createElement('canvas');
+    canvas.width = W;
+    canvas.height = H;
+    const g = canvas.getContext('2d');
+    const sc = { band: situation.band, ...scene, lon: view.lon, lat: view.lat };
+    try {
+      await SCENE_DRAW[type](g, view, sc, dpr, feeds);
+    } catch (error) {
+      if (type === 'eye' || type === 'plain') throw error;
+      // An overlay failing must not cost the card its picture.
+      console.warn(`[globe:thumbnail] ${situation.id}`, error);
+      g.clearRect(0, 0, W, H);
+      await SCENE_DRAW.plain(g, view, sc, dpr, feeds);
+    }
+    return new Promise((resolve, reject) =>
+      canvas.toBlob(
+        (b) => (b ? resolve(b) : reject(new Error('encode failed'))),
+        'image/jpeg',
+        0.86,
+      ),
+    );
+  }
+
+  return {
+    thumbnail(situation, { width = 360, height = 480, dpr = 2 } = {}) {
+      if (!situation?.id)
+        return Promise.reject(new TypeError('thumbnail needs a situation'));
+      const d = Math.max(1, Math.min(3, dpr));
+      const W = Math.round(width * d);
+      const H = Math.round(height * d);
+      const key = keyFor(situation, W, H, d);
+      let p = mem.get(key);
+      if (p) return p;
+      p = run(async () => {
+        const reqUrl = `${location.origin}/__gev-thumb/${key}`;
+        if (cacheApi) {
+          try {
+            const c = await caches.open(CACHE_NAME);
+            const hit = await c.match(reqUrl);
+            if (hit) return URL.createObjectURL(await hit.blob());
+          } catch {
+            /* no Cache API (private mode) */
+          }
+        }
+        const blob = await render(situation, W, H, d);
+        if (cacheApi)
+          caches
+            .open(CACHE_NAME)
+            .then((c) =>
+              c.put(
+                reqUrl,
+                new Response(blob, {
+                  headers: { 'Content-Type': 'image/jpeg' },
+                }),
+              ),
+            )
+            .catch(() => {});
+        const url = URL.createObjectURL(blob);
+        urls.add(url);
+        return url;
+      });
+      p.catch(() => mem.delete(key));
+      mem.set(key, p);
+      while (mem.size > 120) mem.delete(mem.keys().next().value);
+      return p;
+    },
+    destroy() {
+      for (const u of urls) URL.revokeObjectURL(u);
+      urls.clear();
+      mem.clear();
+    },
+  };
+}
diff --git a/mobile/globe/contact.css b/mobile/globe/contact.css
new file mode 100644
index 000000000..cbf40bd92
--- /dev/null
+++ b/mobile/globe/contact.css
@@ -0,0 +1,70 @@
+:root {
+  color-scheme: dark;
+}
+body {
+  margin: 0;
+  background: #05070b;
+  color: #dfe6f0;
+  font:
+    12px/1.35 system-ui,
+    sans-serif;
+}
+#globe {
+  position: fixed;
+  left: -9999px;
+  width: 320px;
+  height: 320px;
+}
+#status {
+  padding: 10px 14px;
+  font:
+    11px ui-monospace,
+    monospace;
+  color: #8aa0b8;
+}
+#sheet {
+  display: grid;
+  grid-template-columns: repeat(auto-fill, var(--cw, 216px));
+  gap: 10px;
+  padding: 0 14px 14px;
+}
+figure {
+  margin: 0;
+  position: relative;
+  width: var(--cw, 216px);
+}
+figure img {
+  display: block;
+  width: var(--cw, 216px);
+  height: var(--ch, 288px);
+  border-radius: 14px;
+  object-fit: cover;
+  background: #111;
+}
+figure .tm {
+  position: absolute;
+  left: 8px;
+  right: 8px;
+  bottom: 52px;
+  font:
+    600 8.5px ui-monospace,
+    monospace;
+  letter-spacing: 0.04em;
+  color: #fff;
+  text-shadow: 0 1px 2px #000;
+}
+figcaption {
+  padding: 4px 2px 0;
+  height: 44px;
+  overflow: hidden;
+}
+figcaption b {
+  display: block;
+  font-size: 12px;
+}
+figcaption small {
+  color: #8aa0b8;
+}
+.err {
+  color: #ff6a3d;
+}
diff --git a/mobile/globe/contact.html b/mobile/globe/contact.html
new file mode 100644
index 000000000..4bce3d096
--- /dev/null
+++ b/mobile/globe/contact.html
@@ -0,0 +1,16 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <link rel="icon" href="data:," />
+    <title>Globe cards · contact sheet</title>
+    <link rel="stylesheet" href="./contact.css" />
+  </head>
+  <body>
+    <div id="globe"></div>
+    <header id="status">building situations…</header>
+    <main id="sheet"></main>
+    <script type="module" src="./contact.js"></script>
+  </body>
+</html>
diff --git a/mobile/globe/contact.js b/mobile/globe/contact.js
new file mode 100644
index 000000000..7ca4535eb
--- /dev/null
+++ b/mobile/globe/contact.js
@@ -0,0 +1,59 @@
+// Contact sheet: every live situation with its composited thumbnail.
+// Open /mobile/globe/contact.html (optionally ?lat=&lon= for a viewer).
+import { createGlobe } from './index.js';
+
+const params = new URLSearchParams(location.search);
+const status = document.getElementById('status');
+const sheet = document.getElementById('sheet');
+const globe = await createGlobe(document.getElementById('globe'), {
+  layers: [],
+  terrain: false,
+});
+window.globe = globe;
+if (params.has('lat'))
+  globe.setViewer({
+    lat: Number(params.get('lat')),
+    lon: Number(params.get('lon')),
+  });
+
+const t0 = performance.now();
+const only = params.get('only');
+const all = await globe.situations();
+const list = only
+  ? all.filter((s) => only.split(',').some((o) => s.id.startsWith(o)))
+  : all;
+const cw = Number(params.get('w') || 216);
+const ch = Math.round((cw * 4) / 3);
+document.documentElement.style.setProperty('--cw', `${cw}px`);
+document.documentElement.style.setProperty('--ch', `${ch}px`);
+window.situations = list;
+status.textContent = `${list.length} situations in ${Math.round(performance.now() - t0)} ms · rendering thumbnails…`;
+const t1 = performance.now();
+let done = 0;
+await Promise.all(
+  list.map(async (s) => {
+    const fig = document.createElement('figure');
+    const img = document.createElement('img');
+    const tm = document.createElement('div');
+    tm.className = 'tm';
+    tm.textContent = s.telemetry || '';
+    const cap = document.createElement('figcaption');
+    cap.innerHTML = `<b></b><small></small>`;
+    cap.querySelector('b').textContent = s.title;
+    cap.querySelector('small').textContent =
+      `${s.band}/${s.archetype} · ${s.subtitle}`;
+    fig.append(img, tm, cap);
+    sheet.append(fig);
+    try {
+      img.src = await globe.thumbnail(s, { width: cw, height: ch, dpr: 2 });
+    } catch (error) {
+      cap.querySelector('small').className = 'err';
+      cap.querySelector('small').textContent =
+        `thumbnail failed: ${error.message}`;
+    }
+    done++;
+  }),
+);
+status.textContent = `${list.length} situations · thumbnails in ${Math.round(performance.now() - t1)} ms · omitted: ${(globe.omitted?.() || []).map((o) => `${o.genre} (${o.reason})`).join('; ')}`;
+console.log('timings', JSON.stringify(window.globe.timings?.()));
+document.body.dataset.ready = '1';
diff --git a/mobile/globe/dev.js b/mobile/globe/dev.js
index 201ac5977..db89d4686 100644
--- a/mobile/globe/dev.js
+++ b/mobile/globe/dev.js
@@ -48,7 +48,7 @@ const drawLabels = () => {
   labelLayer.replaceChildren(
     ...globe.labels(40).map((l) => {
       const el = document.createElement('span');
-      el.textContent = l.title;
+      el.textContent = l.detail ? `${l.title} · ${l.detail}` : l.title;
       el.style.left = `${l.x}px`;
       el.style.top = `${l.y}px`;
       return el;
diff --git a/mobile/globe/feeds.js b/mobile/globe/feeds.js
index 1c03c4a41..9968a057f 100644
--- a/mobile/globe/feeds.js
+++ b/mobile/globe/feeds.js
@@ -89,7 +89,7 @@ const REGISTRATION_CALLSIGN =
   /^(N\d{1,5}[A-Z]{0,2}|[CDFGI]-?[A-Z]{4}|VH-?[A-Z]{3}|D[A-Z]{4}|ZK-?[A-Z]{3}|JA\d{3,4}[A-Z]?)$/;
 
 /** OpenSky state vector → flight record. */
-function flightFromState(s) {
+export function flightFromState(s) {
   const lon = finite(s[5]);
   const lat = finite(s[6]);
   if (lon === null || lat === null) return null;
diff --git a/mobile/globe/feedsWeather.js b/mobile/globe/feedsWeather.js
new file mode 100644
index 000000000..8951c31e9
--- /dev/null
+++ b/mobile/globe/feedsWeather.js
@@ -0,0 +1,716 @@
+/**
+ * Round-two feeds: weather rasters (NOAA nowCOAST through the app's
+ * /api/weather proxy), wind fields (/api/wind GFS, else Open-Meteo), the jet
+ * stream (Open-Meteo 250 hPa), NHC wind radii (api.weather.gov TCM text,
+ * CORS-enabled), GNSS integrity (/api/gnss-integrity), GTFS-realtime transit
+ * (/api/transit), air quality (Open-Meteo) and regional ADS-B scans.
+ *
+ * Every loader is keyless. Each returns real data or throws; nothing here
+ * invents a value when an upstream is down.
+ */
+import { createFeed, FeedError } from './feeds.js';
+import { finite } from './geo.js';
+
+const TIMEOUT_MS = 25_000;
+
+async function getJson(url, { timeoutMs = TIMEOUT_MS, ...init } = {}) {
+  const controller = new AbortController();
+  const timer = setTimeout(() => controller.abort(), timeoutMs);
+  try {
+    const response = await fetch(url, { ...init, signal: controller.signal });
+    if (!response.ok)
+      throw new FeedError(`HTTP ${response.status} for ${url.split('?')[0]}`, {
+        status: response.status,
+      });
+    return await response.json();
+  } finally {
+    clearTimeout(timer);
+  }
+}
+
+/** A small keyed cache of single-flight loads (per anchor / per feed id). */
+export function createKeyedFeed(name, load, { ttlMs = 60_000, max = 32 } = {}) {
+  const entries = new Map();
+  return {
+    name,
+    peek(key) {
+      return entries.get(key)?.data ?? null;
+    },
+    entries() {
+      return [...entries.values()].filter((e) => e.data);
+    },
+    async get(key, args, { maxAgeMs = ttlMs } = {}) {
+      let e = entries.get(key);
+      if (e?.data && Date.now() - e.at < maxAgeMs) return e.data;
+      if (e?.error && Date.now() - e.failedAt < 30_000) {
+        if (e.data) return e.data;
+        throw e.error;
+      }
+      if (!e) {
+        e = { key, data: null, at: 0, inflight: null, error: null };
+        entries.set(key, e);
+        while (entries.size > max) entries.delete(entries.keys().next().value);
+      }
+      if (!e.inflight)
+        e.inflight = (async () => {
+          try {
+            e.data = await load(args ?? key);
+            e.at = Date.now();
+            e.error = null;
+          } catch (error) {
+            e.error = error;
+            e.failedAt = Date.now();
+          } finally {
+            e.inflight = null;
+          }
+        })();
+      await e.inflight;
+      if (!e.data) throw e.error || new FeedError(`${name} unavailable`);
+      return e.data;
+    },
+  };
+}
+
+/* ───────────────────────── Weather rasters ───────────────────────── */
+
+export const WEATHER_TILE_LEVEL_MAX = 6;
+
+/** nowCOAST manifest: { product, times[], latest, bounds, title, attribution }. */
+export function createWeatherManifestFeed(product) {
+  return createFeed(
+    `weather:${product}`,
+    async () => {
+      const m = await getJson(`/api/weather/manifest?product=${product}`, {
+        cache: 'no-store',
+      });
+      if (m?.unavailable || !Array.isArray(m?.times) || !m.times.length)
+        throw new FeedError(m?.reason || `${product} imagery unavailable`);
+      return {
+        data: {
+          product,
+          times: m.times,
+          latest: m.latest,
+          bounds: m.bounds,
+          title: m.title,
+          coverage: m.coverage,
+          description: m.description,
+          attribution: m.attribution,
+          source: `NOAA nowCOAST · ${m.title}`,
+        },
+        stale: Boolean(m.stale),
+      };
+    },
+    { ttlMs: product === 'clouds' ? 10 * 60_000 : 2 * 60_000 },
+  );
+}
+
+/** Same-origin whole-extent image URL for a frame (2:1 sizes only). */
+export function weatherImageUrl(product, time, width = 2048) {
+  const size = width === 4096 ? '' : `&size=${width}x${width / 2}`;
+  return `/api/weather/image?product=${product}&time=${encodeURIComponent(time)}${size}`;
+}
+
+/** Same-origin geographic tile URL (z ≤ 6; 2×1 tiles at level 0). */
+export function weatherTileUrl(product, time, z, x, y) {
+  return `/api/weather/tile?product=${product}&time=${encodeURIComponent(time)}&z=${z}&x=${x}&y=${y}`;
+}
+
+/** Latest frame at or before `ms` (the latest when ms is null). */
+export function frameAt(times, ms) {
+  if (!times?.length) return null;
+  if (ms == null) return times.at(-1);
+  let best = null;
+  for (const t of times) if (Date.parse(t) <= ms + 60_000) best = t;
+  return best;
+}
+
+/* ───────────────────────── Wind ───────────────────────── */
+
+const MS_PER_KMH = 1 / 3.6;
+
+/** u/v (m/s) from a meteorological speed (km/h) and from-direction (deg). */
+function uv(speedKmh, dirDeg) {
+  const s = speedKmh * MS_PER_KMH;
+  const r = (dirDeg * Math.PI) / 180;
+  return [-s * Math.sin(r), -s * Math.cos(r)];
+}
+
+/** A coarse global grid of Open-Meteo points, north to south, 12° spacing
+ * (390 points: one request stays under Open-Meteo's per-minute budget). */
+function omGrid(step = 12, north = 72, south = -72) {
+  const lats = [];
+  const lons = [];
+  for (let la = north; la >= south; la -= step)
+    for (let lo = -180; lo < 180; lo += step) {
+      lats.push(la);
+      lons.push(lo);
+    }
+  return {
+    lats,
+    lons,
+    nx: 360 / step,
+    ny: (north - south) / step + 1,
+    lo1: -180,
+    la1: north,
+    dx: step,
+    dy: step,
+  };
+}
+
+const OM_CACHE_MS = 60 * 60_000;
+
+/** Grids persist per browser for an hour: Open-Meteo counts every point. */
+function readGridCache(key) {
+  try {
+    const raw = localStorage.getItem(key);
+    if (!raw) return null;
+    const j = JSON.parse(raw);
+    if (Date.now() - j.at > OM_CACHE_MS) return null;
+    const dec = (b64) =>
+      new Float32Array(
+        Uint8Array.from(atob(b64), (c) => c.charCodeAt(0)).buffer,
+      );
+    return {
+      field: { ...j.grid, u: dec(j.u), v: dec(j.v) },
+      speed: dec(j.s),
+      time: j.time,
+    };
+  } catch {
+    return null;
+  }
+}
+
+function writeGridCache(key, value) {
+  try {
+    const enc = (arr) =>
+      btoa(String.fromCharCode(...new Uint8Array(arr.buffer)));
+    const { u, v, ...grid } = value.field;
+    localStorage.setItem(
+      key,
+      JSON.stringify({
+        at: Date.now(),
+        time: value.time,
+        grid,
+        u: enc(u),
+        v: enc(v),
+        s: enc(value.speed),
+      }),
+    );
+  } catch {
+    /* storage full or blocked */
+  }
+}
+
+async function openMeteoField(opts = {}) {
+  const key = `gev-om-grid:${opts.hourlyLevel || '10m'}:${opts.step || 12}`;
+  const cached = readGridCache(key);
+  if (cached) return cached;
+  const value = await fetchOpenMeteoField(opts);
+  writeGridCache(key, value);
+  return value;
+}
+
+async function fetchOpenMeteoField({ hourlyLevel = null, step = 12 } = {}) {
+  const g = omGrid(step);
+  const vars = hourlyLevel
+    ? `hourly=wind_speed_${hourlyLevel},wind_direction_${hourlyLevel}&forecast_hours=1`
+    : 'current=wind_speed_10m,wind_direction_10m';
+  // Three parallel chunks: a cold pressure-level request for the whole grid
+  // can take Open-Meteo half a minute; thirds come back in seconds.
+  const chunk = Math.ceil(g.lats.length / 3);
+  const parts = await Promise.all(
+    [0, 1, 2].map((k) => {
+      const la = g.lats.slice(k * chunk, (k + 1) * chunk);
+      const lo = g.lons.slice(k * chunk, (k + 1) * chunk);
+      return getJson(
+        `https://api.open-meteo.com/v1/forecast?latitude=${la.join(',')}&longitude=${lo.join(',')}&${vars}&timezone=GMT`,
+        { timeoutMs: 45_000 },
+      );
+    }),
+  );
+  const rows = parts.flat();
+  if (rows.length !== g.lats.length)
+    throw new FeedError('Malformed Open-Meteo wind grid');
+  const n = rows.length;
+  const u = new Float32Array(n);
+  const v = new Float32Array(n);
+  const speed = new Float32Array(n);
+  let time = null;
+  for (let i = 0; i < n; i++) {
+    const r = rows[i];
+    const s = hourlyLevel
+      ? r.hourly?.[`wind_speed_${hourlyLevel}`]?.[0]
+      : r.current?.wind_speed_10m;
+    const d = hourlyLevel
+      ? r.hourly?.[`wind_direction_${hourlyLevel}`]?.[0]
+      : r.current?.wind_direction_10m;
+    time ??= hourlyLevel ? r.hourly?.time?.[0] : r.current?.time;
+    if (!Number.isFinite(s) || !Number.isFinite(d)) continue;
+    [u[i], v[i]] = uv(s, d);
+    speed[i] = s * MS_PER_KMH;
+  }
+  return {
+    field: {
+      u,
+      v,
+      nx: g.nx,
+      ny: g.ny,
+      lo1: g.lo1,
+      la1: g.la1,
+      dx: g.dx,
+      dy: g.dy,
+    },
+    speed,
+    time: time ? Date.parse(`${time}Z`) : Date.now(),
+  };
+}
+
+/**
+ * Surface (10 m) wind: the app's GFS grid when the server can decode it,
+ * otherwise a 12° Open-Meteo grid (GFS/ICON blend, keyless).
+ */
+export function createWindFeed() {
+  return createFeed(
+    'wind',
+    async () => {
+      try {
+        const m = await getJson('/api/wind/manifest?model=gfs', {
+          cache: 'no-store',
+          timeoutMs: 45_000,
+        });
+        if (!m?.unavailable && m?.grid && m?.gridUrl) {
+          const response = await fetch(m.gridUrl);
+          if (response.ok) {
+            const count = m.grid.nx * m.grid.ny;
+            const values = new Float32Array(await response.arrayBuffer());
+            if (values.length >= count * 2) {
+              const u = values.slice(0, count);
+              const v = values.slice(count, count * 2);
+              return {
+                data: {
+                  field: { ...m.grid, u, v },
+                  level: '10 m',
+                  time: m.fetchedAt || Date.now(),
+                  source: 'NOAA GFS 10 m wind',
+                },
+              };
+            }
+          }
+        }
+      } catch {
+        /* fall through to Open-Meteo */
+      }
+      const om = await openMeteoField();
+      return {
+        data: {
+          ...om,
+          level: '10 m',
+          source: 'Open-Meteo forecast API (12° grid)',
+        },
+      };
+    },
+    { ttlMs: 60 * 60_000 },
+  );
+}
+
+/** Jet stream: Open-Meteo 250 hPa (≈ FL340) wind on a 12° grid. */
+export function createJetFeed() {
+  return createFeed(
+    'jet',
+    async () => {
+      const om = await openMeteoField({ hourlyLevel: '250hPa' });
+      return {
+        data: {
+          ...om,
+          level: '250 hPa',
+          source: 'Open-Meteo forecast API · 250 hPa (12° grid)',
+        },
+      };
+    },
+    { ttlMs: 2 * 3600_000 },
+  );
+}
+
+/** One point's current 10 m wind (for smoke plumes). */
+export const pointWind = createKeyedFeed(
+  'point-wind',
+  async ({ lon, lat }) => {
+    // The app's own regional weather route first (server-side, cached).
+    try {
+      const r = await getJson(
+        `/api/weather-effects?latitude=${lat.toFixed(2)}&longitude=${lon.toFixed(2)}`,
+        { timeoutMs: 15_000 },
+      );
+      const w = r?.weather;
+      if (Number.isFinite(w?.windKph) && Number.isFinite(w?.windDirectionDeg))
+        return {
+          speedKmh: w.windKph,
+          fromDeg: w.windDirectionDeg,
+          gustKmh: null,
+          time: Date.parse(w.observedAt) || Date.now(),
+          source: 'Open-Meteo via /api/weather-effects',
+        };
+    } catch {
+      /* direct below */
+    }
+    const j = await getJson(
+      `https://api.open-meteo.com/v1/forecast?latitude=${lat.toFixed(2)}&longitude=${lon.toFixed(2)}&current=wind_speed_10m,wind_direction_10m,wind_gusts_10m&timezone=GMT`,
+    );
+    const c = j?.current;
+    if (!Number.isFinite(c?.wind_speed_10m))
+      throw new FeedError('No point wind');
+    return {
+      speedKmh: c.wind_speed_10m,
+      fromDeg: c.wind_direction_10m,
+      gustKmh: c.wind_gusts_10m,
+      time: Date.parse(`${c.time}Z`),
+      source: 'Open-Meteo',
+    };
+  },
+  { ttlMs: 30 * 60_000, max: 64 },
+);
+
+/** Bilinear sample of a north-to-south, seam-wrapped field. */
+export function sampleField(field, lon, lat) {
+  const { u, v, nx, ny, lo1, la1, dx, dy } = field;
+  const x = ((((lon - lo1) % 360) + 360) % 360) / dx;
+  const y = Math.max(0, Math.min(ny - 1, (la1 - lat) / dy));
+  const x0 = Math.floor(x);
+  const y0 = Math.floor(y);
+  const tx = x - x0;
+  const ty = y - y0;
+  const x1 = (x0 + 1) % nx;
+  const y1 = Math.min(ny - 1, y0 + 1);
+  const at = (arr, xi, yi) => arr[yi * nx + (xi % nx)];
+  const lerp = (arr) =>
+    (at(arr, x0, y0) * (1 - tx) + at(arr, x1, y0) * tx) * (1 - ty) +
+    (at(arr, x0, y1) * (1 - tx) + at(arr, x1, y1) * tx) * ty;
+  return { u: lerp(u), v: lerp(v) };
+}
+
+/* ───────────────────────── NHC wind radii ───────────────────────── */
+
+const NM_KM = 1.852;
+
+/** Parse an NHC TCM (forecast/advisory) for the current position's radii. */
+export function parseTcm(text) {
+  if (typeof text !== 'string') return null;
+  const name =
+    /(?:HURRICANE|TROPICAL STORM|TROPICAL DEPRESSION|SUBTROPICAL STORM|POST-TROPICAL CYCLONE|POTENTIAL TROPICAL CYCLONE)\s+([A-Z-]+)/.exec(
+      text,
+    )?.[1];
+  const center =
+    /CENTER LOCATED NEAR\s+(\d+\.\d)([NS])\s+(\d+\.\d)([EW])\s+AT\s+(\d\d)\/(\d\d)(\d\d)Z/.exec(
+      text,
+    );
+  if (!center) return null;
+  const lat = Number(center[1]) * (center[2] === 'S' ? -1 : 1);
+  const lon = Number(center[3]) * (center[4] === 'W' ? -1 : 1);
+  // The first radii block after "MAX SUSTAINED WINDS" is the current one.
+  const block = text.split(/MAX SUSTAINED WINDS/)[1]?.split(/REPEAT\.\.\./)[0];
+  const radii = [];
+  for (const m of (block || '').matchAll(
+    /(\d\d) KT\.+\s*(\d+)NE\s+(\d+)SE\s+(\d+)SW\s+(\d+)NW/g,
+  )) {
+    radii.push({
+      kt: Number(m[1]),
+      // NE, SE, SW, NW in km
+      quadrantsKm: [m[2], m[3], m[4], m[5]].map((x) => Number(x) * NM_KM),
+    });
+  }
+  const pressure = /MINIMUM CENTRAL PRESSURE\s+(\d+) MB/.exec(text)?.[1];
+  const maxWind = /MAX SUSTAINED WINDS\s+(\d+) KT/.exec(block ? text : '')?.[1];
+  return {
+    name: name || null,
+    lat,
+    lon,
+    radii,
+    pressureHpa: pressure ? Number(pressure) : null,
+    windKt: maxWind ? Number(maxWind) : null,
+  };
+}
+
+/** Latest TCM per active storm from api.weather.gov (CORS-enabled, keyless). */
+export function createTcmFeed() {
+  return createFeed(
+    'nhc-tcm',
+    async () => {
+      const list = await getJson('https://api.weather.gov/products/types/TCM', {
+        headers: { Accept: 'application/ld+json' },
+      });
+      const graph = list?.['@graph'] || [];
+      const now = Date.now();
+      const latest = new Map();
+      for (const p of graph) {
+        const t = Date.parse(p.issuanceTime);
+        if (!Number.isFinite(t) || now - t > 18 * 3600_000) continue;
+        const key = p.wmoCollectiveId;
+        if (!latest.has(key)) latest.set(key, p);
+      }
+      const storms = [];
+      await Promise.all(
+        [...latest.values()].slice(0, 8).map(async (p) => {
+          try {
+            const prod = await getJson(
+              `https://api.weather.gov/products/${p.id}`,
+              { headers: { Accept: 'application/ld+json' } },
+            );
+            const parsed = parseTcm(prod?.productText);
+            if (parsed)
+              storms.push({
+                ...parsed,
+                issuedAt: Date.parse(p.issuanceTime),
+                wmo: p.wmoCollectiveId,
+              });
+          } catch {
+            /* one advisory failing drops only its radii */
+          }
+        }),
+      );
+      return {
+        data: {
+          storms,
+          source: 'NOAA NHC forecast/advisory via api.weather.gov',
+        },
+      };
+    },
+    { ttlMs: 30 * 60_000 },
+  );
+}
+
+/* ───────────────────────── GNSS integrity ───────────────────────── */
+
+/** Well-known interference regions worth sampling (anchors, whole degrees). */
+export const GNSS_ANCHORS = Object.freeze([
+  { id: 'baltic', name: 'Baltic Sea', lat: 56, lon: 21 },
+  { id: 'black-sea', name: 'Black Sea', lat: 45, lon: 33 },
+  { id: 'levant', name: 'Eastern Mediterranean', lat: 34, lon: 34 },
+  { id: 'gulf', name: 'Persian Gulf', lat: 27, lon: 52 },
+  { id: 'finland', name: 'Gulf of Finland', lat: 60, lon: 26 },
+]);
+
+/** A cell is "anomalous" by the gpsjam band formula on aircraft counts. */
+function gnssCells(rows, cellDeg = 0.5) {
+  const cells = new Map();
+  for (const r of rows) {
+    const key = `${Math.floor(r.lat / cellDeg)}:${Math.floor(r.lon / cellDeg)}`;
+    let c = cells.get(key);
+    if (!c)
+      cells.set(
+        key,
+        (c = {
+          lat: (Math.floor(r.lat / cellDeg) + 0.5) * cellDeg,
+          lon: (Math.floor(r.lon / cellDeg) + 0.5) * cellDeg,
+          total: 0,
+          bad: 0,
+        }),
+      );
+    c.total++;
+    if (r.degraded || r.gpsLost) c.bad++;
+  }
+  const out = [];
+  for (const c of cells.values()) {
+    if (c.total < 3) continue;
+    c.percent = (100 * Math.max(0, c.bad - 1)) / c.total;
+    c.level = c.percent >= 10 ? 'high' : c.percent >= 2 ? 'medium' : 'low';
+    out.push(c);
+  }
+  return out;
+}
+
+export const gnssIntegrity = createKeyedFeed(
+  'gnss',
+  async ({ lat, lon }) => {
+    const j = await getJson(
+      `/api/gnss-integrity?lat=${Math.round(lat)}&lon=${Math.round(lon)}`,
+      { cache: 'no-store' },
+    );
+    if (!Array.isArray(j?.rows)) throw new FeedError('Malformed GNSS snapshot');
+    const rows = j.rows.filter(
+      (r) => Number.isFinite(r.lat) && Number.isFinite(r.lon),
+    );
+    return {
+      anchor: j.anchor,
+      rows,
+      cells: gnssCells(rows),
+      degraded: rows.filter((r) => r.degraded || r.gpsLost).length,
+      fetchedAt: j.fetchedAt || Date.now(),
+      source: 'adsb.lol NIC/NACp via /api/gnss-integrity',
+    };
+  },
+  { ttlMs: 2 * 60_000, max: 24 },
+);
+
+/* ───────────────────────── Transit ───────────────────────── */
+
+export function createTransitCatalogFeed() {
+  return createFeed(
+    'transit-feeds',
+    async () => {
+      const j = await getJson('/api/transit/feeds');
+      if (!Array.isArray(j?.feeds)) throw new FeedError('No transit catalog');
+      return { data: { feeds: j.feeds, source: 'GTFS-realtime agencies' } };
+    },
+    { ttlMs: 6 * 3600_000 },
+  );
+}
+
+export const transitVehicles = createKeyedFeed(
+  'transit',
+  async (feedId) => {
+    const j = await getJson(
+      `/api/transit/vehicles/${encodeURIComponent(feedId)}`,
+      { cache: 'no-store' },
+    );
+    if (!Array.isArray(j?.vehicles)) throw new FeedError('No vehicles');
+    return {
+      feedId,
+      name: j.name,
+      fetchedAt: j.fetchedAt,
+      vehicles: j.vehicles
+        .filter((v) => Number.isFinite(v.lat) && Number.isFinite(v.lon))
+        .map((v) => ({
+          id: String(v.id),
+          lat: v.lat,
+          lon: v.lon,
+          bearing: finite(v.bearing),
+          speedMps: finite(v.speedMps),
+          routeId: v.routeId || '',
+          status: v.status || '',
+          t: (v.timestamp || 0) * 1000,
+        })),
+    };
+  },
+  { ttlMs: 20_000, max: 8 },
+);
+
+/* ───────────────────────── Air quality ───────────────────────── */
+
+export const AQ_CITIES = Object.freeze([
+  ['Delhi', 77.21, 28.61],
+  ['Lahore', 74.35, 31.55],
+  ['Dhaka', 90.41, 23.81],
+  ['Kolkata', 88.36, 22.57],
+  ['Mumbai', 72.88, 19.08],
+  ['Beijing', 116.4, 39.9],
+  ['Shanghai', 121.47, 31.23],
+  ['Chengdu', 104.07, 30.67],
+  ['Seoul', 126.98, 37.57],
+  ['Tokyo', 139.69, 35.69],
+  ['Bangkok', 100.5, 13.76],
+  ['Hanoi', 105.85, 21.03],
+  ['Jakarta', 106.85, -6.21],
+  ['Manila', 120.98, 14.6],
+  ['Karachi', 67.01, 24.86],
+  ['Tehran', 51.39, 35.69],
+  ['Riyadh', 46.68, 24.71],
+  ['Cairo', 31.24, 30.04],
+  ['Lagos', 3.38, 6.52],
+  ['Kinshasa', 15.27, -4.44],
+  ['Johannesburg', 28.05, -26.2],
+  ['Istanbul', 28.98, 41.01],
+  ['Moscow', 37.62, 55.76],
+  ['Warsaw', 21.01, 52.23],
+  ['Paris', 2.35, 48.86],
+  ['London', -0.13, 51.51],
+  ['Madrid', -3.7, 40.42],
+  ['Milan', 9.19, 45.46],
+  ['New York', -74.01, 40.71],
+  ['Los Angeles', -118.24, 34.05],
+  ['Mexico City', -99.13, 19.43],
+  ['Chicago', -87.63, 41.88],
+  ['Houston', -95.37, 29.76],
+  ['São Paulo', -46.63, -23.55],
+  ['Lima', -77.04, -12.05],
+  ['Santiago', -70.67, -33.45],
+  ['Bogotá', -74.07, 4.71],
+  ['Sydney', 151.21, -33.87],
+  ['Ulaanbaatar', 106.92, 47.89],
+  ['Kathmandu', 85.32, 27.72],
+]);
+
+export function createAirQualityFeed() {
+  return createFeed(
+    'air-quality',
+    async () => {
+      const lats = AQ_CITIES.map((c) => c[2]).join(',');
+      const lons = AQ_CITIES.map((c) => c[1]).join(',');
+      const rows = await getJson(
+        `https://air-quality-api.open-meteo.com/v1/air-quality?latitude=${lats}&longitude=${lons}&current=us_aqi_pm2_5,pm2_5&hourly=pm2_5&past_days=1&forecast_days=1&timezone=GMT`,
+        { timeoutMs: 40_000 },
+      );
+      const list = Array.isArray(rows) ? rows : [rows];
+      if (list.length !== AQ_CITIES.length)
+        throw new FeedError('Malformed air-quality response');
+      const now = Date.now();
+      const records = [];
+      list.forEach((r, i) => {
+        const aqi = r?.current?.us_aqi_pm2_5;
+        if (!Number.isFinite(aqi)) return;
+        const times = r.hourly?.time || [];
+        const pm = r.hourly?.pm2_5 || [];
+        const series = [];
+        for (let k = 0; k < times.length; k++) {
+          const t = Date.parse(`${times[k]}Z`);
+          if (t <= now && now - t <= 26 * 3600_000 && Number.isFinite(pm[k]))
+            series.push({ t, v: pm[k] });
+        }
+        records.push({
+          id: `aq-${AQ_CITIES[i][0]}`,
+          name: AQ_CITIES[i][0],
+          lon: AQ_CITIES[i][1],
+          lat: AQ_CITIES[i][2],
+          aqi,
+          pm25: r.current.pm2_5,
+          series,
+          t: Date.parse(`${r.current.time}Z`),
+        });
+      });
+      if (!records.length) throw new FeedError('No air-quality values');
+      return {
+        data: {
+          records,
+          source: 'Open-Meteo Air Quality API (CAMS forecast model)',
+        },
+      };
+    },
+    { ttlMs: 60 * 60_000 },
+  );
+}
+
+export function aqiColor(aqi) {
+  if (aqi <= 50) return '#5BD46B';
+  if (aqi <= 100) return '#F2D33B';
+  if (aqi <= 150) return '#FF9A3D';
+  if (aqi <= 200) return '#FF4D4D';
+  if (aqi <= 300) return '#B04DFF';
+  return '#8C1A3A';
+}
+
+/* ───────────────────────── Regional ADS-B ───────────────────────── */
+
+/**
+ * The flights proxy answers with OpenSky's global snapshot, or (when
+ * OpenSky is down) a 250 nm adsb.lol snapshot around the anchor. Either way
+ * the records near the anchor are real; this cache keeps one per anchor.
+ */
+export function createRegionalFlights(flightFromState) {
+  return createKeyedFeed(
+    'regional-flights',
+    async ({ lat, lon }) => {
+      const j = await getJson(
+        `/api/flights?lat=${lat.toFixed(3)}&lon=${lon.toFixed(3)}`,
+        { cache: 'no-store', timeoutMs: 30_000 },
+      );
+      if (!Array.isArray(j?.states))
+        throw new FeedError('Malformed flight snapshot');
+      const records = [];
+      for (const s of j.states) {
+        const r = flightFromState(s);
+        if (r) records.push(r);
+      }
+      return { records, time: (j.time || 0) * 1000 };
+    },
+    { ttlMs: 30_000, max: 12 },
+  );
+}
diff --git a/mobile/globe/gazetteer.js b/mobile/globe/gazetteer.js
new file mode 100644
index 000000000..183ce8a0c
--- /dev/null
+++ b/mobile/globe/gazetteer.js
@@ -0,0 +1,247 @@
+/**
+ * A small bundled gazetteer for naming where something is ("38 km SW of
+ * Miami"). Coordinates are public city centres, rounded.
+ */
+import { haversineKm } from './geo.js';
+
+/** US metros (radar coverage) — [name, lon, lat]. */
+export const US_METROS = Object.freeze([
+  ['New York', -74.01, 40.71],
+  ['Los Angeles', -118.24, 34.05],
+  ['Chicago', -87.63, 41.88],
+  ['Houston', -95.37, 29.76],
+  ['Phoenix', -112.07, 33.45],
+  ['Philadelphia', -75.17, 39.95],
+  ['San Antonio', -98.49, 29.42],
+  ['San Diego', -117.16, 32.72],
+  ['Dallas', -96.8, 32.78],
+  ['Austin', -97.74, 30.27],
+  ['Jacksonville', -81.66, 30.33],
+  ['Columbus', -83.0, 39.96],
+  ['Charlotte', -80.84, 35.23],
+  ['Indianapolis', -86.16, 39.77],
+  ['San Francisco', -122.42, 37.77],
+  ['Seattle', -122.33, 47.61],
+  ['Denver', -104.99, 39.74],
+  ['Washington', -77.04, 38.9],
+  ['Nashville', -86.78, 36.16],
+  ['Oklahoma City', -97.52, 35.47],
+  ['El Paso', -106.49, 31.76],
+  ['Boston', -71.06, 42.36],
+  ['Portland', -122.68, 45.52],
+  ['Las Vegas', -115.14, 36.17],
+  ['Detroit', -83.05, 42.33],
+  ['Memphis', -90.05, 35.15],
+  ['Louisville', -85.76, 38.25],
+  ['Baltimore', -76.61, 39.29],
+  ['Milwaukee', -87.91, 43.04],
+  ['Albuquerque', -106.65, 35.08],
+  ['Tucson', -110.97, 32.22],
+  ['Atlanta', -84.39, 33.75],
+  ['Kansas City', -94.58, 39.1],
+  ['Miami', -80.19, 25.76],
+  ['Tampa', -82.46, 27.95],
+  ['Orlando', -81.38, 28.54],
+  ['New Orleans', -90.07, 29.95],
+  ['Minneapolis', -93.27, 44.98],
+  ['Cleveland', -81.69, 41.5],
+  ['St. Louis', -90.2, 38.63],
+  ['Pittsburgh', -79.99, 40.44],
+  ['Cincinnati', -84.51, 39.1],
+  ['Raleigh', -78.64, 35.78],
+  ['Salt Lake City', -111.89, 40.76],
+  ['Birmingham', -86.8, 33.52],
+  ['Omaha', -95.94, 41.26],
+  ['Buffalo', -78.88, 42.89],
+  ['Richmond', -77.44, 37.54],
+  ['Corpus Christi', -97.4, 27.8],
+  ['Mobile', -88.04, 30.69],
+  ['Little Rock', -92.29, 34.75],
+  ['Des Moines', -93.61, 41.59],
+  ['Wichita', -97.34, 37.69],
+  ['Boise', -116.2, 43.62],
+  ['Spokane', -117.43, 47.66],
+  ['Billings', -108.5, 45.78],
+  ['Fargo', -96.79, 46.88],
+  ['Charleston', -79.93, 32.78],
+  ['Savannah', -81.1, 32.08],
+  ['Tallahassee', -84.28, 30.44],
+  ['Shreveport', -93.75, 32.53],
+  ['Amarillo', -101.83, 35.22],
+  ['Lubbock', -101.86, 33.58],
+  ['Brownsville', -97.5, 25.9],
+  ['Key West', -81.78, 24.56],
+]);
+
+/** World places and seas for "near X" phrasing — [name, lon, lat]. */
+export const WORLD_PLACES = Object.freeze([
+  ...US_METROS,
+  ['Toronto', -79.38, 43.65],
+  ['Montréal', -73.57, 45.5],
+  ['Vancouver', -123.12, 49.28],
+  ['Calgary', -114.07, 51.05],
+  ['Mexico City', -99.13, 19.43],
+  ['Guadalajara', -103.35, 20.67],
+  ['Monterrey', -100.31, 25.69],
+  ['Mérida', -89.62, 20.97],
+  ['Cancún', -86.85, 21.16],
+  ['Puerto Vallarta', -105.23, 20.65],
+  ['Mazatlán', -106.41, 23.25],
+  ['Cabo San Lucas', -109.92, 22.89],
+  ['Acapulco', -99.88, 16.85],
+  ['Guatemala City', -90.51, 14.63],
+  ['San José', -84.09, 9.93],
+  ['Panama City', -79.52, 8.98],
+  ['Havana', -82.37, 23.11],
+  ['Santo Domingo', -69.93, 18.49],
+  ['San Juan', -66.1, 18.47],
+  ['Kingston', -76.79, 18.02],
+  ['Caracas', -66.9, 10.48],
+  ['Bogotá', -74.07, 4.71],
+  ['Medellín', -75.56, 6.24],
+  ['Quito', -78.47, -0.18],
+  ['Lima', -77.04, -12.05],
+  ['Manaus', -60.02, -3.12],
+  ['Belém', -48.5, -1.46],
+  ['Brasília', -47.88, -15.79],
+  ['São Paulo', -46.63, -23.55],
+  ['Rio de Janeiro', -43.17, -22.91],
+  ['Buenos Aires', -58.38, -34.6],
+  ['Santiago', -70.67, -33.45],
+  ['La Paz', -68.15, -16.5],
+  ['Asunción', -57.58, -25.26],
+  ['Reykjavík', -21.9, 64.15],
+  ['London', -0.13, 51.51],
+  ['Paris', 2.35, 48.86],
+  ['Madrid', -3.7, 40.42],
+  ['Lisbon', -9.14, 38.72],
+  ['Rome', 12.5, 41.9],
+  ['Berlin', 13.4, 52.52],
+  ['Warsaw', 21.01, 52.23],
+  ['Stockholm', 18.07, 59.33],
+  ['Helsinki', 24.94, 60.17],
+  ['Tallinn', 24.75, 59.44],
+  ['Riga', 24.11, 56.95],
+  ['Vilnius', 25.28, 54.69],
+  ['Kaliningrad', 20.51, 54.71],
+  ['Gdańsk', 18.65, 54.35],
+  ['St Petersburg', 30.32, 59.94],
+  ['Moscow', 37.62, 55.76],
+  ['Kyiv', 30.52, 50.45],
+  ['Odesa', 30.73, 46.48],
+  ['Sevastopol', 33.52, 44.62],
+  ['Istanbul', 28.98, 41.01],
+  ['Athens', 23.73, 37.98],
+  ['Nicosia', 33.38, 35.19],
+  ['Beirut', 35.5, 33.89],
+  ['Tel Aviv', 34.78, 32.09],
+  ['Damascus', 36.29, 33.51],
+  ['Cairo', 31.24, 30.04],
+  ['Baghdad', 44.36, 33.31],
+  ['Tehran', 51.39, 35.69],
+  ['Kuwait City', 47.98, 29.38],
+  ['Riyadh', 46.68, 24.71],
+  ['Doha', 51.53, 25.29],
+  ['Dubai', 55.27, 25.2],
+  ['Muscat', 58.4, 23.59],
+  ['Bandar Abbas', 56.27, 27.18],
+  ['Karachi', 67.01, 24.86],
+  ['Lahore', 74.35, 31.55],
+  ['Delhi', 77.21, 28.61],
+  ['Mumbai', 72.88, 19.08],
+  ['Chennai', 80.27, 13.08],
+  ['Kolkata', 88.36, 22.57],
+  ['Dhaka', 90.41, 23.81],
+  ['Kathmandu', 85.32, 27.72],
+  ['Colombo', 79.86, 6.93],
+  ['Yangon', 96.2, 16.87],
+  ['Bangkok', 100.5, 13.76],
+  ['Hanoi', 105.85, 21.03],
+  ['Ho Chi Minh City', 106.63, 10.82],
+  ['Kuala Lumpur', 101.69, 3.14],
+  ['Singapore', 103.82, 1.35],
+  ['Jakarta', 106.85, -6.21],
+  ['Surabaya', 112.75, -7.25],
+  ['Manila', 120.98, 14.6],
+  ['Cebu', 123.89, 10.32],
+  ['Davao', 125.61, 7.07],
+  ['Hong Kong', 114.17, 22.32],
+  ['Taipei', 121.56, 25.03],
+  ['Guangzhou', 113.26, 23.13],
+  ['Shanghai', 121.47, 31.23],
+  ['Beijing', 116.4, 39.9],
+  ['Seoul', 126.98, 37.57],
+  ['Busan', 129.08, 35.18],
+  ['Tokyo', 139.69, 35.69],
+  ['Osaka', 135.5, 34.69],
+  ['Okinawa', 127.68, 26.21],
+  ['Sapporo', 141.35, 43.06],
+  ['Guam', 144.79, 13.44],
+  ['Port Moresby', 147.18, -9.44],
+  ['Darwin', 130.84, -12.46],
+  ['Cairns', 145.77, -16.92],
+  ['Brisbane', 153.03, -27.47],
+  ['Sydney', 151.21, -33.87],
+  ['Melbourne', 144.96, -37.81],
+  ['Perth', 115.86, -31.95],
+  ['Auckland', 174.76, -36.85],
+  ['Suva', 178.44, -18.14],
+  ['Nouméa', 166.46, -22.28],
+  ['Honolulu', -157.86, 21.31],
+  ['Anchorage', -149.9, 61.22],
+  ['Lagos', 3.38, 6.52],
+  ['Accra', -0.19, 5.6],
+  ['Dakar', -17.47, 14.72],
+  ['Kinshasa', 15.27, -4.44],
+  ['Nairobi', 36.82, -1.29],
+  ['Addis Ababa', 38.75, 9.03],
+  ['Khartoum', 32.53, 15.5],
+  ['Johannesburg', 28.05, -26.2],
+  ['Cape Town', 18.42, -33.92],
+  ['Antananarivo', 47.52, -18.88],
+  ['Maputo', 32.57, -25.97],
+  ['Luanda', 13.23, -8.84],
+  ['Ulaanbaatar', 106.92, 47.89],
+  ['Almaty', 76.89, 43.24],
+  ['Novosibirsk', 82.93, 55.03],
+  ['Vladivostok', 131.89, 43.12],
+]);
+
+const DIRS = ['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW'];
+
+/** Compass bearing (deg) from a to b. */
+export function bearingDeg(lat1, lon1, lat2, lon2) {
+  const r = Math.PI / 180;
+  const y = Math.sin((lon2 - lon1) * r) * Math.cos(lat2 * r);
+  const x =
+    Math.cos(lat1 * r) * Math.sin(lat2 * r) -
+    Math.sin(lat1 * r) * Math.cos(lat2 * r) * Math.cos((lon2 - lon1) * r);
+  return (((Math.atan2(y, x) / r) % 360) + 360) % 360;
+}
+
+export function compass(deg) {
+  return DIRS[Math.round((((deg % 360) + 360) % 360) / 45) % 8];
+}
+
+/** Nearest bundled place: { name, km, dir } (dir is from the place). */
+export function nearestPlace(lat, lon, list = WORLD_PLACES) {
+  let best = null;
+  for (const [name, plon, plat] of list) {
+    const km = haversineKm(lat, lon, plat, plon);
+    if (!best || km < best.km) best = { name, km, plon, plat };
+  }
+  if (!best) return null;
+  return {
+    name: best.name,
+    km: Math.round(best.km),
+    dir: compass(bearingDeg(best.plat, best.plon, lat, lon)),
+  };
+}
+
+/** "Miami", "38 km SW of Miami" or "640 km E of Manila". */
+export function describePlace(lat, lon, list) {
+  const p = nearestPlace(lat, lon, list);
+  if (!p) return '';
+  if (p.km < 15) return p.name;
+  return `${p.km.toLocaleString('en-US')} km ${p.dir} of ${p.name}`;
+}
diff --git a/mobile/globe/glyphs.js b/mobile/globe/glyphs.js
index e4ab2fc4d..8a7219758 100644
--- a/mobile/globe/glyphs.js
+++ b/mobile/globe/glyphs.js
@@ -237,6 +237,117 @@ const painters = {
     ctx.strokeStyle = '#fff';
     ctx.stroke();
   },
+  bolt(ctx) {
+    ctx.beginPath();
+    ctx.moveTo(28, 3);
+    ctx.lineTo(12, 27);
+    ctx.lineTo(23, 27);
+    ctx.lineTo(19, 45);
+    ctx.lineTo(37, 18);
+    ctx.lineTo(26, 18);
+    ctx.closePath();
+    stroke(ctx, 3);
+  },
+  aq(ctx, s) {
+    const g = ctx.createRadialGradient(s / 2, s / 2, 4, s / 2, s / 2, s / 2);
+    g.addColorStop(0, 'rgba(255,255,255,0.9)');
+    g.addColorStop(0.45, 'rgba(255,255,255,0.45)');
+    g.addColorStop(1, 'rgba(255,255,255,0)');
+    ctx.fillStyle = g;
+    ctx.fillRect(0, 0, s, s);
+    ctx.beginPath();
+    ctx.arc(s / 2, s / 2, 9, 0, Math.PI * 2);
+    stroke(ctx, 3);
+  },
+  bus(ctx) {
+    ctx.beginPath();
+    ctx.moveTo(24, 4);
+    ctx.lineTo(33, 14);
+    ctx.lineTo(33, 42);
+    ctx.lineTo(15, 42);
+    ctx.lineTo(15, 14);
+    ctx.closePath();
+    stroke(ctx, 3);
+  },
+  post(ctx) {
+    ctx.beginPath();
+    ctx.moveTo(8, 10);
+    ctx.lineTo(40, 10);
+    ctx.lineTo(40, 32);
+    ctx.lineTo(22, 32);
+    ctx.lineTo(13, 41);
+    ctx.lineTo(14, 32);
+    ctx.lineTo(8, 32);
+    ctx.closePath();
+    stroke(ctx, 3);
+  },
+  witness(ctx) {
+    // a seal: a rosette with a check
+    ctx.beginPath();
+    for (let i = 0; i < 24; i++) {
+      const a = (i / 24) * Math.PI * 2;
+      const r = i % 2 ? 17 : 21;
+      ctx.lineTo(24 + r * Math.cos(a), 24 + r * Math.sin(a));
+    }
+    ctx.closePath();
+    stroke(ctx, 3);
+    ctx.beginPath();
+    ctx.moveTo(16, 24);
+    ctx.lineTo(22, 30);
+    ctx.lineTo(33, 18);
+    ctx.lineWidth = 4;
+    ctx.strokeStyle = 'rgba(0,0,0,0.75)';
+    ctx.stroke();
+  },
+  eye(ctx) {
+    ctx.beginPath();
+    ctx.moveTo(4, 24);
+    ctx.quadraticCurveTo(24, 4, 44, 24);
+    ctx.quadraticCurveTo(24, 44, 4, 24);
+    ctx.closePath();
+    stroke(ctx, 3);
+    ctx.beginPath();
+    ctx.arc(24, 24, 7, 0, Math.PI * 2);
+    ctx.fillStyle = 'rgba(0,0,0,0.7)';
+    ctx.fill();
+  },
+  live(ctx) {
+    ctx.beginPath();
+    ctx.arc(24, 24, 9, 0, Math.PI * 2);
+    stroke(ctx, 3);
+    for (const r of [15, 21]) {
+      ctx.beginPath();
+      ctx.arc(24, 24, r, -0.7, 0.7);
+      ctx.moveTo(24 - r * Math.cos(0.7), 24 - r * Math.sin(0.7));
+      ctx.arc(24, 24, r, Math.PI - 0.7, Math.PI + 0.7);
+      ctx.lineWidth = 3;
+      ctx.strokeStyle = '#fff';
+      ctx.stroke();
+    }
+  },
+  hologram(ctx) {
+    ctx.beginPath();
+    ctx.moveTo(24, 3);
+    ctx.lineTo(42, 14);
+    ctx.lineTo(42, 34);
+    ctx.lineTo(24, 45);
+    ctx.lineTo(6, 34);
+    ctx.lineTo(6, 14);
+    ctx.closePath();
+    ctx.lineWidth = 6;
+    ctx.strokeStyle = 'rgba(0,0,0,0.5)';
+    ctx.stroke();
+    ctx.lineWidth = 3;
+    ctx.strokeStyle = '#fff';
+    ctx.stroke();
+    ctx.beginPath();
+    ctx.moveTo(6, 14);
+    ctx.lineTo(24, 25);
+    ctx.lineTo(42, 14);
+    ctx.moveTo(24, 25);
+    ctx.lineTo(24, 45);
+    ctx.stroke();
+  },
 };
 
 /** `{ image, imageId }` for a named glyph. */
diff --git a/mobile/globe/index.js b/mobile/globe/index.js
index d443ebe3b..fb0380c27 100644
--- a/mobile/globe/index.js
+++ b/mobile/globe/index.js
@@ -6,6 +6,30 @@
  * an adaptive pixel-ratio governor, a single-full-res-pass post chain, and
  * live layers drawn with batched billboards and polylines (never Entities,
  * never Cesium labels).
+ *
+ * Round-two contract additions (full notes in ./API.md):
+ *
+ *   globe.setViewer({ lon, lat } | null) / globe.viewer()
+ *   globe.situations({ observer? }) → Promise<Situation[]>, each Situation now
+ *     also has band: 'orbit'|'sky'|'ground'|'inside',
+ *     archetype: 'sensor'|'eye'|'track'|'number', telemetry: string,
+ *     media?: { kind:'image', url, refreshMs, cameraId, headingDeg? },
+ *     series?: [{ t, v }], seriesLabel?, headline?: { value, unit, label },
+ *     distanceKm? (once a viewer is known)
+ *   globe.omitted() → [{ genre, reason }]   globe.timings() → { genre: ms }
+ *   globe.thumbnail(situation, { width=360, height=480, dpr=2 })
+ *     → Promise<string> (blob: URL of a composited JPEG; never the viewer)
+ *   globe.addPin({ id, lon, lat, kind:'post'|'witness'|'eye'|'live'|'hologram',
+ *     headingDeg?, fovDeg?, rangeM?, color?, label?, altM? }) → id
+ *   globe.removePin(id) → boolean      globe.pins() → Pin[]
+ *     'pick' → { kind:'pin', pinKind, id, title, subtitle, lon, lat, meta }
+ *   globe.nearestEye(lon, lat, km=50)
+ *     → Promise<{ id, title, lon, lat, distanceKm, headingDeg, fovDeg,
+ *                 imageUrl, city, provider } | null>
+ *   globe.eyeFrameUrl(cameraId) → string | null
+ *   labels() entries may carry `detail` ('CAT 2 · 85 KT · 974 HPA', 'SQ 7700')
+ *   New layers: radar, clouds, lightning, wind, jet, air-quality, gnss,
+ *     transit; cyclones gain a filled cone and NHC wind radii.
  */
 import * as Cesium from 'cesium';
 import { createImagery } from './imagery.js';
@@ -30,6 +54,19 @@ import {
   createTleFeed,
   createVesselsFeed,
 } from './feeds.js';
+import {
+  createAirQualityFeed,
+  createJetFeed,
+  createRegionalFlights,
+  createTcmFeed,
+  createTransitCatalogFeed,
+  createWeatherManifestFeed,
+  createWindFeed,
+} from './feedsWeather.js';
+import { cctvFrameUrl, flightFromState } from './feeds.js';
+import { createPins } from './pins.js';
+import { createCompositor } from './compositor.js';
+import { haversineKm } from './geo.js';
 import { applyModelAtmosphereWorkaround } from '../../src/app/atmosphereCompat.js';
 
 export { LENSES, FAMILIES };
@@ -46,6 +83,7 @@ export const DEFAULT_LAYERS = Object.freeze([
 
 const LABEL_PRIORITY = [
   'squawk',
+  'air-quality',
   'iss',
   'cyclones',
   'launches',
@@ -67,6 +105,7 @@ const LABEL_PRIORITY = [
 
 const PLANETARY_LABELS = new Set([
   'squawk',
+  'air-quality',
   'iss',
   'cyclones',
   'launches',
@@ -93,6 +132,14 @@ const DATA_CREDITS = {
   floods:
     'Bhote Koshi: GeoPera river centerline (CC BY-NC 4.0), Vantor (Maxar) Open Data',
   cctv: 'Cameras: public agency traffic camera feeds (see per-camera provider)',
+  radar: 'Radar: NOAA/NWS MRMS via nowCOAST',
+  clouds: 'Satellite IR: NOAA/NESDIS via nowCOAST',
+  lightning: 'Lightning: NOAA/NWS nowCOAST (Vaisala NLDN/GLD360)',
+  wind: 'Wind: NOAA GFS / Open-Meteo',
+  jet: 'Jet stream: Open-Meteo (250 hPa)',
+  'air-quality': 'Air quality: Open-Meteo / Copernicus CAMS',
+  gnss: 'GNSS integrity: adsb.lol (ODbL), gpsjam.org method',
+  transit: 'Transit: agency GTFS-realtime feeds (see per-feed credit)',
 };
 
 function viewerOptions(creditContainer, options) {
@@ -266,6 +313,15 @@ export async function createGlobe(container, options = {}) {
     cyclones: createCyclonesFeed(eonet),
     cctv: createCctvFeed(),
     flood: createFloodFeed(),
+    radar: createWeatherManifestFeed('radar'),
+    clouds: createWeatherManifestFeed('clouds'),
+    lightning: createWeatherManifestFeed('lightning'),
+    wind: createWindFeed(),
+    jet: createJetFeed(),
+    tcm: createTcmFeed(),
+    airQuality: createAirQualityFeed(),
+    transitCatalog: createTransitCatalogFeed(),
+    regionalFlights: createRegionalFlights(flightFromState),
   };
 
   let layersTimer = null;
@@ -285,6 +341,24 @@ export async function createGlobe(container, options = {}) {
     },
   };
   const layers = buildLayers(ctx, feeds);
+  const pins = createPins({ scene, requestRender });
+  const compositor = createCompositor({ feeds });
+  // Slow keyless sources warm in the background so the first feed has them.
+  setTimeout(() => {
+    for (const f of [
+      feeds.jet,
+      feeds.tcm,
+      feeds.airQuality,
+      feeds.cctv,
+      feeds.lightning,
+      feeds.radar,
+      feeds.clouds,
+    ])
+      f.get().catch(() => {});
+  }, 1500);
+  let viewerPos = opts.observer
+    ? { lon: opts.observer.lon, lat: opts.observer.lat }
+    : null;
 
   // ── Selection visuals ────────────────────────────────────────────
   const selectionRoot = scene.primitives.add(new Cesium.PrimitiveCollection());
@@ -437,7 +511,15 @@ export async function createGlobe(container, options = {}) {
   handler.setInputAction((movement) => {
     const picked = scene.pick(movement.position, 30, 30);
     const id = picked?.id;
-    if (id && typeof id === 'object' && id.layer && layers.has(id.layer)) {
+    if (id && typeof id === 'object' && id.layer === 'pins') {
+      if (selected) api.select(null);
+      emit('pick', pins.pick(id.key));
+    } else if (
+      id &&
+      typeof id === 'object' &&
+      id.layer &&
+      layers.has(id.layer)
+    ) {
       api.select({ layer: id.layer, id: id.key });
       emit('pick', selected?.pick ?? null);
     } else {
@@ -458,6 +540,7 @@ export async function createGlobe(container, options = {}) {
       drawSelection();
       moved = true;
     }
+    if (pins.tick()) moved = true;
     if (moved) requestRender();
   }, 1000);
 
@@ -751,10 +834,92 @@ export async function createGlobe(container, options = {}) {
     },
 
     situations(extra = {}) {
-      return buildSituations(
-        { feeds, timeMs },
-        { observer: extra.observer ?? opts.observer },
-      );
+      const observer = extra.observer ?? viewerPos ?? opts.observer;
+      return buildSituations({ feeds, timeMs }, { observer }).then((list) => {
+        if (observer && Number.isFinite(observer.lat))
+          for (const s of list)
+            s.distanceKm = Math.round(
+              haversineKm(observer.lat, observer.lon, s.lat, s.lon),
+            );
+        return list;
+      });
+    },
+
+    /** Genres the last situations() call left out, and why (for QA/UI). */
+    omitted() {
+      return buildSituations.lastOmitted || [];
+    },
+
+    /** Per-genre build times (ms since the feeds resolved) of the last call. */
+    timings() {
+      return buildSituations.lastTimings || {};
+    },
+
+    /** Where the person is (for distanceKm and "near you"); null clears. */
+    setViewer(pos) {
+      viewerPos =
+        pos && Number.isFinite(pos.lon) && Number.isFinite(pos.lat)
+          ? { lon: pos.lon, lat: pos.lat }
+          : null;
+      emit('viewer', viewerPos);
+    },
+
+    viewer() {
+      return viewerPos ? { ...viewerPos } : null;
+    },
+
+    /** Card compositor: Promise<object URL> (see API.md). */
+    thumbnail(situation, options) {
+      return compositor.thumbnail(situation, options);
+    },
+
+    addPin(pin) {
+      return pins.add(pin);
+    },
+
+    removePin(id) {
+      return pins.remove(id);
+    },
+
+    pins() {
+      return pins.list();
+    },
+
+    /** Nearest public camera within `km`, from the CCTV catalog. */
+    async nearestEye(lon, lat, km = 50) {
+      if (!Number.isFinite(lon) || !Number.isFinite(lat)) return null;
+      let data;
+      try {
+        data = await feeds.cctv.get();
+      } catch {
+        return null;
+      }
+      let best = null;
+      for (const c of data.records) {
+        if (Math.abs(c.lat - lat) > km / 100 + 0.5) continue;
+        const d = haversineKm(lat, lon, c.lat, c.lon);
+        if (d <= km && (!best || d < best.d)) best = { c, d };
+      }
+      if (!best) return null;
+      const c = best.c;
+      return {
+        id: c.id,
+        title: c.name,
+        lon: c.lon,
+        lat: c.lat,
+        distanceKm: Math.round(best.d * 100) / 100,
+        headingDeg: c.heading,
+        fovDeg: c.fovDeg,
+        imageUrl: cctvFrameUrl(c),
+        city: c.city,
+        provider: c.provider,
+      };
+    },
+
+    /** A fresh same-origin frame URL for a catalog camera (or null). */
+    eyeFrameUrl(cameraId) {
+      const c = feeds.cctv.data?.records.find((r) => r.id === cameraId);
+      return c ? cctvFrameUrl(c) : null;
     },
 
     credits() {
@@ -803,6 +968,7 @@ export async function createGlobe(container, options = {}) {
         if (!glyphs) continue;
         // Semantic zoom for words too: from orbit only the headline layers.
         if (planetary && !PLANETARY_LABELS.has(layer.id)) continue;
+        if (layer.id === 'lightning') continue; // the glow is the label
         const rank = LABEL_PRIORITY.indexOf(layer.id);
         for (let i = 0; i < glyphs.length; i++) {
           const bb = glyphs.get(i);
@@ -821,6 +987,19 @@ export async function createGlobe(container, options = {}) {
           });
         }
       }
+      for (let i = 0; i < pins.billboards.length; i++) {
+        const bb = pins.billboards.get(i);
+        if (!occluder.isPointVisible(bb.position)) continue;
+        const p = scene.cartesianToCanvasCoordinates(bb.position, scratch);
+        if (!p || p.x < 0 || p.y < 0 || p.x > w || p.y > h) continue;
+        candidates.push({
+          layer: { id: 'pins', pick: (key) => pins.pick(key) },
+          key: bb.id.key,
+          x: p.x,
+          y: p.y,
+          score: -50,
+        });
+      }
       candidates.sort((a, b) => a.score - b.score);
       // Greedy placement: a label never overlaps one already placed.
       const placed = [];
@@ -854,6 +1033,8 @@ export async function createGlobe(container, options = {}) {
           layer: c.layer.id,
           kind: pick.kind,
           title: pick.title,
+          ...(pick.labelDetail ? { detail: pick.labelDetail } : {}),
+          ...(pick.pinKind ? { pinKind: pick.pinKind } : {}),
           x: c.x,
           y: c.y,
         });
@@ -886,6 +1067,8 @@ export async function createGlobe(container, options = {}) {
       removeMoveEnd();
       handler.destroy();
       for (const layer of layers.values()) layer.destroy();
+      pins.destroy();
+      compositor.destroy();
       governor.destroy();
       post.destroy();
       viewer.destroy();
diff --git a/mobile/globe/layers/air.js b/mobile/globe/layers/air.js
index b516d1126..05ff40c65 100644
--- a/mobile/globe/layers/air.js
+++ b/mobile/globe/layers/air.js
@@ -176,6 +176,7 @@ export class AircraftLayer extends Layer {
         .join(' · '),
       lon,
       lat,
+      ...(r.emergency ? { labelDetail: `SQ ${r.squawk}` } : {}),
       meta: {
         layer: this.id,
         icao24: r.id,
diff --git a/mobile/globe/layers/catalog.js b/mobile/globe/layers/catalog.js
index 615e2bfb0..a16f9dc62 100644
--- a/mobile/globe/layers/catalog.js
+++ b/mobile/globe/layers/catalog.js
@@ -8,6 +8,7 @@ import { createSkyLayers } from './air.js';
 import { createOrbitLayers } from './orbit.js';
 import { createHazardLayers } from './hazards.js';
 import { createSeaLayers, createEyesLayers } from './sea.js';
+import { createWeatherLayers } from './weather.js';
 
 export const FAMILIES = Object.freeze([
   'Sky',
@@ -62,7 +63,8 @@ export const CATALOG = Object.freeze([
   ['Weather', 'radar', 'Radar'],
   ['Weather', 'clouds', 'Clouds'],
   ['Weather', 'lightning', 'Lightning'],
-  ['Weather', 'wind', 'Wind'],
+  ['Weather', 'wind', 'Wind (10 m)'],
+  ['Weather', 'jet', 'Jet stream (250 hPa)'],
   ['Weather', 'forecast', 'Forecast models'],
   ['Infra', 'datacenters', 'Datacenters'],
   ['Infra', 'dams', 'Dams'],
@@ -81,6 +83,7 @@ export function buildLayers(ctx, feeds) {
     ...createOrbitLayers(ctx, feeds),
     ...createHazardLayers(ctx, feeds),
     ...createEyesLayers(ctx, feeds),
+    ...createWeatherLayers(ctx, feeds),
   ])
     live.set(layer.id, layer);
   const out = new Map();
diff --git a/mobile/globe/layers/hazards.js b/mobile/globe/layers/hazards.js
index 782550496..fbe724d9b 100644
--- a/mobile/globe/layers/hazards.js
+++ b/mobile/globe/layers/hazards.js
@@ -224,7 +224,7 @@ export function createHazardLayers(ctx, feeds) {
   return [
     quakes,
     fires,
-    new CycloneLayer(ctx, { feed: feeds.cyclones }),
+    new CycloneLayer(ctx, { feed: feeds.cyclones, tcm: feeds.tcm }),
     new FloodLayer(ctx, { feed: feeds.flood }),
     volcanoes,
   ];
@@ -255,8 +255,55 @@ export function stormPositionAt(storm, ms) {
   return null; // beyond the forecast
 }
 
+const SAFFIR = [
+  [137, 'CAT 5'],
+  [113, 'CAT 4'],
+  [96, 'CAT 3'],
+  [83, 'CAT 2'],
+  [64, 'CAT 1'],
+  [34, 'TS'],
+  [0, 'TD'],
+];
+
+/** Saffir-Simpson category (or TS/TD) for a 1-min sustained wind in kt. */
+export function stormCategory(windKt) {
+  if (!Number.isFinite(windKt)) return '';
+  return SAFFIR.find(([kt]) => windKt >= kt)[1];
+}
+
+/** Ring of a quadrant wind-radii shape ([NE, SE, SW, NW] km) around a point. */
+export function radiiRing(lon, lat, quadrantsKm, stepDeg = 6) {
+  const ring = [];
+  const cosLat = Math.max(0.05, Math.cos((lat * Math.PI) / 180));
+  for (let a = 0; a <= 360; a += stepDeg) {
+    const q = Math.min(3, Math.floor((a % 360) / 90));
+    const r = quadrantsKm[q];
+    const rad = (a * Math.PI) / 180;
+    ring.push([
+      lon + (r * Math.sin(rad)) / (111.32 * cosLat),
+      lat + (r * Math.cos(rad)) / 111.32,
+    ]);
+  }
+  return ring;
+}
+
+export const RADII_COLORS = { 34: '#FFD84D', 50: '#FF9A3D', 64: '#FF3B30' };
+
+/** Match an NHC TCM (wind radii) to a storm by position (≤ 250 km). */
+export function radiiFor(storm, tcm) {
+  let best = null;
+  for (const t of tcm?.storms || []) {
+    const d = Math.hypot(
+      (t.lon - storm.lon) * Math.cos((storm.lat * Math.PI) / 180),
+      t.lat - storm.lat,
+    );
+    if (d < 2.3 && (!best || d < best.d)) best = { d, t };
+  }
+  return best?.t || null;
+}
+
 class CycloneLayer extends Layer {
-  constructor(ctx, { feed }) {
+  constructor(ctx, { feed, tcm }) {
     super(ctx, {
       id: 'cyclones',
       family: 'Hazards',
@@ -264,6 +311,8 @@ class CycloneLayer extends Layer {
       pollMs: 15 * 60_000,
     });
     this.feed = feed;
+    this.tcm = tcm;
+    this.fills = null;
     this.renderer = new ContactRenderer(this.root, {
       layerId: this.id,
       tint: color('#FFFFFF'),
@@ -284,6 +333,64 @@ class CycloneLayer extends Layer {
       this.fromFeed(this.feed);
     }
     this._draw(true);
+    // Wind radii arrive from a second source; the cone and track never wait.
+    this.tcm
+      ?.get()
+      .then(() => this.on && this._fills(this.feed.data?.records || []))
+      .catch(() => {});
+  }
+
+  /** Filled cone of uncertainty and 34/50/64-kt wind-radii quadrants. */
+  _fills(storms) {
+    if (this.fills) this.root.remove(this.fills);
+    this.fills = null;
+    const instances = [];
+    const poly = (ring, css, alpha, height) => {
+      if (!ring || ring.length < 4) return;
+      instances.push(
+        new Cesium.GeometryInstance({
+          geometry: new Cesium.PolygonGeometry({
+            polygonHierarchy: new Cesium.PolygonHierarchy(
+              Cesium.Cartesian3.fromDegreesArray(ring.flat()),
+            ),
+            height,
+            vertexFormat: Cesium.PerInstanceColorAppearance.FLAT_VERTEX_FORMAT,
+          }),
+          attributes: {
+            color: Cesium.ColorGeometryInstanceAttribute.fromColor(
+              color(css, alpha),
+            ),
+          },
+        }),
+      );
+    };
+    for (const s of storms) {
+      poly(outerRing(s.cone), '#FFFFFF', 0.1, 1500);
+      const tcm = radiiFor(s, this.tcm?.data);
+      if (tcm) s.radii = tcm.radii;
+      for (const r of [...(s.radii || [])].sort((a, b) => a.kt - b.kt)) {
+        if (!r.quadrantsKm.some((k) => k > 0)) continue;
+        poly(
+          radiiRing(s.lon, s.lat, r.quadrantsKm),
+          RADII_COLORS[r.kt] || '#FFD84D',
+          r.kt === 64 ? 0.26 : r.kt === 50 ? 0.18 : 0.12,
+          2500 + r.kt * 20,
+        );
+      }
+    }
+    if (!instances.length) return;
+    this.fills = this.root.add(
+      new Cesium.Primitive({
+        geometryInstances: instances,
+        appearance: new Cesium.PerInstanceColorAppearance({
+          flat: true,
+          translucent: true,
+        }),
+        asynchronous: true,
+        allowPicking: false,
+      }),
+    );
+    this.ctx.requestRender();
   }
 
   _draw(full) {
@@ -308,7 +415,10 @@ class CycloneLayer extends Layer {
     }
     this.count = items.length;
     this.renderer.setItems(items);
-    if (full) this._lines(data.records);
+    if (full) {
+      this._lines(data.records);
+      this._fills(data.records);
+    }
   }
 
   _lines(storms) {
@@ -402,9 +512,17 @@ class CycloneLayer extends Layer {
         .join(' · '),
       lon: s.now.lon,
       lat: s.now.lat,
+      labelDetail: [
+        stormCategory(s.now.windKt),
+        s.now.windKt ? `${Math.round(s.now.windKt)} KT` : null,
+        s.pressureHpa ? `${s.pressureHpa} HPA` : null,
+      ]
+        .filter(Boolean)
+        .join(' · '),
       meta: {
         layer: this.id,
         windKt: s.now.windKt ?? null,
+        radii: s.radii ?? null,
         pressureHpa: s.pressureHpa ?? null,
         movement: s.movement ?? null,
         basin: s.basin,
diff --git a/mobile/globe/layers/weather.js b/mobile/globe/layers/weather.js
new file mode 100644
index 000000000..d4477542f
--- /dev/null
+++ b/mobile/globe/layers/weather.js
@@ -0,0 +1,906 @@
+/**
+ * Weather family (radar, satellite IR clouds, lightning, surface wind, jet
+ * stream) plus the round-two Ground/Infra/Hazards layers that share the same
+ * plumbing (transit vehicles, GNSS interference, air quality).
+ *
+ * Rasters come from NOAA nowCOAST through the app's /api/weather proxy as
+ * whole-extent frames and are drawn as one unlit, translucent rectangle each
+ * (a few kilometres above the ground, where the weather is), so the night
+ * side does not swallow them the way lit imagery layers would. Scrubbing the
+ * time ribbon swaps to the frame valid at that time (radar ≈ 50 min of 4-min
+ * frames, lightning 3 h of 15-min frames, IR 6 h of hourly frames). Wind uses
+ * the desktop app's GPU streamline renderer (src/layers/wind/gpuRendering.js).
+ */
+import * as Cesium from 'cesium';
+import {
+  ContactRenderer,
+  Layer,
+  color,
+  FAMILY_COLORS,
+  inRect,
+} from './base.js';
+import { createWindGpuRendering } from '../../../src/layers/wind/gpuRendering.js';
+import {
+  aqiColor,
+  frameAt,
+  gnssIntegrity,
+  GNSS_ANCHORS,
+  transitVehicles,
+  weatherImageUrl,
+} from '../feedsWeather.js';
+import { haversineKm, relTime } from '../geo.js';
+
+const WX = FAMILY_COLORS.Weather;
+
+/* ───────────────────────── Frame decoding (shared) ───────────────────────── */
+
+const frameCache = new Map(); // url → Promise<canvas>
+const FRAME_CACHE_MAX = 8;
+
+/** Decode a same-origin weather frame into a canvas (IR gets an alpha key). */
+async function decodeFrame(url, product) {
+  const response = await fetch(url);
+  if (!response.ok) throw new Error(`Weather frame HTTP ${response.status}`);
+  const bitmap = await createImageBitmap(await response.blob());
+  const canvas = document.createElement('canvas');
+  canvas.width = bitmap.width;
+  canvas.height = bitmap.height;
+  const g = canvas.getContext('2d', { willReadFrequently: true });
+  g.drawImage(bitmap, 0, 0);
+  bitmap.close?.();
+  if (product === 'clouds' || product === 'clouds-regional') {
+    // Key the IR to clouds: warm surfaces clear, cloud tops white with a
+    // soft ramp (the repo's cloud key is tuned for a lit globe; this one
+    // also has to read on the unlit night side).
+    const px = g.getImageData(0, 0, canvas.width, canvas.height);
+    const d = px.data;
+    for (let i = 0; i < d.length; i += 4) {
+      const l = d[i];
+      const t = Math.max(0, Math.min(1, (l - 95) / 95));
+      const a = t * t * (3 - 2 * t);
+      d[i + 3] = (d[i + 3] * a * 215) / 255;
+      // Unlit clouds must not blow out under bloom: grey-white body,
+      // coldest tops leaning icy blue.
+      const cold = Math.max(0, (l - 200) / 55);
+      d[i] = 168 + 42 * a - 22 * cold;
+      d[i + 1] = 176 + 40 * a - 6 * cold;
+      d[i + 2] = 192 + 36 * a + 10 * cold;
+    }
+    g.putImageData(px, 0, 0);
+  }
+  return canvas;
+}
+
+function cached(url, make, keep) {
+  let p = frameCache.get(url);
+  if (p) {
+    frameCache.delete(url);
+    frameCache.set(url, p);
+    return p;
+  }
+  p = make();
+  p.catch(() => frameCache.delete(url));
+  if (!keep) return p;
+  frameCache.set(url, p);
+  while (frameCache.size > FRAME_CACHE_MAX)
+    frameCache.delete(frameCache.keys().next().value);
+  return p;
+}
+
+/** Decode a same-origin weather frame into a canvas (IR gets a cloud key). */
+export function loadWeatherFrame(
+  product,
+  time,
+  width = 2048,
+  { keep = true } = {},
+) {
+  const url = weatherImageUrl(product, time, width);
+  return cached(url, () => decodeFrame(url, product), keep);
+}
+
+/** A 2:1 detail window (0.25° grid) covering a view rect inside bounds. */
+export function detailWindow(rect, bounds) {
+  if (!rect || rect.west > rect.east) return null;
+  const lonSpan = rect.east - rect.west;
+  const latSpan = rect.north - rect.south;
+  let width = Math.max(1, lonSpan * 1.1, latSpan * 2.2);
+  width = Math.ceil(width / 0.5) * 0.5;
+  const height = width / 2;
+  if (width >= bounds.east - bounds.west - 0.5) return null;
+  if (height >= bounds.north - bounds.south - 0.5) return null;
+  const snap = (v) => Math.round(v / 0.25) * 0.25;
+  const cLon = (rect.west + rect.east) / 2;
+  const cLat = (rect.south + rect.north) / 2;
+  const minW = Math.ceil(bounds.west / 0.25) * 0.25;
+  const maxW = Math.floor((bounds.east - width) / 0.25) * 0.25;
+  const minS = Math.ceil(bounds.south / 0.25) * 0.25;
+  const maxS = Math.floor((bounds.north - height) / 0.25) * 0.25;
+  const west = Math.max(minW, Math.min(maxW, snap(cLon - width / 2)));
+  const south = Math.max(minS, Math.min(maxS, snap(cLat - height / 2)));
+  return { west, south, east: west + width, north: south + height };
+}
+
+/** Decode a detail window of a frame (2048×1024). */
+export function loadWeatherDetail(product, time, box) {
+  const url = `/api/weather/image?product=${product}&time=${encodeURIComponent(time)}&bbox=${box.west},${box.south},${box.east},${box.north}&size=2048x1024`;
+  return cached(url, () => decodeFrame(url, product), true);
+}
+
+/* ───────────────────────── Raster layer ───────────────────────── */
+
+class WeatherRasterLayer extends Layer {
+  /**
+   * @param {object} ctx
+   * @param {object} def
+   * @param {{feed:object, product:string, heightM:number, alpha:number,
+   *   width?:number}} opts
+   */
+  constructor(ctx, def, opts) {
+    super(ctx, { pollMs: 2 * 60_000, ...def });
+    this.feed = opts.feed;
+    this.product = opts.product;
+    this.heightM = opts.heightM;
+    this.alpha = opts.alpha;
+    this.width = opts.width ?? 2048;
+    this.primitive = null;
+    this.material = null;
+    this.frame = null;
+    this._want = null;
+  }
+
+  async refresh() {
+    try {
+      await this.feed.get();
+    } finally {
+      this.fromFeed(this.feed);
+    }
+    await this._apply();
+    if (this.frame && this.feed.data)
+      this.message = `${this.feed.data.title} · ${relTime(this.frameTime, Date.now())}`;
+    else if (this.feed.data?.coverage) this.message ||= this.feed.data.coverage;
+  }
+
+  _ensurePrimitive(bounds) {
+    if (this.primitive) return;
+    this.material = Cesium.Material.fromType('Image', {
+      image: Cesium.Material.DefaultImageId,
+      color: new Cesium.Color(1, 1, 1, this.alpha),
+    });
+    const rect = Cesium.Rectangle.fromDegrees(
+      bounds.west,
+      bounds.south,
+      bounds.east,
+      bounds.north,
+    );
+    this.primitive = this.root.add(
+      new Cesium.Primitive({
+        geometryInstances: new Cesium.GeometryInstance({
+          geometry: new Cesium.RectangleGeometry({
+            rectangle: rect,
+            height: this.heightM,
+            granularity: Cesium.Math.toRadians(1),
+            vertexFormat: Cesium.EllipsoidSurfaceAppearance.VERTEX_FORMAT,
+          }),
+        }),
+        appearance: new Cesium.EllipsoidSurfaceAppearance({
+          material: this.material,
+          flat: true,
+          aboveGround: true,
+          translucent: true,
+          renderState: { depthMask: false },
+        }),
+        asynchronous: true,
+        allowPicking: false,
+        show: false,
+      }),
+    );
+  }
+
+  async _apply() {
+    const data = this.feed.data;
+    if (!data) return;
+    const time = frameAt(
+      data.times,
+      this.ctx.isLive() ? null : this.ctx.timeMs(),
+    );
+    this._want = time;
+    if (!time) {
+      if (this.primitive) this.primitive.show = false;
+      this.count = 0;
+      this.message = 'No observation at this time';
+      this.ctx.requestRender();
+      return;
+    }
+    if (time === this.frame) {
+      if (this.primitive) this.primitive.show = true;
+      return;
+    }
+    this._ensurePrimitive(data.bounds);
+    const canvas = await loadWeatherFrame(this.product, time, this.width);
+    if (this._want !== time || !this.on) return;
+    this.material.uniforms.image = canvas;
+    this.primitive.show = true;
+    this.frame = time;
+    this.frameCanvas = canvas;
+    this.frameTime = Date.parse(time);
+    this.message = `${data.title} · ${relTime(this.frameTime, Date.now())}`;
+    if (this.afterFrame) this.afterFrame(canvas, data);
+    else this.count = 1;
+    this._detail().catch(() => {});
+    this.ctx.requestRender();
+  }
+
+  /** Close in, a sharper window of the same frame is laid over the global one. */
+  onView(view) {
+    this.lastView = view;
+    if (!this.on) return;
+    clearTimeout(this._detailTimer);
+    this._detailTimer = setTimeout(
+      () => this._detail().catch((e) => console.warn(`[globe:${this.id}]`, e)),
+      350,
+    );
+  }
+
+  async _detail() {
+    const v = this.lastView;
+    const data = this.feed.data;
+    const box =
+      v && v.heightM < 3_500_000 && this.frame && data
+        ? detailWindow(v.rect, data.bounds)
+        : null;
+    if (!box) {
+      if (this.detailPrim) this.detailPrim.show = false;
+      this._detailKey = null;
+      this.ctx.requestRender();
+      return;
+    }
+    const key = `${this.frame}|${box.west},${box.south},${box.east},${box.north}`;
+    if (key === this._detailKey) {
+      if (this.detailPrim) this.detailPrim.show = true;
+      return;
+    }
+    this._detailKey = key;
+    const canvas = await loadWeatherDetail(this.product, this.frame, box);
+    if (this._detailKey !== key || !this.on) return;
+    if (this.detailPrim) this.root.remove(this.detailPrim);
+    const material = Cesium.Material.fromType('Image', {
+      image: canvas,
+      color: new Cesium.Color(1, 1, 1, this.alpha),
+    });
+    this.detailPrim = this.root.add(
+      new Cesium.Primitive({
+        geometryInstances: new Cesium.GeometryInstance({
+          geometry: new Cesium.RectangleGeometry({
+            rectangle: Cesium.Rectangle.fromDegrees(
+              box.west,
+              box.south,
+              box.east,
+              box.north,
+            ),
+            height: this.heightM + 60,
+            granularity: Cesium.Math.toRadians(0.25),
+            vertexFormat: Cesium.EllipsoidSurfaceAppearance.VERTEX_FORMAT,
+          }),
+        }),
+        appearance: new Cesium.EllipsoidSurfaceAppearance({
+          material,
+          flat: true,
+          aboveGround: true,
+          translucent: true,
+          renderState: { depthMask: false },
+        }),
+        asynchronous: true,
+        allowPicking: false,
+      }),
+    );
+    // The coarse global frame stays underneath only where the window ends.
+    this.ctx.requestRender();
+  }
+
+  onTime() {
+    if (!this.on) return;
+    clearTimeout(this._timeTimer);
+    // Frames are whole-extent images: decode at most ~4 per second while
+    // the ribbon is being dragged.
+    this._timeTimer = setTimeout(
+      () => this._apply().catch((e) => console.warn(`[globe:${this.id}]`, e)),
+      250,
+    );
+  }
+
+  onHide() {
+    if (this.primitive) this.primitive.show = false;
+    if (this.detailPrim) this.detailPrim.show = false;
+    this._detailKey = null;
+    this.frame = null;
+  }
+
+  info() {
+    const i = super.info();
+    if (this.on && this.feed.data) i.frames = this.feed.data.times.length;
+    return i;
+  }
+}
+
+/* ───────────────────────── Lightning ───────────────────────── */
+
+const STRIKE_BIN_DEG = 0.5;
+const STRIKE_CAP = 1500;
+
+/**
+ * Strike-density raster plus a glow per active 0.5° cell, so storms read as
+ * flickering points of light from orbit. nowCOAST's palette runs yellow →
+ * orange → red → magenta with density; the glow grades the same way.
+ */
+class LightningLayer extends WeatherRasterLayer {
+  constructor(ctx, opts) {
+    super(
+      ctx,
+      { id: 'lightning', family: 'Weather', name: 'Lightning' },
+      { ...opts, product: 'lightning', heightM: 9000, alpha: 0.95 },
+    );
+    this.renderer = new ContactRenderer(this.root, {
+      layerId: this.id,
+      tint: color('#FFF2A8'),
+      glyphName: 'bolt',
+      rotate: false,
+      lodHeightM: 1_500_000,
+      cap: 300,
+      dotScale: 0.55,
+      glyphScale: 0.42,
+      dotAlpha: 1,
+    });
+    this.cells = new Map();
+  }
+
+  onView(view) {
+    super.onView(view);
+    this.renderer.setView(view);
+  }
+
+  afterFrame(canvas, data) {
+    const cells = strikeCells(canvas, data.bounds);
+    this.cells = new Map(cells.map((c) => [c.key, c]));
+    this.count = cells.length;
+    this.renderer.setItems(
+      cells.map((c) => ({
+        key: c.key,
+        lon: c.lon,
+        lat: c.lat,
+        altM: 9500,
+        color: color(
+          c.level >= 3 ? '#FF8AE6' : c.level === 2 ? '#FFD27A' : '#FFF6C8',
+        ),
+        dotScale: 0.32 + Math.min(0.55, c.pixels / 12),
+        glyphScale: 0.8 + c.level * 0.12,
+      })),
+    );
+  }
+
+  /** 1 Hz flicker: a few cells flare each second (cheap, no render loop). */
+  onTick() {
+    const n = this.renderer.dots.length;
+    if (!n) return false;
+    for (let k = 0; k < Math.min(24, n); k++) {
+      const i = Math.floor(Math.random() * n);
+      const bb = this.renderer.dots.get(i);
+      bb.scale = bb._base ??= bb.scale;
+      bb.scale = bb._base * (1.4 + Math.random() * 0.9);
+      setTimeout(() => {
+        if (this.renderer.dots.contains(bb)) bb.scale = bb._base;
+      }, 220);
+    }
+    setTimeout(() => this.ctx.requestRender(), 230);
+    return true;
+  }
+
+  locate(key) {
+    const c = this.cells.get(key);
+    return c ? [c.lon, c.lat, 9500] : null;
+  }
+
+  pick(key) {
+    const c = this.cells.get(key);
+    if (!c) return null;
+    return {
+      kind: 'lightning',
+      id: key,
+      title: 'Lightning',
+      subtitle: `Strike density class ${c.level} · ${relTime(this.frameTime, Date.now())}`,
+      lon: c.lon,
+      lat: c.lat,
+      meta: { layer: this.id, level: c.level, source: this.source },
+    };
+  }
+}
+
+/** Classify a nowCOAST lightning-density pixel 1 (low) .. 4 (extreme). */
+export function strikeLevel(r, g, b) {
+  if (r > 200 && g > 200 && b < 140) return 1; // yellow
+  if (r > 200 && g > 90) return 2; // orange
+  if (r > 170 && b > 120) return 4; // magenta / pink
+  if (r > 150) return 3; // red
+  return 1;
+}
+
+/** Bin the lit pixels of a whole-extent lightning frame into 0.5° cells. */
+export function strikeCells(canvas, bounds, bbox = null) {
+  const g = canvas.getContext('2d', { willReadFrequently: true });
+  const { width, height } = canvas;
+  const px = g.getImageData(0, 0, width, height).data;
+  const dLon = (bounds.east - bounds.west) / width;
+  const dLat = (bounds.north - bounds.south) / height;
+  const bins = new Map();
+  for (let y = 0; y < height; y++) {
+    const lat = bounds.north - (y + 0.5) * dLat;
+    if (bbox && (lat < bbox.south || lat > bbox.north)) continue;
+    for (let x = 0; x < width; x++) {
+      const i = (y * width + x) * 4;
+      if (px[i + 3] < 40) continue;
+      const lon = bounds.west + (x + 0.5) * dLon;
+      if (bbox && (lon < bbox.west || lon > bbox.east)) continue;
+      const level = strikeLevel(px[i], px[i + 1], px[i + 2]);
+      const key = `${Math.floor(lat / STRIKE_BIN_DEG)}:${Math.floor(lon / STRIKE_BIN_DEG)}`;
+      let c = bins.get(key);
+      if (!c)
+        bins.set(
+          key,
+          (c = { key, lat: 0, lon: 0, pixels: 0, level: 0, weight: 0 }),
+        );
+      c.lat += lat;
+      c.lon += lon;
+      c.pixels++;
+      c.weight += level;
+      c.level = Math.max(c.level, level);
+    }
+  }
+  const out = [];
+  for (const c of bins.values()) {
+    c.lat /= c.pixels;
+    c.lon /= c.pixels;
+    out.push(c);
+  }
+  out.sort((a, b) => b.weight - a.weight);
+  return out.slice(0, STRIKE_CAP);
+}
+
+/* ───────────────────────── Wind (GPU streamlines) ───────────────────────── */
+
+class WindLayer extends Layer {
+  constructor(ctx, def, { feed }) {
+    super(ctx, { pollMs: 60 * 60_000, ...def });
+    this.feed = feed;
+    this.gpu = createWindGpuRendering({
+      cesium: Cesium,
+      getViewer: () => ctx.viewer,
+    });
+    this.field = null;
+    this.started = performance.now();
+    this._raf = 0;
+    this._lastFrame = 0;
+    const scene = ctx.scene;
+    this._pre = scene.preRender.addEventListener(() => {
+      if (!this.on || !this.field) return;
+      this.gpu.tick((performance.now() - this.started) / 1000);
+      this.gpu.updateVisibility(scene.camera);
+    });
+  }
+
+  async refresh() {
+    try {
+      await this.feed.get();
+    } finally {
+      this.fromFeed(this.feed);
+    }
+    const d = this.feed.data;
+    if (!d) return;
+    if (d.field !== this.field) {
+      this.field = d.field;
+      if (this.on) this.gpu.setField(this.field);
+    }
+    this.count = this.gpu.getParticleCount();
+    this.message = `${d.level} · ${d.source}`;
+    this._loop();
+  }
+
+  setOn(on) {
+    super.setOn(on);
+    if (on && this.field) {
+      this.gpu.setField(this.field);
+      this._loop();
+    }
+  }
+
+  onHide() {
+    this.gpu.clear();
+    cancelAnimationFrame(this._raf);
+    this._raf = 0;
+  }
+
+  /** Flowing streaks need frames: ~30 fps while on and visible, 0 otherwise. */
+  _loop() {
+    if (this._raf || !this.on) return;
+    const step = (t) => {
+      this._raf = 0;
+      if (!this.on) return;
+      if (this.ctx.active() && t - this._lastFrame > 33) {
+        this._lastFrame = t;
+        this.ctx.requestRender();
+      }
+      this._raf = requestAnimationFrame(step);
+    };
+    this._raf = requestAnimationFrame(step);
+  }
+
+  destroy() {
+    cancelAnimationFrame(this._raf);
+    this._pre?.();
+    this.gpu.destroy();
+    super.destroy();
+  }
+}
+
+/* ───────────────────────── Air quality ───────────────────────── */
+
+class AirQualityLayer extends Layer {
+  constructor(ctx, { feed }) {
+    super(ctx, {
+      id: 'air-quality',
+      family: 'Hazards',
+      name: 'Air quality',
+      pollMs: 60 * 60_000,
+    });
+    this.feed = feed;
+    this.renderer = new ContactRenderer(this.root, {
+      layerId: this.id,
+      tint: color('#F2D33B'),
+      glyphName: 'aq',
+      rotate: false,
+      alwaysGlyph: true,
+      dotScale: 0.9,
+      glyphScale: 0.5,
+    });
+    this.records = new Map();
+  }
+  async refresh() {
+    try {
+      await this.feed.get();
+    } finally {
+      this.fromFeed(this.feed);
+    }
+    const recs = this.feed.data.records;
+    this.records = new Map(recs.map((r) => [r.id, r]));
+    this.count = recs.length;
+    this.renderer.setItems(
+      recs.map((r) => ({
+        key: r.id,
+        lon: r.lon,
+        lat: r.lat,
+        color: color(aqiColor(r.aqi)),
+        dotScale: 0.8 + Math.min(2, r.aqi / 100),
+        glyphScale: 0.55 + Math.min(0.6, r.aqi / 300),
+      })),
+    );
+  }
+  onView(view) {
+    this.renderer.setView(view);
+  }
+  locate(key) {
+    const r = this.records.get(key);
+    return r ? [r.lon, r.lat, 0] : null;
+  }
+  pick(key) {
+    const r = this.records.get(key);
+    if (!r) return null;
+    return {
+      kind: 'air-quality',
+      id: r.id,
+      title: `${r.name} · AQI ${Math.round(r.aqi)}`,
+      subtitle: `PM2.5 ${r.pm25?.toFixed(0) ?? '–'} µg/m³ · modelled (CAMS)`,
+      lon: r.lon,
+      lat: r.lat,
+      labelDetail: `AQI ${Math.round(r.aqi)}`,
+      meta: { layer: this.id, aqi: r.aqi, pm25: r.pm25, source: this.source },
+    };
+  }
+}
+
+/* ───────────────────────── GNSS interference ───────────────────────── */
+
+const GNSS_COLORS = { high: '#FF3B6B', medium: '#FFB13D', low: '#4ADE80' };
+
+class GnssLayer extends Layer {
+  constructor(ctx) {
+    super(ctx, {
+      id: 'gnss',
+      family: 'Infra',
+      name: 'GNSS interference',
+      pollMs: 2 * 60_000,
+    });
+    this.source = 'adsb.lol NIC/NACp (gpsjam.org bands)';
+    this.cellsPrim = null;
+    this.anchor = null;
+    this.cells = new Map();
+  }
+
+  _anchors() {
+    const v = this.lastView;
+    if (v && v.heightM < 3_000_000 && v.center)
+      return [{ id: 'view', lat: v.center.lat, lon: v.center.lon }];
+    return GNSS_ANCHORS;
+  }
+
+  async refresh() {
+    const anchors = this._anchors();
+    const results = await Promise.allSettled(
+      anchors.map((a) =>
+        gnssIntegrity.get(`${Math.round(a.lat)}:${Math.round(a.lon)}`, a),
+      ),
+    );
+    const ok = results
+      .filter((r) => r.status === 'fulfilled')
+      .map((r) => r.value);
+    if (!ok.length) {
+      this.status = 'error';
+      this.message =
+        results[0]?.reason?.message || 'GNSS integrity source unavailable';
+      return;
+    }
+    this.status = 'live';
+    this.message = 'Low NIC/NACp is a proxy for jamming or spoofing, not proof';
+    const cells = new Map();
+    for (const snap of ok)
+      for (const c of snap.cells)
+        cells.set(`${c.lat.toFixed(2)}:${c.lon.toFixed(2)}`, c);
+    this.cells = cells;
+    this._draw();
+  }
+
+  _draw() {
+    if (this.cellsPrim) this.root.remove(this.cellsPrim);
+    this.cellsPrim = null;
+    const shown = [...this.cells.entries()].filter(
+      ([, c]) => c.level !== 'low' || c.total >= 6,
+    );
+    this.count = shown.filter(([, c]) => c.level !== 'low').length;
+    if (!shown.length) return;
+    const instances = shown.map(([key, c]) => {
+      const h = 0.25;
+      return new Cesium.GeometryInstance({
+        id: { layer: this.id, key },
+        geometry: new Cesium.RectangleGeometry({
+          rectangle: Cesium.Rectangle.fromDegrees(
+            c.lon - h,
+            c.lat - h,
+            c.lon + h,
+            c.lat + h,
+          ),
+          height: 2000,
+          vertexFormat: Cesium.PerInstanceColorAppearance.FLAT_VERTEX_FORMAT,
+        }),
+        attributes: {
+          color: Cesium.ColorGeometryInstanceAttribute.fromColor(
+            color(GNSS_COLORS[c.level], c.level === 'low' ? 0.18 : 0.5),
+          ),
+        },
+      });
+    });
+    this.cellsPrim = this.root.add(
+      new Cesium.Primitive({
+        geometryInstances: instances,
+        appearance: new Cesium.PerInstanceColorAppearance({
+          flat: true,
+          translucent: true,
+        }),
+        asynchronous: true,
+      }),
+    );
+    this.ctx.requestRender();
+  }
+
+  onView(view) {
+    const prev = this.lastView;
+    this.lastView = view;
+    const moved =
+      !prev ||
+      view.heightM < 3_000_000 !== prev.heightM < 3_000_000 ||
+      (view.heightM < 3_000_000 &&
+        haversineKm(
+          view.center.lat,
+          view.center.lon,
+          prev.center.lat,
+          prev.center.lon,
+        ) > 150);
+    if (moved && this.on) this.kick();
+  }
+
+  locate(key) {
+    const c = this.cells.get(key);
+    return c ? [c.lon, c.lat, 0] : null;
+  }
+
+  pick(key) {
+    const c = this.cells.get(key);
+    if (!c) return null;
+    return {
+      kind: 'gnss',
+      id: key,
+      title: `GNSS ${c.level === 'high' ? 'interference likely' : c.level === 'medium' ? 'degraded' : 'nominal'}`,
+      subtitle: `${c.bad}/${c.total} aircraft with low NIC/NACp · ${c.percent.toFixed(0)}%`,
+      lon: c.lon,
+      lat: c.lat,
+      meta: { layer: this.id, ...c, source: this.source },
+    };
+  }
+}
+
+/* ───────────────────────── Transit ───────────────────────── */
+
+function routeColor(routeId) {
+  let h = 0;
+  for (const ch of String(routeId)) h = (h * 31 + ch.charCodeAt(0)) >>> 0;
+  return `hsl(${h % 360} 85% 62%)`;
+}
+
+class TransitLayer extends Layer {
+  constructor(ctx, { catalog }) {
+    super(ctx, {
+      id: 'transit',
+      family: 'Ground',
+      name: 'Transit vehicles',
+      pollMs: 20_000,
+    });
+    this.catalog = catalog;
+    this.renderer = new ContactRenderer(this.root, {
+      layerId: this.id,
+      tint: color(FAMILY_COLORS.Ground),
+      glyphName: 'bus',
+      lodHeightM: 400_000,
+      cap: 600,
+      dotScale: 0.32,
+      glyphScale: 0.38,
+    });
+    this.records = new Map();
+    this.feedId = null;
+  }
+
+  async refresh() {
+    let cat;
+    try {
+      cat = await this.catalog.get();
+    } finally {
+      this.fromFeed(this.catalog);
+    }
+    const c = this.lastView?.center;
+    const feeds = cat.feeds;
+    let best = null;
+    for (const f of feeds) {
+      const d = c ? haversineKm(c.lat, c.lon, f.center.lat, f.center.lon) : 0;
+      if (!best || d - f.loadRadiusKm < best.d - best.f.loadRadiusKm)
+        best = { f, d };
+    }
+    if (
+      !best ||
+      (c && best.d > best.f.loadRadiusKm + 400 && this.lastView?.heightM < 3e6)
+    ) {
+      this.count = 0;
+      this.message = 'No open transit feed near this view';
+      this.renderer.clear();
+      return;
+    }
+    // From orbit the nearest feed is arbitrary: show Helsinki's (busy, CC BY).
+    const feed =
+      this.lastView?.heightM >= 3e6
+        ? feeds.find((f) => f.id === 'hsl-helsinki') || best.f
+        : best.f;
+    this.feedId = feed.id;
+    const snap = await transitVehicles.get(feed.id);
+    this.source = `${feed.name} · ${feed.attribution}`;
+    this.message = `${feed.region} · ${snap.vehicles.length} vehicles`;
+    this.status = 'live';
+    this.records = new Map(snap.vehicles.map((v) => [v.id, v]));
+    this.count = snap.vehicles.length;
+    this.renderer.setItems(
+      snap.vehicles.map((v) => ({
+        key: v.id,
+        lon: v.lon,
+        lat: v.lat,
+        heading: v.bearing ?? 0,
+        color: color(routeColor(v.routeId)),
+      })),
+    );
+  }
+
+  onView(view) {
+    const prev = this.lastView;
+    this.lastView = view;
+    this.renderer.setView(view);
+    if (
+      this.on &&
+      prev?.center &&
+      haversineKm(
+        view.center.lat,
+        view.center.lon,
+        prev.center.lat,
+        prev.center.lon,
+      ) > 120
+    )
+      this.kick();
+  }
+
+  locate(key) {
+    const v = this.records.get(key);
+    return v ? [v.lon, v.lat, 0] : null;
+  }
+
+  pick(key) {
+    const v = this.records.get(key);
+    if (!v) return null;
+    return {
+      kind: 'transit',
+      id: v.id,
+      title: `Route ${v.routeId || '?'}`,
+      subtitle: [
+        v.speedMps != null ? `${Math.round(v.speedMps * 3.6)} km/h` : null,
+        v.status ? v.status.replace(/_/g, ' ').toLowerCase() : null,
+      ]
+        .filter(Boolean)
+        .join(' · '),
+      lon: v.lon,
+      lat: v.lat,
+      meta: { layer: this.id, feedId: this.feedId, source: this.source },
+    };
+  }
+
+  contacts() {
+    return [...this.records.values()].map((v) => ({
+      kind: 'transit',
+      id: v.id,
+      title: `Route ${v.routeId}`,
+      lon: v.lon,
+      lat: v.lat,
+      altM: 0,
+      headingDeg: v.bearing ?? 0,
+      speedMps: v.speedMps,
+      layer: this.id,
+    }));
+  }
+}
+
+export { inRect };
+
+export function createWeatherLayers(ctx, feeds) {
+  return [
+    new WeatherRasterLayer(
+      ctx,
+      { id: 'radar', family: 'Weather', name: 'Radar' },
+      { feed: feeds.radar, product: 'radar', heightM: 4000, alpha: 0.9 },
+    ),
+    new WeatherRasterLayer(
+      ctx,
+      {
+        id: 'clouds',
+        family: 'Weather',
+        name: 'Clouds (satellite IR)',
+        pollMs: 10 * 60_000,
+      },
+      { feed: feeds.clouds, product: 'clouds', heightM: 7000, alpha: 0.85 },
+    ),
+    new LightningLayer(ctx, { feed: feeds.lightning, width: 2048 }),
+    new WindLayer(
+      ctx,
+      { id: 'wind', family: 'Weather', name: 'Wind (10 m)' },
+      { feed: feeds.wind },
+    ),
+    new WindLayer(
+      ctx,
+      { id: 'jet', family: 'Weather', name: 'Jet stream (250 hPa)' },
+      { feed: feeds.jet },
+    ),
+    new AirQualityLayer(ctx, { feed: feeds.airQuality }),
+    new GnssLayer(ctx),
+    new TransitLayer(ctx, { catalog: feeds.transitCatalog }),
+  ];
+}
+
+export { WX };
diff --git a/mobile/globe/pins.js b/mobile/globe/pins.js
new file mode 100644
index 000000000..9ed29142b
--- /dev/null
+++ b/mobile/globe/pins.js
@@ -0,0 +1,196 @@
+/**
+ * Pins for discourse and capture (DESIGN.md §11.3–11.4): posts, sealed
+ * witness captures, public camera eyes, live broadcasts and holograms. Eyes
+ * and live pins draw their view frustum as a translucent wedge on the ground
+ * along the camera heading. Pins are few (tens), so the wedge primitive is
+ * simply rebuilt on change.
+ */
+import * as Cesium from 'cesium';
+import { glyph } from './glyphs.js';
+import { offsetLonLat } from './geo.js';
+
+export const PIN_KINDS = Object.freeze([
+  'post',
+  'witness',
+  'eye',
+  'live',
+  'hologram',
+]);
+
+const PIN_COLORS = Object.freeze({
+  post: '#E8EEF7',
+  witness: '#FFC857',
+  eye: '#FFD166',
+  live: '#FF4D6D',
+  hologram: '#C9A7FF',
+});
+
+const PIN_TITLES = Object.freeze({
+  post: 'Post',
+  witness: 'Sealed witness capture',
+  eye: 'Public camera',
+  live: 'Live broadcast',
+  hologram: 'Hologram',
+});
+
+export function createPins({ scene, requestRender }) {
+  const root = scene.primitives.add(new Cesium.PrimitiveCollection());
+  const billboards = root.add(new Cesium.BillboardCollection());
+  const edges = root.add(new Cesium.PolylineCollection());
+  let wedges = null;
+  const pins = new Map();
+  let pulse = 0;
+
+  function rebuildWedges() {
+    if (wedges) root.remove(wedges);
+    wedges = null;
+    edges.removeAll();
+    const instances = [];
+    for (const p of pins.values()) {
+      if (p.kind !== 'eye' && p.kind !== 'live') continue;
+      if (!Number.isFinite(p.headingDeg)) continue;
+      const half = (p.fovDeg ?? 60) / 2;
+      const ring = [[p.lon, p.lat]];
+      for (let a = -half; a <= half + 0.01; a += Math.max(2, half / 6))
+        ring.push(offsetLonLat(p.lon, p.lat, p.headingDeg + a, p.rangeM));
+      const css = p.color || PIN_COLORS[p.kind];
+      instances.push(
+        new Cesium.GeometryInstance({
+          id: { layer: 'pins', key: p.id },
+          geometry: new Cesium.PolygonGeometry({
+            polygonHierarchy: new Cesium.PolygonHierarchy(
+              Cesium.Cartesian3.fromDegreesArray(ring.flat()),
+            ),
+            height: (p.altM || 0) + 3,
+            vertexFormat: Cesium.PerInstanceColorAppearance.FLAT_VERTEX_FORMAT,
+          }),
+          attributes: {
+            color: Cesium.ColorGeometryInstanceAttribute.fromColor(
+              Cesium.Color.fromCssColorString(css).withAlpha(0.28),
+            ),
+          },
+        }),
+      );
+      edges.add({
+        positions: Cesium.Cartesian3.fromDegreesArrayHeights(
+          [...ring, ring[0]].flatMap(([lo, la]) => [lo, la, (p.altM || 0) + 4]),
+        ),
+        width: 1.5,
+        material: Cesium.Material.fromType('Color', {
+          color: Cesium.Color.fromCssColorString(css).withAlpha(0.85),
+        }),
+      });
+    }
+    if (instances.length)
+      wedges = root.add(
+        new Cesium.Primitive({
+          geometryInstances: instances,
+          appearance: new Cesium.PerInstanceColorAppearance({
+            flat: true,
+            translucent: true,
+          }),
+          asynchronous: true,
+        }),
+      );
+  }
+
+  function rebuildBillboards() {
+    billboards.removeAll();
+    for (const p of pins.values()) {
+      const g = glyph(p.kind);
+      p._bb = billboards.add({
+        position: Cesium.Cartesian3.fromDegrees(
+          p.lon,
+          p.lat,
+          (p.altM || 0) + 8,
+        ),
+        image: g.image,
+        imageId: g.imageId,
+        color: Cesium.Color.fromCssColorString(p.color || PIN_COLORS[p.kind]),
+        scale: 0.62,
+        scaleByDistance: new Cesium.NearFarScalar(2e3, 1.15, 8e6, 0.55),
+        verticalOrigin: Cesium.VerticalOrigin.CENTER,
+        disableDepthTestDistance: 2e5,
+        id: { layer: 'pins', key: p.id },
+      });
+    }
+  }
+
+  function changed() {
+    rebuildBillboards();
+    rebuildWedges();
+    requestRender();
+  }
+
+  return {
+    add(pin) {
+      if (!pin || pin.id == null) throw new TypeError('addPin needs an id');
+      if (!Number.isFinite(pin.lon) || !Number.isFinite(pin.lat))
+        throw new TypeError('addPin needs lon and lat');
+      const kind = PIN_KINDS.includes(pin.kind) ? pin.kind : 'post';
+      const p = {
+        id: String(pin.id),
+        lon: pin.lon,
+        lat: pin.lat,
+        kind,
+        headingDeg: Number.isFinite(pin.headingDeg) ? pin.headingDeg : null,
+        fovDeg: Number.isFinite(pin.fovDeg) ? pin.fovDeg : 60,
+        rangeM: Number.isFinite(pin.rangeM) ? pin.rangeM : 350,
+        color: pin.color || null,
+        label: pin.label || '',
+        altM: Number.isFinite(pin.altM) ? pin.altM : 0,
+      };
+      pins.set(p.id, p);
+      changed();
+      return p.id;
+    },
+    remove(id) {
+      const ok = pins.delete(String(id));
+      if (ok) changed();
+      return ok;
+    },
+    list() {
+      return [...pins.values()].map(({ _bb, ...p }) => ({ ...p }));
+    },
+    locate(id) {
+      const p = pins.get(String(id));
+      return p ? [p.lon, p.lat, p.altM || 0] : null;
+    },
+    pick(id) {
+      const p = pins.get(String(id));
+      if (!p) return null;
+      return {
+        kind: 'pin',
+        pinKind: p.kind,
+        id: p.id,
+        title: p.label || PIN_TITLES[p.kind],
+        subtitle: PIN_TITLES[p.kind],
+        lon: p.lon,
+        lat: p.lat,
+        meta: {
+          layer: 'pins',
+          headingDeg: p.headingDeg,
+          fovDeg: p.fovDeg,
+          label: p.label,
+        },
+      };
+    },
+    /** Live pins breathe once a second; returns true when anything changed. */
+    tick() {
+      let any = false;
+      pulse = (pulse + 1) % 2;
+      for (const p of pins.values())
+        if (p.kind === 'live' && p._bb) {
+          p._bb.scale = pulse ? 0.74 : 0.6;
+          any = true;
+        }
+      return any;
+    },
+    get billboards() {
+      return billboards;
+    },
+    destroy() {
+      scene.primitives.remove(root);
+    },
+  };
+}
diff --git a/mobile/globe/situations.js b/mobile/globe/situations.js
index 78fd403d9..99a8c8d03 100644
--- a/mobile/globe/situations.js
+++ b/mobile/globe/situations.js
@@ -1,20 +1,47 @@
 /**
- * Situation cards for the Now feed, built from the same live feeds the layers
- * use. Every card carries real imagery of its place (keyless Esri export),
- * a target-centred camera and the layers worth turning on. A feed that fails
- * drops only its own cards: the bundled Bhote Koshi reconstruction and the
- * evergreen places always resolve, so the feed is never empty.
+ * Situation cards for the Now feed (DESIGN.md §11.2): space → sky → ground,
+ * four archetypes (sensor, eye, track, number), every number from a live
+ * keyless feed with its source named. A genre whose feed fails, or that has
+ * nothing real to show right now, is omitted, never invented.
+ *
+ * Each card also registers a compositor scene (SCENES, keyed by card id):
+ * the data the thumbnail compositor draws over the imagery. Scenes stay out
+ * of the card objects so the shell can clone and serialise cards freely.
  */
 import { twoline2satrec } from 'satellite.js';
 import { findNextIssPass } from '../../src/data/issPass.js';
 import { satPosition } from './layers/orbit.js';
-import { AIRPORTS, EVERGREEN, FORT_NOVOSEL } from './places.js';
-import { densestCell, haversineKm, relTime, thumbnailAround } from './geo.js';
+import { radiiFor, stormCategory } from './layers/hazards.js';
+import { loadWeatherFrame, strikeCells } from './layers/weather.js';
+import { AIRPORTS, FORT_NOVOSEL } from './places.js';
+import {
+  densestCell,
+  haversineKm,
+  relTime,
+  subsolarPoint,
+  thumbnailAround,
+} from './geo.js';
+import { cctvFrameUrl } from './feeds.js';
+import {
+  GNSS_ANCHORS,
+  gnssIntegrity,
+  pointWind,
+  transitVehicles,
+} from './feedsWeather.js';
+import { describePlace, US_METROS, compass } from './gazetteer.js';
 
 const DAY = 86_400_000;
-const FEED_BUDGET_MS = 9_000;
-// OpenSky's global snapshot routinely takes 10-15 s through the proxy.
-const FLIGHTS_BUDGET_MS = 16_000;
+const HOUR = 3_600_000;
+const FEED_BUDGET_MS = 12_000;
+const FLIGHTS_BUDGET_MS = 26_000;
+const SLOW_BUDGET_MS = 20_000;
+/** No genre may hold the feed back longer than this (after its feeds). */
+const GENRE_BUDGET_MS = 25_000;
+
+/** Compositor scenes by situation id (see compositor.js). */
+export const SCENES = new Map();
+/** Verified camera frames fetched while building eye cards: id → {blob, at}. */
+export const EYE_FRAMES = new Map();
 
 const withBudget = (promise, ms = FEED_BUDGET_MS) =>
   Promise.race([
@@ -24,32 +51,44 @@ const withBudget = (promise, ms = FEED_BUDGET_MS) =>
     ),
   ]);
 
+const M_TO_FT = 3.28084;
+const MPS_TO_KT = 1 / 0.514444;
+const up = (s) => String(s).toUpperCase();
+const hhmmss = (ms) => new Date(ms).toISOString().slice(11, 19) + 'Z';
+const hhmm = (ms) => new Date(ms).toISOString().slice(11, 16) + 'Z';
+const fmtInt = (n) => Math.round(n).toLocaleString('en-US');
+const fl = (altM) =>
+  `FL${String(Math.round((altM * M_TO_FT) / 100)).padStart(3, '0')}`;
+
+function fmtLatLon(lat, lon) {
+  return `${Math.abs(lat).toFixed(1)}°${lat >= 0 ? 'N' : 'S'} ${Math.abs(lon).toFixed(1)}°${lon >= 0 ? 'E' : 'W'}`;
+}
+
 function corridorKm(ev) {
   const c = ev?.reconstruction?.corridor;
   if (!c?.length) return 22;
   return Math.round(Math.abs(c.at(-1).chainageM - c[0].chainageM) / 100) / 10;
 }
 
-function fmtLatLon(lat, lon) {
-  return `${Math.abs(lat).toFixed(1)}°${lat >= 0 ? 'N' : 'S'} ${Math.abs(lon).toFixed(1)}°${lon >= 0 ? 'E' : 'W'}`;
-}
-
-function card(base) {
+function card(base, scene) {
   const radiusKm = base.radiusKm ?? 60;
   const camHeight = base.camera?.height ?? radiusKm * 2500;
-  return {
+  const c = {
     id: base.id,
     kind: base.kind,
     family: base.family,
     section: base.section || 'now',
+    band: base.band,
+    archetype: base.archetype,
+    telemetry: base.telemetry,
     title: base.title,
     subtitle: base.subtitle || '',
     place: base.place || fmtLatLon(base.lat, base.lon),
     lon: base.lon,
     lat: base.lat,
     camera: {
-      lon: base.lon,
-      lat: base.lat,
+      lon: base.camera?.lon ?? base.lon,
+      lat: base.camera?.lat ?? base.lat,
       height: camHeight,
       heading: base.camera?.heading ?? 0,
       pitch: base.camera?.pitch ?? -50,
@@ -60,12 +99,25 @@ function card(base) {
     layers: base.layers || [],
     ...(base.time ? { time: base.time } : {}),
     metrics: base.metrics || [],
+    ...(base.headline ? { headline: base.headline } : {}),
+    ...(base.media ? { media: base.media } : {}),
+    ...(base.series?.length > 1
+      ? { series: base.series, seriesLabel: base.seriesLabel || '' }
+      : {}),
     thumbnail: base.thumbnail || thumbnailAround(base.lon, base.lat, radiusKm),
     live: base.live ?? true,
     updatedAt: base.updatedAt ?? Date.now(),
     source: base.source || '',
     severity: base.severity ?? 0,
   };
+  SCENES.set(c.id, {
+    lon: base.lon,
+    lat: base.lat,
+    spanKm: base.spanKm ?? radiusKm * 2,
+    band: base.band,
+    ...scene,
+  });
+  return c;
 }
 
 /** Region words for a lat/lon (coarse, for subtitles only). */
@@ -81,7 +133,6 @@ function regionOf(lat, lon) {
   return 'Open ocean';
 }
 
-/** Tropical cyclone basin for a position (for storms without an NHC basin). */
 function basinOf(lat, lon) {
   if (lat >= 0) {
     if (lon >= 100 || lon < -180) return 'Western Pacific';
@@ -95,10 +146,205 @@ function basinOf(lat, lon) {
   return 'South Atlantic';
 }
 
+/** Sun elevation (deg) at a place, from the sub-solar point. */
+function sunElevation(lat, lon, ms) {
+  const s = subsolarPoint(ms);
+  const r = Math.PI / 180;
+  const cosZ =
+    Math.sin(lat * r) * Math.sin(s.lat * r) +
+    Math.cos(lat * r) * Math.cos(s.lat * r) * Math.cos((lon - s.lon) * r);
+  return 90 - Math.acos(Math.max(-1, Math.min(1, cosZ))) / r;
+}
+
+/* ───────────────────────── Raster analysis ───────────────────────── */
+
+/** Approximate dBZ for a pixel of nowCOAST's base-reflectivity palette. */
+export function dbzOf(r, g, b, a) {
+  if (a < 40) return null;
+  const max = Math.max(r, g, b);
+  const min = Math.min(r, g, b);
+  if (max < 40) return null;
+  if (min > 225) return 70; // white core
+  let h = 0;
+  const d = max - min || 1;
+  if (max === r) h = ((g - b) / d) % 6;
+  else if (max === g) h = (b - r) / d + 2;
+  else h = (r - g) / d + 4;
+  h = (h * 60 + 360) % 360;
+  if (h >= 270 && h < 330) return 62; // magenta / purple
+  if (h >= 330 || h < 12) return max > 190 ? 52 : 57; // reds
+  if (h < 35) return 47; // orange
+  if (h < 70) return 41; // yellow
+  if (h < 160) return g > 170 ? 27 : 33; // greens (dark = heavier)
+  if (h < 200) return 12; // cyan
+  return 20; // blue
+}
+
+/** Max dBZ and heavy-pixel count near a point in a whole-extent radar frame. */
+function radarNear(canvas, bounds, lat, lon, km) {
+  const g = canvas.getContext('2d', { willReadFrequently: true });
+  const { width, height } = canvas;
+  const dLon = (bounds.east - bounds.west) / width;
+  const dLat = (bounds.north - bounds.south) / height;
+  const rLat = km / 111.32;
+  const rLon = km / (111.32 * Math.cos((lat * Math.PI) / 180));
+  const x0 = Math.max(0, Math.floor((lon - rLon - bounds.west) / dLon));
+  const x1 = Math.min(width - 1, Math.ceil((lon + rLon - bounds.west) / dLon));
+  const y0 = Math.max(0, Math.floor((bounds.north - (lat + rLat)) / dLat));
+  const y1 = Math.min(
+    height - 1,
+    Math.ceil((bounds.north - (lat - rLat)) / dLat),
+  );
+  if (x1 <= x0 || y1 <= y0) return { max: null, heavy: 0, wet: 0 };
+  const px = g.getImageData(x0, y0, x1 - x0 + 1, y1 - y0 + 1).data;
+  const zs = [];
+  let heavy = 0;
+  for (let i = 0; i < px.length; i += 4) {
+    const z = dbzOf(px[i], px[i + 1], px[i + 2], px[i + 3]);
+    if (z == null) continue;
+    zs.push(z);
+    if (z >= 40) heavy++;
+  }
+  if (!zs.length) return { max: null, heavy: 0, wet: 0 };
+  zs.sort((a, b) => a - b);
+  // A robust peak: the 98th percentile, so one stray pixel is not "heavy".
+  const max = zs[Math.min(zs.length - 1, Math.floor(zs.length * 0.98))];
+  return { max, heavy, wet: zs.length };
+}
+
+/** Lit-pixel area (km²) of a lightning frame inside a bbox. */
+function lightningArea(canvas, bounds, bbox) {
+  const cells = strikeCells(canvas, bounds, bbox);
+  const pxLon = (bounds.east - bounds.west) / canvas.width;
+  const pxLat = (bounds.north - bounds.south) / canvas.height;
+  let area = 0;
+  for (const c of cells)
+    area +=
+      c.pixels *
+      pxLon *
+      111.32 *
+      Math.cos((c.lat * Math.PI) / 180) *
+      pxLat *
+      111.32;
+  return area;
+}
+
+/** Group 0.5° strike cells into storm clusters (≈ 4° bins). */
+function lightningClusters(cells) {
+  const bins = new Map();
+  for (const c of cells) {
+    const key = `${Math.floor(c.lat / 4)}:${Math.floor(c.lon / 4)}`;
+    let b = bins.get(key);
+    if (!b) bins.set(key, (b = { lat: 0, lon: 0, w: 0, cells: [], level: 0 }));
+    b.lat += c.lat * c.weight;
+    b.lon += c.lon * c.weight;
+    b.w += c.weight;
+    b.level = Math.max(b.level, c.level);
+    b.cells.push(c);
+  }
+  return [...bins.values()]
+    .map((b) => ({ ...b, lat: b.lat / b.w, lon: b.lon / b.w }))
+    .sort((a, b) => b.w - a.w);
+}
+
+/* ───────────────────────── Eyes ───────────────────────── */
+
+/** Famous busy places with public cameras in the catalog (matched by name). */
+const EYE_WISHLIST = [
+  { re: /^Piccadilly Circus$/i, title: 'Piccadilly Circus', place: 'London' },
+  { re: /^Trafalgar Square$/i, title: 'Trafalgar Square', place: 'London' },
+  { re: /Tower Bridge App/i, title: 'Tower Bridge approach', place: 'London' },
+  {
+    re: /^YONGE ST & DUNDAS ST$/i,
+    title: 'Yonge–Dundas Square',
+    place: 'Toronto',
+  },
+  {
+    re: /towards Sydney Harbour Bridge/i,
+    title: 'Sydney Harbour Bridge',
+    place: 'Sydney',
+  },
+  {
+    re: /Railway Square, George Street/i,
+    title: 'George Street, Railway Square',
+    place: 'Sydney',
+  },
+  {
+    re: /I-5 at MP 165\.4/i,
+    title: 'I-5 through downtown Seattle',
+    place: 'Seattle',
+  },
+  {
+    re: /Bay Bridge SAS Tower West/i,
+    title: 'Bay Bridge tower',
+    place: 'San Francisco',
+  },
+  {
+    re: /Hollywood Blvd/i,
+    title: 'US-101 at Hollywood Blvd',
+    place: 'Los Angeles',
+  },
+  {
+    re: /Helsinki Ruoholahti/i,
+    title: 'Ruoholahti, Helsinki',
+    place: 'Helsinki',
+  },
+  { re: /^Viru väljak \(suund Mere/i, title: 'Viru Square', place: 'Tallinn' },
+  {
+    re: /Diagonal - Maria Cristina/i,
+    title: 'Avinguda Diagonal',
+    place: 'Barcelona',
+  },
+  { re: /^8 Ave & 1 St SE$/i, title: 'Downtown Calgary', place: 'Calgary' },
+];
+
+function camCode(id) {
+  const m = /(\d{3,6})(?!.*\d)/.exec(String(id));
+  return m ? m[1].slice(-5) : String(id).slice(-5).toUpperCase();
+}
+
+async function verifyFrame(cam) {
+  const url = cctvFrameUrl(cam);
+  const response = await fetch(url, { cache: 'no-store' });
+  const kind = response.headers.get('x-cctv-source') || '';
+  const type = response.headers.get('content-type') || '';
+  if (
+    !response.ok ||
+    kind !== 'upstream-image' ||
+    !/^image\/(jpeg|png|gif|webp)/.test(type)
+  )
+    throw new Error(`no live frame (${kind || response.status})`);
+  const blob = await response.blob();
+  if (blob.size < 4000) throw new Error('frame too small');
+  EYE_FRAMES.set(cam.id, { blob, at: Date.now() });
+  return url;
+}
+
+/* ───────────────────────── Builder ───────────────────────── */
+
 export async function buildSituations(engine, { observer } = {}) {
   const { feeds } = engine;
   const now = Date.now();
   const get = (feed, opts, ms) => withBudget(feed.get(opts), ms);
+  const settled = await Promise.allSettled([
+    get(feeds.quakes),
+    get(feeds.cyclones),
+    get(feeds.fires),
+    get(feeds.military, { maxAgeMs: 60_000 }),
+    get(feeds.flights, { maxAgeMs: 60_000 }, FLIGHTS_BUDGET_MS),
+    get(feeds.stations),
+    get(feeds.launches),
+    get(feeds.flood),
+    get(feeds.radar),
+    get(feeds.lightning),
+    get(feeds.clouds),
+    get(feeds.tcm, undefined, SLOW_BUDGET_MS),
+    get(feeds.airQuality, undefined, SLOW_BUDGET_MS),
+    get(feeds.cctv, undefined, SLOW_BUDGET_MS),
+    get(feeds.transitCatalog),
+    get(feeds.starlink, undefined, SLOW_BUDGET_MS),
+    get(feeds.eonet),
+  ]);
   const [
     quakes,
     cyclones,
@@ -108,64 +354,52 @@ export async function buildSituations(engine, { observer } = {}) {
     stations,
     launches,
     flood,
-  ] = await Promise.allSettled([
-    get(feeds.quakes),
-    get(feeds.cyclones),
-    get(feeds.fires),
-    get(feeds.military, { maxAgeMs: 60_000 }),
-    get(feeds.flights, { maxAgeMs: 60_000 }, FLIGHTS_BUDGET_MS),
-    get(feeds.stations),
-    get(feeds.launches),
-    get(feeds.flood),
-  ]);
-  const ok = (r) => (r.status === 'fulfilled' ? r.value : null);
+    radar,
+    lightning,
+    clouds,
+    tcm,
+    airQuality,
+    cctv,
+    transitCatalog,
+    starlink,
+    eonet,
+  ] = settled.map((r) => (r.status === 'fulfilled' ? r.value : null));
+  // The jet stream grid is slow upstream (first load only; it is cached).
+  const jet =
+    feeds.jet.data ||
+    (await withBudget(feeds.jet.get(), 10_000).catch(() => null));
+
+  const t0 = performance.now();
   const out = [];
-  const tryAdd = (fn) => {
-    try {
-      const c = fn();
-      if (Array.isArray(c)) out.push(...c);
-      else if (c) out.push(c);
-    } catch (error) {
-      console.warn('[globe:situations]', error);
-    }
-  };
+  const omitted = [];
+  const tasks = [];
+  const timings = {};
+  const add = (name, fn) =>
+    tasks.push(
+      withBudget(Promise.resolve().then(fn), GENRE_BUDGET_MS)
+        .finally(() => {
+          timings[name] = Math.round(performance.now() - t0);
+        })
+        .then(
+          (c) => {
+            if (Array.isArray(c)) out.push(...c.filter(Boolean));
+            else if (c) out.push(c);
+            else omitted.push({ genre: name, reason: 'nothing to show now' });
+          },
+          (error) => {
+            omitted.push({
+              genre: name,
+              reason: error?.message || String(error),
+            });
+            console.warn(`[globe:situations] ${name}`, error);
+          },
+        ),
+    );
 
-  // Largest quake in the past 24 h.
-  tryAdd(() => {
-    const d = ok(quakes);
-    if (!d) return null;
-    const day = d.records.filter((q) => q.time && now - q.time < DAY);
-    if (!day.length) return null;
-    const q = day.reduce((a, b) => (b.mag > a.mag ? b : a));
-    return card({
-      id: `quake-${q.stableId}`,
-      kind: 'earthquake',
-      family: 'Hazards',
-      title: `M${q.mag.toFixed(1)} earthquake`,
-      subtitle: `Largest in 24 h · ${relTime(q.time, now)}`,
-      place: q.place || fmtLatLon(q.lat, q.lon),
-      lon: q.lon,
-      lat: q.lat,
-      radiusKm: 120,
-      camera: { height: 450_000, heading: 0, pitch: -65 },
-      layers: ['earthquakes'],
-      time: { start: q.time, end: now },
-      metrics: [
-        { label: 'Magnitude', value: Number(q.mag.toFixed(1)), unit: 'M' },
-        { label: 'Depth', value: Math.round(q.depthKm ?? 0), unit: 'km' },
-        { label: 'M2.5+ in 24 h', value: day.length, unit: '' },
-      ],
-      updatedAt: feeds.quakes.updatedAt,
-      source: 'USGS',
-      severity: q.mag,
-    });
-  });
-
-  // Active tropical cyclones.
-  tryAdd(() => {
-    const d = ok(cyclones);
-    if (!d) return null;
-    return d.records.slice(0, 4).map((s) => {
+  /* ── Cyclones: GIBS-style IR + NHC cone, track, wind radii ── */
+  add('cyclones', () => {
+    if (!cyclones) throw new Error('cyclone feeds unavailable');
+    return cyclones.records.slice(0, 3).map((s) => {
       const label =
         s.label ||
         {
@@ -178,152 +412,863 @@ export async function buildSituations(engine, { observer } = {}) {
         'Storm';
       const kmh = s.windKt ? Math.round(s.windKt * 1.852) : null;
       const lastTau = s.forecast?.at(-1)?.tauHours ?? 0;
-      return card({
-        id: `cyclone-${s.id}`,
-        kind: 'cyclone',
-        family: 'Hazards',
-        title: `${label} ${s.name}`,
-        subtitle: [
-          kmh ? `${kmh} km/h` : null,
-          s.pressureHpa ? `${s.pressureHpa} hPa` : null,
-          s.forecast?.length ? `${lastTau} h forecast track` : null,
-        ]
-          .filter(Boolean)
-          .join(' · '),
-        place: `${{ EP: 'Eastern Pacific', AL: 'Atlantic', CP: 'Central Pacific' }[s.basin] || basinOf(s.lat, s.lon)} basin`,
-        lon: s.lon,
-        lat: s.lat,
-        radiusKm: 700,
-        camera: { height: 2_600_000, heading: 0, pitch: -75 },
-        layers: ['cyclones'],
-        time: { start: s.t, end: s.t + lastTau * 3_600_000 },
-        metrics: [
-          ...(kmh ? [{ label: 'Wind', value: kmh, unit: 'km/h' }] : []),
-          ...(s.pressureHpa
-            ? [{ label: 'Pressure', value: s.pressureHpa, unit: 'hPa' }]
-            : []),
-          ...(s.movement?.speedKt
-            ? [
-                {
-                  label: 'Moving',
-                  value: Math.round(s.movement.speedKt * 1.852),
-                  unit: 'km/h',
-                },
-              ]
-            : []),
-        ],
-        updatedAt: feeds.cyclones.updatedAt,
-        source: s.source,
-        severity: 5 + (s.windKt || 0) / 40,
-      });
+      const radii = radiiFor(s, tcm)?.radii || null;
+      const r34 = radii?.find((r) => r.kt === 34);
+      const cat = stormCategory(s.windKt);
+      return card(
+        {
+          id: `cyclone-${s.id}`,
+          kind: 'cyclone',
+          family: 'Hazards',
+          band: 'orbit',
+          archetype: 'sensor',
+          telemetry: [
+            'ORBIT',
+            'LW IR',
+            up(`${s.classification || ''} ${s.name}`.trim()),
+            cat && cat !== 'TS' && cat !== 'TD' ? cat : null,
+            s.windKt ? `${s.windKt} KT` : null,
+            s.pressureHpa ? `${s.pressureHpa} HPA` : null,
+          ]
+            .filter(Boolean)
+            .join(' · '),
+          title: `${label} ${s.name}`,
+          subtitle: [
+            kmh ? `${kmh} km/h winds` : null,
+            s.movement?.directionDegrees != null && s.movement?.speedKt
+              ? `moving ${compass(s.movement.directionDegrees)} at ${Math.round(s.movement.speedKt * 1.852)} km/h`
+              : null,
+            describePlace(s.lat, s.lon),
+          ]
+            .filter(Boolean)
+            .join(' · '),
+          place: `${{ EP: 'Eastern Pacific', AL: 'Atlantic', CP: 'Central Pacific' }[s.basin] || basinOf(s.lat, s.lon)}`,
+          lon: s.lon,
+          lat: s.lat,
+          radiusKm: 700,
+          spanKm: Math.max(
+            1600,
+            (r34 ? Math.max(...r34.quadrantsKm) * 4 : 0) + 900,
+          ),
+          camera: { height: 2_600_000, heading: 0, pitch: -75 },
+          layers: ['cyclones', 'clouds', 'lightning', 'wind'],
+          time: { start: s.t, end: s.t + lastTau * HOUR },
+          metrics: [
+            ...(kmh ? [{ label: 'Wind', value: kmh, unit: 'km/h' }] : []),
+            ...(s.pressureHpa
+              ? [{ label: 'Pressure', value: s.pressureHpa, unit: 'hPa' }]
+              : []),
+            ...(r34
+              ? [
+                  {
+                    label: 'Gale radius',
+                    value: Math.round(Math.max(...r34.quadrantsKm)),
+                    unit: 'km',
+                  },
+                ]
+              : []),
+            ...(lastTau
+              ? [{ label: 'Forecast', value: lastTau, unit: 'h' }]
+              : []),
+          ],
+          headline: kmh
+            ? { value: kmh, unit: 'km/h', label: cat || 'wind' }
+            : undefined,
+          updatedAt: feeds.cyclones.updatedAt,
+          source: `${s.source}${radii ? ' · NHC wind radii' : ''} · IR: NOAA nowCOAST`,
+          severity: 6 + (s.windKt || 0) / 40,
+        },
+        {
+          type: 'cyclone',
+          storm: {
+            lon: s.lon,
+            lat: s.lat,
+            windKt: s.windKt,
+            cone: s.cone,
+            forecast: s.forecast || [],
+            pastTrack: s.pastTrack || null,
+            track: s.track || null,
+            radii,
+          },
+          irTime: clouds?.latest || null,
+          irBounds: clouds?.bounds || null,
+        },
+      );
     });
   });
 
-  // Fire cluster: Europe first if it has a real cluster, else the densest.
-  tryAdd(() => {
-    const d = ok(fires);
-    if (!d?.records.length) return null;
-    const hotspots = d.mode === 'hotspots';
-    const recent = hotspots
-      ? d.records.filter((f) => !f.t || now - f.t < DAY)
-      : d.records;
-    const cell = hotspots ? 1 : 4;
-    const europe = densestCell(
-      recent.filter((f) => regionOf(f.lat, f.lon) === 'Europe'),
-      cell,
+  /* ── Lightning storm cells (number + sensor) ── */
+  add('lightning', async () => {
+    if (!lightning) throw new Error('lightning manifest unavailable');
+    const canvas = await loadWeatherFrame('lightning', lightning.latest, 1024);
+    const cells = strikeCells(canvas, lightning.bounds);
+    const clusters = lightningClusters(cells);
+    if (!clusters.length) return null;
+    const picks = [clusters[0]];
+    const second = clusters.find(
+      (c) => haversineKm(c.lat, c.lon, clusters[0].lat, clusters[0].lon) > 1500,
     );
+    if (second && second.w > clusters[0].w * 0.15) picks.push(second);
+    const cards = [];
+    for (const [i, c] of picks.entries()) {
+      const lats = c.cells.map((x) => x.lat);
+      const lons = c.cells.map((x) => x.lon);
+      const bbox = {
+        west: Math.min(...lons) - 1,
+        east: Math.max(...lons) + 1,
+        south: Math.min(...lats) - 1,
+        north: Math.max(...lats) + 1,
+      };
+      const series = [];
+      if (i === 0) {
+        for (const t of lightning.times) {
+          try {
+            const f = await loadWeatherFrame('lightning', t, 1024, {
+              keep: t === lightning.latest,
+            });
+            series.push({
+              t: Date.parse(t),
+              v: Math.round(lightningArea(f, lightning.bounds, bbox)),
+            });
+          } catch {
+            /* a missing frame leaves a gap */
+          }
+        }
+      }
+      const area = lightningArea(canvas, lightning.bounds, bbox);
+      const where = describePlace(c.lat, c.lon);
+      const spanKm = Math.min(
+        1400,
+        Math.max(
+          350,
+          haversineKm(bbox.south, bbox.west, bbox.north, bbox.east) * 0.75,
+        ),
+      );
+      const inRadar =
+        radar &&
+        c.lon > radar.bounds.west &&
+        c.lon < radar.bounds.east &&
+        c.lat > radar.bounds.south &&
+        c.lat < radar.bounds.north;
+      const peakNote =
+        c.level >= 3 ? 'intense' : c.level === 2 ? 'strong' : 'active';
+      cards.push(
+        card(
+          {
+            id: `lightning-${Math.round(c.lat)}-${Math.round(c.lon)}`,
+            kind: 'lightning',
+            family: 'Weather',
+            band: 'sky',
+            archetype: i === 0 ? 'number' : 'sensor',
+            telemetry: `SKY · LIGHTNING · 15 MIN · ${fmtInt(area)} KM² · ${hhmm(Date.parse(lightning.latest))}`,
+            title:
+              i === 0
+                ? `Thunderstorms · ${where}`
+                : `Lightning cell · ${where}`,
+            subtitle: `${c.cells.length} lightning-active 0.5° cells, ${peakNote} strike density in the last 15 min`,
+            place: where,
+            lon: c.lon,
+            lat: c.lat,
+            radiusKm: spanKm / 2,
+            spanKm,
+            camera: { height: spanKm * 2200, heading: 0, pitch: -70 },
+            layers: ['lightning', 'clouds', ...(inRadar ? ['radar'] : [])],
+            time: {
+              start: Date.parse(lightning.times[0]),
+              end: Date.parse(lightning.latest),
+            },
+            metrics: [
+              { label: 'Active area', value: Math.round(area), unit: 'km²' },
+              { label: 'Active cells', value: c.cells.length, unit: '' },
+            ],
+            headline: {
+              value: fmtInt(area),
+              unit: 'km²',
+              label: 'lightning-active area, 15 min',
+            },
+            series,
+            seriesLabel: 'lightning-active area (km²) per 15 min',
+            updatedAt: Date.parse(lightning.latest),
+            source: 'NOAA nowCOAST lightning density (Vaisala NLDN/GLD360)',
+            severity: 4 + Math.min(2, c.w / 200) - i,
+          },
+          {
+            type: 'lightning',
+            times: lightning.times,
+            bounds: lightning.bounds,
+            radar: inRadar
+              ? { time: radar.latest, bounds: radar.bounds }
+              : null,
+            irTime: clouds?.latest || null,
+            irBounds: clouds?.bounds || null,
+          },
+        ),
+      );
+    }
+    return cards;
+  });
+
+  /* ── Rain over a US city (radar) ── */
+  add('radar', async () => {
+    if (!radar) throw new Error('radar manifest unavailable');
+    const canvas = await loadWeatherFrame('radar', radar.latest, 2048);
+    let best = null;
+    for (const [name, lon, lat] of US_METROS) {
+      const r = radarNear(canvas, radar.bounds, lat, lon, 45);
+      if (r.max == null) continue;
+      const score = r.max * 10 + r.heavy * 0.5 + r.wet * 0.02;
+      if (!best || score > best.score) best = { name, lon, lat, ...r, score };
+    }
+    if (!best || best.max < 20) return null;
+    const series = [];
+    for (const t of radar.times) {
+      try {
+        const f = await loadWeatherFrame('radar', t, 2048, {
+          keep: t === radar.latest,
+        });
+        const r = radarNear(f, radar.bounds, best.lat, best.lon, 45);
+        series.push({ t: Date.parse(t), v: r.max ?? 0 });
+      } catch {
+        /* gap */
+      }
+    }
+    const heavy = best.max >= 40;
+    return card(
+      {
+        id: `radar-${best.name.replace(/\W+/g, '-').toLowerCase()}`,
+        kind: 'radar',
+        family: 'Weather',
+        band: 'sky',
+        archetype: 'sensor',
+        telemetry: `SKY · MRMS · ${best.max} DBZ · ${up(best.name)} · ${hhmm(Date.parse(radar.latest))}`,
+        title: `${heavy ? 'Heavy rain' : best.max >= 30 ? 'Rain' : 'Showers'} over ${best.name}`,
+        subtitle: `Radar returns to ~${best.max} dBZ within 45 km${best.heavy ? ` · ${best.heavy} heavy-echo pixels` : ''}`,
+        place: best.name,
+        lon: best.lon,
+        lat: best.lat,
+        radiusKm: 60,
+        spanKm: 230,
+        camera: { height: 160_000, heading: 0, pitch: -55 },
+        layers: ['radar', 'lightning'],
+        time: {
+          start: Date.parse(radar.times[0]),
+          end: Date.parse(radar.latest),
+        },
+        metrics: [
+          { label: 'Peak reflectivity', value: best.max, unit: 'dBZ' },
+          { label: 'Frames', value: radar.times.length, unit: '' },
+        ],
+        headline: { value: best.max, unit: 'dBZ', label: 'peak reflectivity' },
+        series,
+        seriesLabel: 'peak reflectivity (dBZ) within 45 km',
+        updatedAt: Date.parse(radar.latest),
+        source:
+          'NOAA MRMS base reflectivity via nowCOAST (dBZ read from colour scale)',
+        severity: 2 + (best.max - 20) / 10,
+      },
+      {
+        type: 'radar',
+        time: radar.latest,
+        times: radar.times,
+        bounds: radar.bounds,
+      },
+    );
+  });
+
+  /* ── Jet stream core ── */
+  add('jet', () => {
+    if (!jet?.field) throw new Error('jet-stream grid not loaded yet');
+    const { field, speed } = jet;
+    let best = null;
+    for (let i = 0; i < speed.length; i++) {
+      const lat = field.la1 - Math.floor(i / field.nx) * field.dy;
+      if (Math.abs(lat) < 20 || Math.abs(lat) > 70) continue;
+      if (!best || speed[i] > best.s)
+        best = {
+          i,
+          s: speed[i],
+          lat,
+          lon: field.lo1 + (i % field.nx) * field.dx,
+        };
+    }
+    if (!best) return null;
+    const kt = Math.round(best.s * MPS_TO_KT);
+    const kmh = Math.round(best.s * 3.6);
+    const where = describePlace(best.lat, best.lon);
+    return card(
+      {
+        id: `jet-${best.lat}-${best.lon}`,
+        kind: 'jet',
+        family: 'Weather',
+        band: 'sky',
+        archetype: 'sensor',
+        telemetry: `SKY · 250 HPA · FL340 · ${kt} KT · ${fmtLatLon(best.lat, best.lon).replace(/°/g, '')}`,
+        title: `Jet stream core · ${kmh} km/h`,
+        subtitle: `Fastest 250 hPa wind on a 12° global grid · ${where}`,
+        place: where,
+        lon: best.lon,
+        lat: best.lat,
+        radiusKm: 2500,
+        spanKm: 7000,
+        camera: { height: 7_500_000, heading: 0, pitch: -90 },
+        layers: ['jet', 'clouds'],
+        metrics: [
+          { label: 'Core speed', value: kmh, unit: 'km/h' },
+          { label: 'Level', value: 250, unit: 'hPa' },
+        ],
+        headline: { value: kt, unit: 'kt', label: 'jet core at FL340' },
+        updatedAt: jet.time,
+        source: jet.source,
+        severity: 2 + Math.max(0, kt - 120) / 40,
+      },
+      { type: 'jet', windLevel: 'jet' },
+    );
+  });
+
+  /* ── Quakes: largest in 24 h (sensor) + global count (number) ── */
+  add('quakes', () => {
+    if (!quakes) throw new Error('USGS unavailable');
+    const day = quakes.records.filter((q) => q.time && now - q.time < DAY);
+    if (!day.length) return null;
+    const q = day.reduce((a, b) => (b.mag > a.mag ? b : a));
+    const nearby = quakes.records
+      .filter((r) => r !== q && haversineKm(q.lat, q.lon, r.lat, r.lon) < 400)
+      .map((r) => ({ lon: r.lon, lat: r.lat, mag: r.mag, time: r.time }));
+    const series = [];
+    for (let h = 23; h >= 0; h--) {
+      const t0 = now - (h + 1) * HOUR;
+      series.push({
+        t: t0 + HOUR,
+        v: quakes.records.filter((r) => r.time >= t0 && r.time < t0 + HOUR)
+          .length,
+      });
+    }
+    const biggest = card(
+      {
+        id: `quake-${q.stableId}`,
+        kind: 'earthquake',
+        family: 'Hazards',
+        band: 'ground',
+        archetype: 'sensor',
+        telemetry: `GROUND · M${q.mag.toFixed(1)} · ${Math.round(q.depthKm ?? 0)} KM DEEP · ${hhmmss(q.time)}`,
+        title: `M${q.mag.toFixed(1)} earthquake`,
+        subtitle: `Largest in 24 h · ${relTime(q.time, now)} · ${nearby.length} other M2.5+ within 400 km this week`,
+        place: q.place || describePlace(q.lat, q.lon),
+        lon: q.lon,
+        lat: q.lat,
+        radiusKm: 120,
+        spanKm: 260,
+        camera: { height: 450_000, heading: 0, pitch: -65 },
+        layers: ['earthquakes'],
+        time: { start: q.time, end: now },
+        metrics: [
+          { label: 'Magnitude', value: Number(q.mag.toFixed(1)), unit: 'M' },
+          { label: 'Depth', value: Math.round(q.depthKm ?? 0), unit: 'km' },
+          { label: 'M2.5+ in 24 h', value: day.length, unit: '' },
+        ],
+        headline: { value: q.mag.toFixed(1), unit: 'M', label: 'magnitude' },
+        updatedAt: feeds.quakes.updatedAt,
+        source: 'USGS',
+        severity: q.mag,
+      },
+      {
+        type: 'quake',
+        quake: { lon: q.lon, lat: q.lat, mag: q.mag, depthKm: q.depthKm },
+        nearby,
+      },
+    );
+    const busiest = densestCell(day, 30) || q;
+    const count = card(
+      {
+        id: 'quakes-24h',
+        kind: 'earthquake',
+        family: 'Hazards',
+        band: 'ground',
+        archetype: 'number',
+        telemetry: `GROUND · USGS · ${day.length} EVENTS M2.5+ · 24 H`,
+        title: `${day.length} earthquakes M2.5+ in 24 h`,
+        subtitle: `Worldwide · largest M${q.mag.toFixed(1)} ${q.place ? `· ${q.place}` : ''}`,
+        place: 'Worldwide',
+        lon: busiest.lon,
+        lat: Math.max(-50, Math.min(55, busiest.lat)),
+        radiusKm: 4000,
+        spanKm: 11000,
+        camera: { height: 18_000_000, heading: 0, pitch: -90 },
+        layers: ['earthquakes'],
+        time: { start: now - DAY, end: now },
+        metrics: [{ label: 'M2.5+ in 24 h', value: day.length, unit: '' }],
+        headline: { value: day.length, unit: '', label: 'quakes M2.5+ · 24 h' },
+        series,
+        seriesLabel: 'M2.5+ quakes per hour',
+        updatedAt: feeds.quakes.updatedAt,
+        source: 'USGS',
+        severity: 2,
+      },
+      {
+        type: 'quake-world',
+        quakes: quakes.records.slice(0, 900).map((r) => ({
+          lon: r.lon,
+          lat: r.lat,
+          mag: r.mag,
+          time: r.time,
+        })),
+      },
+    );
+    return [biggest, count];
+  });
+
+  /* ── Fires with smoke direction from wind ── */
+  add('fires', async () => {
+    if (!fires?.records.length) throw new Error('fire feeds unavailable');
+    const hotspots = fires.mode === 'hotspots';
+    const recent = hotspots
+      ? fires.records.filter((f) => !f.t || now - f.t < DAY)
+      : fires.records;
+    const cell = hotspots ? 1 : 4;
+    // Prescribed burns are real but not news: prefer wildfires.
+    const wild = recent.filter(
+      (f) => !/prescribed|\bRX\b/i.test(f.title || ''),
+    );
+    const pool = wild.length ? wild : recent;
+    const largest = hotspots
+      ? null
+      : pool.reduce(
+          (a, b) => ((b.acres ?? 0) > (a.acres ?? 0) ? b : a),
+          pool[0],
+        );
     const best =
-      europe && europe.count >= (hotspots ? 20 : 2)
-        ? europe
-        : densestCell(recent, cell);
+      largest?.acres > 0
+        ? {
+            count: pool.filter(
+              (f) => haversineKm(f.lat, f.lon, largest.lat, largest.lon) < 300,
+            ).length,
+            lat: largest.lat,
+            lon: largest.lon,
+            items: [
+              largest,
+              ...pool.filter(
+                (f) =>
+                  f !== largest &&
+                  haversineKm(f.lat, f.lon, largest.lat, largest.lon) < 60,
+              ),
+            ],
+          }
+        : densestCell(pool, cell);
     if (!best) return null;
-    const region = regionOf(best.lat, best.lon);
     const sample = best.items.find(
       (f) => f.title && f.title !== 'Fire hotspot',
     );
-    return card({
-      id: `fires-${best.lat.toFixed(1)}-${best.lon.toFixed(1)}`,
-      kind: 'fires',
-      family: 'Hazards',
-      title: `Fire cluster · ${region}`,
-      subtitle: hotspots
-        ? `${best.count} hotspots in 24 h`
-        : sample
-          ? sample.title
-          : `${best.count} active wildfire events`,
-      place: sample?.title?.split(',').slice(1).join(',').trim() || region,
-      lon: best.lon,
-      lat: best.lat,
-      radiusKm: hotspots ? 90 : 220,
-      camera: { height: hotspots ? 260_000 : 700_000, heading: 0, pitch: -60 },
-      layers: ['fires'],
-      metrics: [
+    const focus = sample || best.items[0];
+    let w = null;
+    try {
+      w = await withBudget(
+        pointWind.get(`${focus.lat.toFixed(1)}:${focus.lon.toFixed(1)}`, {
+          lon: focus.lon,
+          lat: focus.lat,
+        }),
+        8000,
+      );
+    } catch {
+      /* no plume without wind */
+    }
+    const to = w ? (w.fromDeg + 180) % 360 : null;
+    const where = describePlace(focus.lat, focus.lon);
+    return card(
+      {
+        id: `fires-${focus.lat.toFixed(1)}-${focus.lon.toFixed(1)}`,
+        kind: 'fires',
+        family: 'Hazards',
+        band: 'ground',
+        archetype: 'sensor',
+        telemetry: [
+          'GROUND',
+          hotspots ? 'VIIRS/MODIS' : 'EONET',
+          w ? `WIND ${Math.round(w.speedKmh)} KM/H → ${compass(to)}` : null,
+          fmtLatLon(focus.lat, focus.lon).replace(/°/g, ''),
+        ]
+          .filter(Boolean)
+          .join(' · '),
+        title: sample
+          ? sample.title.split(',')[0]
+          : `Fire cluster · ${regionOf(best.lat, best.lon)}`,
+        subtitle: [
+          hotspots
+            ? `${best.count} hotspots in 24 h`
+            : `${best.count} open wildfire event${best.count > 1 ? 's' : ''} nearby`,
+          w
+            ? `smoke drifting ${compass(to)} on ${Math.round(w.speedKmh)} km/h winds`
+            : null,
+        ]
+          .filter(Boolean)
+          .join(' · '),
+        place: where,
+        lon: focus.lon,
+        lat: focus.lat,
+        radiusKm: 30,
+        spanKm: 70,
+        camera: { height: 80_000, heading: to ?? 0, pitch: -45 },
+        layers: ['fires', 'wind', 'air-quality'],
+        metrics: [
+          {
+            label: hotspots ? 'Hotspots' : 'Events',
+            value: best.count,
+            unit: '',
+          },
+          ...(w
+            ? [{ label: 'Wind', value: Math.round(w.speedKmh), unit: 'km/h' }]
+            : []),
+          { label: 'Worldwide', value: recent.length, unit: '' },
+        ],
+        updatedAt: feeds.fires.updatedAt,
+        source: `${fires.source}${w ? ' · wind: Open-Meteo' : ''}`,
+        severity: 3 + Math.min(2, best.count / 50),
+      },
+      {
+        type: 'fire',
+        fires: best.items.map((f) => ({
+          lon: f.lon,
+          lat: f.lat,
+          frp: f.frp ?? null,
+          acres: f.acres ?? null,
+        })),
+        wind: w ? { toDeg: to, speedKmh: w.speedKmh } : null,
+      },
+    );
+  });
+
+  /* ── Aircraft: squawks, busiest airport, Fort Novosel, military ── */
+  let flightRecords = flights?.records || [];
+  // OpenSky down: the proxy answers per anchor (250 nm of adsb.lol), so a
+  // few busy regions are sampled to keep squawks and airports meaningful.
+  if (!flights || flights.regional) {
+    const anchors = [
+      [51.47, -0.45],
+      [40.64, -73.78],
+      [33.64, -84.43],
+      [50.04, 8.57],
+      [35.55, 139.78],
+    ];
+    const extra = await Promise.allSettled(
+      anchors.map(([lat, lon]) =>
+        withBudget(
+          feeds.regionalFlights.get(`${lat}:${lon}`, { lat, lon }),
+          FLIGHTS_BUDGET_MS,
+        ),
+      ),
+    );
+    const byId = new Map(flightRecords.map((r) => [r.id, r]));
+    for (const r of extra)
+      if (r.status === 'fulfilled')
+        for (const f of r.value.records) byId.set(f.id, f);
+    flightRecords = [...byId.values()];
+  }
+  const aircraftScene = (lon, lat, km, list) =>
+    list
+      .filter((r) => haversineKm(lat, lon, r.lat, r.lon) <= km)
+      .slice(0, 400)
+      .map((r) => ({
+        lon: r.lon,
+        lat: r.lat,
+        heading: r.heading,
+        speed: r.speed,
+        altM: r.altM,
+        onGround: r.onGround,
+        helicopter: r.helicopter,
+        emergency: r.emergency,
+        military: r.military,
+      }));
+
+  add('squawk', () => {
+    if (!flightRecords.length) throw new Error('flight feed unavailable');
+    const em = flightRecords.filter((r) => r.emergency && !r.onGround);
+    if (!em.length) return null;
+    return em.slice(0, 2).map((r) => {
+      const meaning = {
+        7700: 'General emergency',
+        7600: 'Radio failure',
+        7500: 'Unlawful interference',
+      }[r.squawk];
+      const kt = Number.isFinite(r.speed)
+        ? Math.round(r.speed * MPS_TO_KT)
+        : null;
+      const where = describePlace(r.lat, r.lon);
+      const descending = r.vRate != null && r.vRate < -3;
+      return card(
         {
-          label: hotspots ? 'Hotspots' : 'Events',
-          value: best.count,
-          unit: '',
+          id: `squawk-${r.id}`,
+          kind: 'squawk',
+          family: 'Sky',
+          band: 'sky',
+          archetype: 'track',
+          telemetry: [
+            'SKY',
+            fl(r.altM),
+            kt ? `${kt} KT` : null,
+            `SQ ${r.squawk}`,
+            up(r.callsign),
+          ]
+            .filter(Boolean)
+            .join(' · '),
+          title: `${r.callsign} squawking ${r.squawk}`,
+          subtitle: [
+            meaning,
+            `${fmtInt(Math.round((r.altM * M_TO_FT) / 100) * 100)} ft`,
+            descending
+              ? `descending ${fmtInt(Math.abs(r.vRate) * 196.85)} ft/min`
+              : null,
+            where,
+          ]
+            .filter(Boolean)
+            .join(' · '),
+          place: where,
+          lon: r.lon,
+          lat: r.lat,
+          radiusKm: 60,
+          spanKm: 220,
+          camera: { height: 120_000, heading: r.heading, pitch: -45 },
+          layers: ['squawk', 'flights'],
+          metrics: [
+            { label: 'Squawk', value: r.squawk, unit: '' },
+            {
+              label: 'Altitude',
+              value: Math.round(r.altM * M_TO_FT),
+              unit: 'ft',
+            },
+            ...(kt ? [{ label: 'Ground speed', value: kt, unit: 'kt' }] : []),
+          ],
+          headline: { value: r.squawk, unit: '', label: meaning },
+          updatedAt: feeds.flights.updatedAt,
+          source: flights?.source || 'adsb.lol (regional snapshots)',
+          severity: 7,
         },
-        { label: 'Worldwide', value: recent.length, unit: '' },
-      ],
-      updatedAt: feeds.fires.updatedAt,
-      source: d.source,
-      severity: 3 + Math.min(2, best.count / 50),
+        {
+          type: 'aircraft',
+          focus: {
+            lon: r.lon,
+            lat: r.lat,
+            heading: r.heading,
+            speed: r.speed,
+            altM: r.altM,
+            emergency: true,
+          },
+          aircraft: aircraftScene(r.lon, r.lat, 160, flightRecords),
+        },
+      );
     });
   });
 
-  // Military air activity hotspot.
-  tryAdd(() => {
-    const d = ok(military);
-    if (!d?.records.length) return null;
-    const airborne = d.records.filter((r) => !r.onGround);
+  add('airport', () => {
+    if (!flightRecords.length) throw new Error('flight feed unavailable');
+    let best = null;
+    for (const ap of AIRPORTS) {
+      let n = 0;
+      for (const r of flightRecords) {
+        if (Math.abs(r.lat - ap.lat) > 0.6 || Math.abs(r.lon - ap.lon) > 0.9)
+          continue;
+        if (r.altM > 4000) continue;
+        if (haversineKm(ap.lat, ap.lon, r.lat, r.lon) <= 50) n++;
+      }
+      if (!best || n > best.n) best = { ...ap, n };
+    }
+    if (!best?.n) return null;
+    return card(
+      {
+        id: `airport-${best.code}`,
+        kind: 'airport',
+        family: 'Sky',
+        band: 'sky',
+        archetype: 'sensor',
+        telemetry: `SKY · ${best.code} · ${best.n} AIRCRAFT < FL130 · 50 KM`,
+        title: `Busiest airspace · ${best.code}`,
+        subtitle: `${best.n} aircraft below 4 km within 50 km of ${best.name}`,
+        place: best.name,
+        lon: best.lon,
+        lat: best.lat,
+        radiusKm: 40,
+        spanKm: 110,
+        camera: { height: 60_000, heading: 20, pitch: -45 },
+        layers: ['flights', 'ga', 'helicopters'],
+        metrics: [
+          { label: 'Low aircraft', value: best.n, unit: '' },
+          {
+            label: 'Airborne worldwide',
+            value: flightRecords.filter((r) => !r.onGround).length,
+            unit: '',
+          },
+        ],
+        headline: { value: best.n, unit: '', label: 'aircraft below FL130' },
+        updatedAt: feeds.flights.updatedAt,
+        source: flights?.source || 'adsb.lol (regional snapshots)',
+        severity: 1.5,
+      },
+      {
+        type: 'aircraft',
+        aircraft: aircraftScene(best.lon, best.lat, 90, flightRecords),
+        airport: { lon: best.lon, lat: best.lat },
+      },
+    );
+  });
+
+  add('fort-novosel', async () => {
+    let records = flightRecords;
+    let source = flights?.source || 'OpenSky Network';
+    const near = (r) =>
+      haversineKm(FORT_NOVOSEL.lat, FORT_NOVOSEL.lon, r.lat, r.lon) <=
+      FORT_NOVOSEL.radiusKm;
+    if (!records.some(near)) {
+      const reg = await withBudget(
+        feeds.regionalFlights.get('novosel', {
+          lat: FORT_NOVOSEL.lat,
+          lon: FORT_NOVOSEL.lon,
+        }),
+        FLIGHTS_BUDGET_MS,
+      ).catch(() => null);
+      if (reg) {
+        records = reg.records;
+        source = 'adsb.lol / OpenSky';
+      }
+    }
+    const local = records.filter(near);
+    const mil = (military?.records || []).filter(
+      (r) => r.helicopter && near(r),
+    );
+    const helis = [...local.filter((r) => r.helicopter), ...mil];
+    const lowSlow = local.filter(
+      (r) =>
+        !r.onGround && r.altM < 900 && (r.speed ?? 99) < 60 && !r.helicopter,
+    );
+    if (!helis.length && !lowSlow.length) return null;
+    const lead = helis[0] || lowSlow[0];
+    return card(
+      {
+        id: 'fort-novosel',
+        kind: 'helicopters',
+        family: 'Sky',
+        section: 'always',
+        band: 'sky',
+        archetype: 'track',
+        telemetry:
+          `SKY · KOZR · ${helis.length} ROTOR · ${lowSlow.length} LOW+SLOW · ${lead ? fl(lead.altM) : ''}`.replace(
+            / · $/,
+            '',
+          ),
+        title: 'Helicopter school circuits',
+        subtitle: `${helis.length} rotorcraft · ${lowSlow.length} low & slow contacts over Fort Novosel`,
+        place: 'Fort Novosel, Alabama',
+        lon: FORT_NOVOSEL.lon,
+        lat: FORT_NOVOSEL.lat,
+        radiusKm: 35,
+        spanKm: 80,
+        camera: { height: 45_000, heading: 340, pitch: -45 },
+        layers: ['helicopters', 'military', 'ga'],
+        metrics: [
+          { label: 'Rotorcraft', value: helis.length, unit: '' },
+          { label: 'Low & slow', value: lowSlow.length, unit: '' },
+          { label: 'All aircraft', value: local.length, unit: '' },
+        ],
+        headline: {
+          value: helis.length + lowSlow.length,
+          unit: '',
+          label: 'training contacts',
+        },
+        updatedAt: now,
+        source,
+        severity: 1.2,
+      },
+      {
+        type: 'aircraft',
+        aircraft: aircraftScene(FORT_NOVOSEL.lon, FORT_NOVOSEL.lat, 70, [
+          ...local,
+          ...mil,
+        ]),
+      },
+    );
+  });
+
+  add('military', () => {
+    if (!military?.records.length) throw new Error('military feed unavailable');
+    const airborne = military.records.filter((r) => !r.onGround);
     const best = densestCell(airborne, 6);
     if (!best || best.count < 2) return null;
     const types = [
       ...new Set(best.items.map((r) => r.type).filter(Boolean)),
     ].slice(0, 3);
-    return card({
-      id: `military-${Math.round(best.lat)}-${Math.round(best.lon)}`,
-      kind: 'military',
-      family: 'Sky',
-      title: `Military air activity · ${regionOf(best.lat, best.lon)}`,
-      subtitle: `${best.count} military aircraft${types.length ? ` · ${types.join(', ')}` : ''}`,
-      lon: best.lon,
-      lat: best.lat,
-      radiusKm: 260,
-      camera: { height: 900_000, heading: 0, pitch: -70 },
-      layers: ['military'],
-      metrics: [
-        { label: 'In area', value: best.count, unit: '' },
-        { label: 'Tracked worldwide', value: airborne.length, unit: '' },
-      ],
-      updatedAt: feeds.military.updatedAt,
-      source: 'adsb.lol',
-      severity: 2.5,
-    });
+    const where = describePlace(best.lat, best.lon);
+    return card(
+      {
+        id: `military-${Math.round(best.lat)}-${Math.round(best.lon)}`,
+        kind: 'military',
+        family: 'Sky',
+        band: 'sky',
+        archetype: 'sensor',
+        telemetry:
+          `SKY · MIL · ${best.count} AIRCRAFT · ${types.join(' ').toUpperCase()}`.trim(),
+        title: `Military air activity · ${regionOf(best.lat, best.lon)}`,
+        subtitle: `${best.count} military aircraft${types.length ? ` · ${types.join(', ')}` : ''} · ${where}`,
+        place: where,
+        lon: best.lon,
+        lat: best.lat,
+        radiusKm: 260,
+        spanKm: Math.max(
+          160,
+          Math.min(
+            900,
+            2.6 *
+              Math.max(
+                ...best.items.map((r) =>
+                  haversineKm(best.lat, best.lon, r.lat, r.lon),
+                ),
+              ),
+          ),
+        ),
+        camera: { height: 900_000, heading: 0, pitch: -70 },
+        layers: ['military'],
+        metrics: [
+          { label: 'In area', value: best.count, unit: '' },
+          { label: 'Tracked worldwide', value: airborne.length, unit: '' },
+        ],
+        updatedAt: feeds.military.updatedAt,
+        source: 'adsb.lol',
+        severity: 2.5,
+      },
+      {
+        type: 'aircraft',
+        military: true,
+        aircraft: best.items.map((r) => ({
+          lon: r.lon,
+          lat: r.lat,
+          heading: r.heading,
+          speed: r.speed,
+          altM: r.altM,
+          military: true,
+          helicopter: r.helicopter,
+        })),
+      },
+    );
   });
 
-  // ISS now (+ next pass when we know where the viewer is).
-  tryAdd(() => {
-    const d = ok(stations);
-    const iss = d?.entries.find((e) => e.line1.slice(2, 7).trim() === '25544');
-    if (!iss) return null;
+  /* ── ISS and the newest Starlink train ── */
+  add('iss', () => {
+    const iss = stations?.entries.find(
+      (e) => e.line1.slice(2, 7).trim() === '25544',
+    );
+    if (!iss) throw new Error('CelesTrak stations unavailable');
     const satrec = twoline2satrec(iss.line1, iss.line2);
     const p = satPosition(satrec, now);
     if (!p) return null;
+    const altKm = Math.round(p.altM / 1000);
+    const kms = (p.speedMps / 1000).toFixed(2);
+    let subtitle = `Over ${describePlace(p.lat, p.lon)} · ${altKm} km up`;
+    let passTag = null;
     const metrics = [
-      { label: 'Altitude', value: Math.round(p.altM / 1000), unit: 'km' },
+      { label: 'Altitude', value: altKm, unit: 'km' },
       {
         label: 'Speed',
         value: Math.round((p.speedMps * 3.6) / 100) * 100,
         unit: 'km/h',
       },
     ];
-    let subtitle = `Over ${regionOf(p.lat, p.lon)} · ${fmtLatLon(p.lat, p.lon)}`;
-    if (
-      observer &&
-      Number.isFinite(observer.lat) &&
-      Number.isFinite(observer.lon)
-    ) {
+    if (observer && Number.isFinite(observer.lat)) {
       const pass = findNextIssPass({
         satrec,
         latDeg: observer.lat,
@@ -333,6 +1278,7 @@ export async function buildSituations(engine, { observer } = {}) {
       });
       if (pass) {
         subtitle = `Next pass over you ${relTime(pass.riseMs, now)} · max ${Math.round(pass.maxElevDeg)}°`;
+        passTag = `PASS ${hhmm(pass.riseMs).replace('Z', '')}`;
         metrics.push({
           label: 'Next pass',
           value: new Date(pass.riseMs).toISOString(),
@@ -340,227 +1286,714 @@ export async function buildSituations(engine, { observer } = {}) {
         });
       }
     }
-    return card({
-      id: 'iss-now',
-      kind: 'iss',
-      family: 'Orbit',
-      title: 'ISS now',
-      subtitle,
-      place: regionOf(p.lat, p.lon),
-      lon: p.lon,
-      lat: p.lat,
-      radiusKm: 900,
-      camera: { height: 5_500_000, heading: 0, pitch: -90 },
-      layers: ['iss', 'satellites'],
-      metrics,
-      updatedAt: now,
-      source: 'CelesTrak TLE · SGP4',
-      severity: 2,
-    });
+    return card(
+      {
+        id: 'iss-now',
+        kind: 'iss',
+        family: 'Orbit',
+        band: 'orbit',
+        archetype: 'track',
+        telemetry: ['ORBIT', 'ISS', `${altKm} KM`, `${kms} KM/S`, passTag]
+          .filter(Boolean)
+          .join(' · '),
+        title: 'ISS now',
+        subtitle,
+        place: regionOf(p.lat, p.lon),
+        lon: p.lon,
+        lat: p.lat,
+        radiusKm: 2500,
+        spanKm: 9000,
+        camera: { height: 5_500_000, heading: 0, pitch: -90 },
+        layers: ['iss', 'satellites'],
+        metrics,
+        headline: { value: kms, unit: 'km/s', label: `${altKm} km up` },
+        updatedAt: now,
+        source: 'CelesTrak TLE · SGP4',
+        severity: 2,
+      },
+      {
+        type: 'orbit',
+        sats: [{ line1: iss.line1, line2: iss.line2, name: 'ISS', main: true }],
+        at: now,
+        observer: observer || null,
+      },
+    );
   });
 
-  // Busiest airport airspace now, and the Fort Novosel helicopter school.
-  tryAdd(() => {
-    const d = ok(flights) || { records: [], source: 'OpenSky Network' };
-    const flightsLive = d.records.length > 0;
-    const cards = [];
-    let best = null;
-    for (const ap of AIRPORTS) {
-      let n = 0;
-      for (const r of d.records) {
-        if (Math.abs(r.lat - ap.lat) > 0.6 || Math.abs(r.lon - ap.lon) > 0.9)
-          continue;
-        if (r.altM > 4000) continue;
-        if (haversineKm(ap.lat, ap.lon, r.lat, r.lon) <= 50) n++;
-      }
-      if (!best || n > best.n) best = { ...ap, n };
+  add('starlink', () => {
+    const entries = starlink?.entries;
+    if (!entries?.length) throw new Error('Starlink TLEs unavailable');
+    // International designator YYNNN: the newest launch still flying in a train.
+    const byLaunch = new Map();
+    for (const e of entries) {
+      const id = e.line1.slice(9, 14).trim();
+      if (!/^\d{5}$/.test(id)) continue;
+      if (!byLaunch.has(id)) byLaunch.set(id, []);
+      byLaunch.get(id).push(e);
     }
-    if (flightsLive && best && best.n > 0)
-      cards.push(
-        card({
-          id: `airport-${best.code}`,
-          kind: 'airport',
-          family: 'Sky',
-          title: `Busiest airspace · ${best.code}`,
-          subtitle: `${best.n} aircraft below 4 km within 50 km of ${best.name}`,
-          place: best.name,
-          lon: best.lon,
-          lat: best.lat,
-          radiusKm: 40,
-          camera: { height: 60_000, heading: 20, pitch: -45 },
-          layers: ['flights', 'ga', 'helicopters'],
+    const launchKey = (k) =>
+      (Number(k.slice(0, 2)) < 57 ? 2000 : 1900) * 1000 +
+      Number(k.slice(0, 2)) * 1000 +
+      Number(k.slice(2));
+    const launchesSorted = [...byLaunch.keys()].sort(
+      (a, b) => launchKey(b) - launchKey(a),
+    );
+    for (const key of launchesSorted.slice(0, 4)) {
+      const group = byLaunch.get(key);
+      if (group.length < 8) continue;
+      const pts = [];
+      for (const e of group) {
+        try {
+          const p = satPosition(twoline2satrec(e.line1, e.line2), now);
+          if (p) pts.push({ ...p, e });
+        } catch {
+          /* skip */
+        }
+      }
+      if (pts.length < 8) continue;
+      // A train: the largest group still within 1,500 km of one satellite.
+      let core = [];
+      let c = null;
+      for (const p of pts) {
+        const n = pts.filter(
+          (q) => haversineKm(p.lat, p.lon, q.lat, q.lon) < 1500,
+        );
+        if (n.length > core.length) {
+          core = n;
+          c = p;
+        }
+      }
+      if (core.length < 8) continue;
+      pts.length = 0;
+      pts.push(...core);
+      const spread = Math.max(
+        ...pts.map((p) => haversineKm(c.lat, c.lon, p.lat, p.lon)),
+      );
+      const year = 2000 + Number(key.slice(0, 2));
+      const altKm = Math.round(
+        pts.reduce((a, p) => a + p.altM, 0) / pts.length / 1000,
+      );
+      return card(
+        {
+          id: `starlink-${key}`,
+          kind: 'starlink',
+          family: 'Orbit',
+          band: 'orbit',
+          archetype: 'track',
+          telemetry: `ORBIT · STARLINK ${year}-${key.slice(2)} · ${pts.length} SATS · ${altKm} KM`,
+          title: `Starlink train · ${pts.length} satellites`,
+          subtitle: `Launch ${year}-${key.slice(2)} still flying in formation · over ${describePlace(c.lat, c.lon)}`,
+          place: regionOf(c.lat, c.lon),
+          lon: c.lon,
+          lat: c.lat,
+          radiusKm: 2000,
+          spanKm: Math.max(5000, spread * 2.6),
+          camera: { height: 4_500_000, heading: 0, pitch: -90 },
+          layers: ['starlink'],
           metrics: [
-            { label: 'Low aircraft', value: best.n, unit: '' },
+            { label: 'Satellites', value: pts.length, unit: '' },
+            { label: 'Mean altitude', value: altKm, unit: 'km' },
             {
-              label: 'Airborne worldwide',
-              value: d.records.filter((r) => !r.onGround).length,
-              unit: '',
+              label: 'Train length',
+              value: Math.round(spread * 2),
+              unit: 'km',
             },
           ],
-          updatedAt: feeds.flights.updatedAt,
-          source: d.source,
-          severity: 1.5,
-        }),
+          headline: {
+            value: pts.length,
+            unit: '',
+            label: 'satellites in the train',
+          },
+          updatedAt: now,
+          source: 'CelesTrak TLE · SGP4',
+          severity: 1.8,
+        },
+        {
+          type: 'orbit',
+          sats: pts.slice(0, 60).map((p, i) => ({
+            line1: p.e.line1,
+            line2: p.e.line2,
+            main: i === Math.floor(pts.length / 2),
+          })),
+          at: now,
+          train: true,
+        },
       );
-    const near = d.records.filter(
-      (r) =>
-        haversineKm(FORT_NOVOSEL.lat, FORT_NOVOSEL.lon, r.lat, r.lon) <=
-        FORT_NOVOSEL.radiusKm,
-    );
-    const mil = ok(military)?.records || [];
-    const helis = [
-      ...near.filter((r) => r.helicopter),
-      ...mil.filter(
-        (r) =>
-          r.helicopter &&
-          haversineKm(FORT_NOVOSEL.lat, FORT_NOVOSEL.lon, r.lat, r.lon) <=
-            FORT_NOVOSEL.radiusKm,
-      ),
-    ];
-    const lowSlow = near.filter(
-      (r) =>
-        !r.onGround && r.altM < 900 && (r.speed ?? 99) < 60 && !r.helicopter,
-    );
-    cards.push(
-      card({
-        id: 'fort-novosel',
-        kind: 'helicopters',
-        family: 'Sky',
-        section: 'always',
-        title: 'Helicopter school circuits',
-        subtitle: !flightsLive
-          ? 'US Army Aviation Center of Excellence · live traffic unavailable'
-          : helis.length || lowSlow.length
-            ? `${helis.length} rotorcraft · ${lowSlow.length} low & slow contacts over Fort Novosel`
-            : 'Quiet right now · US Army Aviation Center of Excellence',
-        place: 'Fort Novosel, Alabama',
-        lon: FORT_NOVOSEL.lon,
-        lat: FORT_NOVOSEL.lat,
-        radiusKm: 35,
-        camera: { height: 45_000, heading: 340, pitch: -45 },
-        layers: ['helicopters', 'military', 'ga'],
+    }
+    // No train in formation right now: the constellation over the night side.
+    const sun = subsolarPoint(now);
+    const center =
+      observer && Number.isFinite(observer.lat)
+        ? { lat: observer.lat, lon: observer.lon }
+        : { lat: 40, lon: ((sun.lon + 180 - 25 + 540) % 360) - 180 };
+    const sats = [];
+    let overhead = 0;
+    for (const e of entries) {
+      try {
+        const p = satPosition(twoline2satrec(e.line1, e.line2), now);
+        if (!p) continue;
+        sats.push(e);
+        if (haversineKm(center.lat, center.lon, p.lat, p.lon) < 2000)
+          overhead++;
+      } catch {
+        /* skip */
+      }
+    }
+    if (!sats.length) return null;
+    const where = observer ? 'you' : describePlace(center.lat, center.lon);
+    return card(
+      {
+        id: 'starlink-shell',
+        kind: 'starlink',
+        family: 'Orbit',
+        band: 'orbit',
+        archetype: 'number',
+        telemetry: `ORBIT · STARLINK · ${fmtInt(sats.length)} SATS · ${overhead} WITHIN 2,000 KM`,
+        title: `${fmtInt(sats.length)} Starlink satellites in orbit`,
+        subtitle: `${overhead} within 2,000 km of ${where} right now`,
+        place: observer ? 'Over you' : describePlace(center.lat, center.lon),
+        lon: center.lon,
+        lat: center.lat,
+        radiusKm: 3000,
+        spanKm: 8000,
+        camera: { height: 9_000_000, heading: 0, pitch: -90 },
+        layers: ['starlink'],
         metrics: [
-          { label: 'Rotorcraft', value: helis.length, unit: '' },
-          { label: 'Low & slow', value: lowSlow.length, unit: '' },
-          { label: 'All aircraft', value: near.length, unit: '' },
+          { label: 'In orbit', value: sats.length, unit: '' },
+          { label: 'Within 2,000 km', value: overhead, unit: '' },
         ],
-        updatedAt: feeds.flights.updatedAt || now,
-        source: d.source,
-        live: flightsLive,
-        severity: helis.length ? 1.2 : 0.2,
-      }),
+        headline: {
+          value: fmtInt(sats.length),
+          unit: '',
+          label: 'Starlink satellites',
+        },
+        updatedAt: now,
+        source: 'CelesTrak TLE · SGP4',
+        severity: 1.4,
+      },
+      {
+        type: 'constellation',
+        sats: sats.map((e) => ({ line1: e.line1, line2: e.line2 })),
+        at: now,
+      },
     );
-    return cards;
   });
 
-  // Next launch.
-  tryAdd(() => {
-    const d = ok(launches);
-    const next = d?.records.find((r) => r.net > now - 3600_000);
-    if (!next) return null;
-    return card({
-      id: `launch-${next.id}`,
-      kind: 'launch',
-      family: 'Orbit',
-      title: next.name,
-      subtitle: `${next.provider || 'Launch'} · T−${relTime(next.net, now).replace('in ', '')}`,
-      place: next.location || next.pad,
-      lon: next.lon,
-      lat: next.lat,
-      radiusKm: 25,
-      camera: { height: 30_000, heading: 0, pitch: -40 },
-      layers: ['launches', 'iss'],
-      time: { start: next.net - 3600_000, end: next.net + 3600_000 },
-      metrics: [
-        { label: 'NET', value: new Date(next.net).toISOString(), unit: 'utc' },
-        ...(next.orbit
-          ? [{ label: 'Orbit', value: next.orbit, unit: '' }]
-          : []),
-        ...(next.status
-          ? [{ label: 'Status', value: next.status, unit: '' }]
-          : []),
-      ],
-      updatedAt: feeds.launches.updatedAt,
-      source: d.source,
-      severity: next.net - now < 2 * DAY ? 3 : 1,
-      live: d.upcomingOk,
+  /* ── Next launch ── */
+  add('launch', () => {
+    const next = launches?.records.find((r) => r.net > now - HOUR);
+    if (!next) throw new Error('launch feeds unavailable');
+    const tMinus = next.net - now;
+    const hh = Math.floor(Math.abs(tMinus) / HOUR);
+    const mm = Math.floor((Math.abs(tMinus) % HOUR) / 60_000);
+    const vehicle = next.name.split('|')[0].trim();
+    return card(
+      {
+        id: `launch-${next.id}`,
+        kind: 'launch',
+        family: 'Orbit',
+        band: 'orbit',
+        archetype: 'sensor',
+        telemetry: [
+          'ORBIT',
+          `T${tMinus >= 0 ? '−' : '+'}${String(hh).padStart(2, '0')}:${String(mm).padStart(2, '0')}`,
+          up(vehicle).slice(0, 18),
+          next.orbit ? up(next.orbit) : null,
+        ]
+          .filter(Boolean)
+          .join(' · '),
+        title: next.name,
+        subtitle: `${next.provider || 'Launch'} · ${tMinus >= 0 ? `T−${relTime(next.net, now).replace('in ', '')}` : `launched ${relTime(next.net, now)}`} · ${next.pad}`,
+        place: next.location || next.pad,
+        lon: next.lon,
+        lat: next.lat,
+        radiusKm: 120,
+        spanKm: 420,
+        camera: { height: 30_000, heading: 0, pitch: -40 },
+        layers: ['launches', 'iss'],
+        time: { start: next.net - HOUR, end: next.net + HOUR },
+        metrics: [
+          {
+            label: 'NET',
+            value: new Date(next.net).toISOString(),
+            unit: 'utc',
+          },
+          ...(next.orbit
+            ? [{ label: 'Orbit', value: next.orbit, unit: '' }]
+            : []),
+          ...(next.status
+            ? [{ label: 'Status', value: next.status, unit: '' }]
+            : []),
+        ],
+        updatedAt: feeds.launches.updatedAt,
+        source: `${launches.source} · ascent azimuth indicative`,
+        severity: tMinus < 2 * DAY ? 3 : 1,
+        live: launches.upcomingOk,
+      },
+      {
+        type: 'launch',
+        pad: { lon: next.lon, lat: next.lat },
+        orbit: next.orbit || '',
+      },
+    );
+  });
+
+  /* ── GNSS interference ── */
+  add('gnss', async () => {
+    const snaps = await Promise.allSettled(
+      GNSS_ANCHORS.map((a) =>
+        withBudget(gnssIntegrity.get(`${a.lat}:${a.lon}`, a), 12_000).then(
+          (s) => ({ a, s }),
+        ),
+      ),
+    );
+    const ok = snaps
+      .filter((r) => r.status === 'fulfilled')
+      .map((r) => r.value);
+    if (!ok.length)
+      throw new Error(
+        snaps[0]?.reason?.message || 'GNSS integrity unavailable',
+      );
+    let best = null;
+    for (const { a, s } of ok) {
+      if (s.rows.length < 8) continue;
+      const frac = s.degraded / s.rows.length;
+      const score = s.degraded * frac;
+      if (!best || score > best.score) best = { a, s, frac, score };
+    }
+    if (!best || best.s.degraded < 4 || best.frac < 0.15) return null;
+    const pct = Math.round(best.frac * 100);
+    const bad = best.s.cells.filter((c) => c.level !== 'low');
+    const hot = bad.length
+      ? bad.reduce((x, y) => (y.percent > x.percent ? y : x))
+      : null;
+    const c = hot || best.a;
+    return card(
+      {
+        id: `gnss-${best.a.id}`,
+        kind: 'gnss',
+        family: 'Infra',
+        band: 'sky',
+        archetype: 'number',
+        telemetry: `SKY · GNSS · ${pct}% DEGRADED · ${best.s.rows.length} AIRCRAFT · 250 NM`,
+        title: `GNSS interference · ${best.a.name}`,
+        subtitle: `${best.s.degraded} of ${best.s.rows.length} aircraft report degraded GPS integrity (low NIC/NACp)`,
+        place: best.a.name,
+        lon: c.lon,
+        lat: c.lat,
+        radiusKm: 350,
+        spanKm: 900,
+        camera: { height: 1_100_000, heading: 0, pitch: -80 },
+        layers: ['gnss', 'flights'],
+        metrics: [
+          { label: 'Degraded aircraft', value: best.s.degraded, unit: '' },
+          { label: 'Sampled aircraft', value: best.s.rows.length, unit: '' },
+          { label: 'Anomalous cells', value: bad.length, unit: '' },
+        ],
+        headline: {
+          value: pct,
+          unit: '%',
+          label: 'aircraft with degraded GNSS',
+        },
+        updatedAt: best.s.fetchedAt,
+        source:
+          'adsb.lol NIC/NACp · gpsjam.org bands (a proxy for jamming, not proof)',
+        severity: 2 + Math.min(3, pct / 15),
+      },
+      { type: 'gnss', rows: best.s.rows, cells: best.s.cells, anchor: best.a },
+    );
+  });
+
+  /* ── Transit at (or nearest to) rush hour ── */
+  add('transit', async () => {
+    if (!transitCatalog) throw new Error('transit catalog unavailable');
+    const TZ = {
+      mbta: 'America/New_York',
+      'capmetro-austin': 'America/Chicago',
+      'metrotransit-msp': 'America/Chicago',
+      'hsl-helsinki': 'Europe/Helsinki',
+      'ovapi-nl': 'Europe/Amsterdam',
+      'entur-norway': 'Europe/Oslo',
+      'translink-seq': 'Australia/Brisbane',
+      'ttc-toronto': 'America/Toronto',
+    };
+    const localHour = (tz) => {
+      const parts = new Intl.DateTimeFormat('en-GB', {
+        timeZone: tz,
+        hour: 'numeric',
+        minute: 'numeric',
+        hour12: false,
+      }).formatToParts(new Date(now));
+      const h = Number(parts.find((p) => p.type === 'hour')?.value);
+      const m = Number(parts.find((p) => p.type === 'minute')?.value);
+      return (h % 24) + m / 60;
+    };
+    const ranked = transitCatalog.feeds
+      .filter((f) => TZ[f.id])
+      .map((f) => {
+        const h = localHour(TZ[f.id]);
+        return { f, h, gap: Math.min(Math.abs(h - 8.25), Math.abs(h - 17.5)) };
+      })
+      .sort((a, b) => a.gap - b.gap);
+    for (const { f, h, gap } of ranked.slice(0, 3)) {
+      const snap = await withBudget(transitVehicles.get(f.id), 14_000).catch(
+        () => null,
+      );
+      if (!snap || snap.vehicles.length < 10) continue;
+      const moving = snap.vehicles.filter((v) => (v.speedMps ?? 0) > 1).length;
+      const rush = gap <= 1.25;
+      const clock = `${String(Math.floor(h)).padStart(2, '0')}:${String(Math.round((h % 1) * 60)).padStart(2, '0')}`;
+      const city = f.region.split(',')[0];
+      const center = densestCell(snap.vehicles, 0.15) || {
+        lat: f.center.lat,
+        lon: f.center.lon,
+      };
+      return card(
+        {
+          id: `transit-${f.id}`,
+          kind: 'transit',
+          family: 'Ground',
+          band: 'ground',
+          archetype: 'sensor',
+          telemetry: `GROUND · GTFS-RT · ${snap.vehicles.length} VEHICLES · ${clock} LOCAL`,
+          title: `${rush ? 'Rush hour' : 'Transit now'} · ${city}`,
+          subtitle: `${snap.vehicles.length} ${f.name} vehicles reporting · ${moving} moving · ${clock} local time`,
+          place: f.region,
+          lon: center.lon,
+          lat: center.lat,
+          radiusKm: 10,
+          spanKm: 24,
+          camera: { height: 18_000, heading: 0, pitch: -50 },
+          layers: ['transit'],
+          metrics: [
+            { label: 'Vehicles', value: snap.vehicles.length, unit: '' },
+            { label: 'Moving', value: moving, unit: '' },
+          ],
+          headline: {
+            value: snap.vehicles.length,
+            unit: '',
+            label: 'vehicles live',
+          },
+          updatedAt: snap.fetchedAt,
+          source: `${f.name} GTFS-realtime · ${f.attribution}`,
+          severity: rush ? 1.6 : 0.8,
+        },
+        { type: 'transit', vehicles: snap.vehicles },
+      );
+    }
+    return null;
+  });
+
+  /* ── Eyes: live public cameras at famous busy places ── */
+  add('eyes', async () => {
+    if (!cctv?.records.length) throw new Error('camera catalog unavailable');
+    const found = [];
+    for (const wish of EYE_WISHLIST) {
+      const cam = cctv.records.find((c) => wish.re.test(c.name));
+      if (cam) found.push({ wish, cam });
+    }
+    found.sort(
+      (a, b) =>
+        (sunElevation(b.cam.lat, b.cam.lon, now) > -6) -
+        (sunElevation(a.cam.lat, a.cam.lon, now) > -6),
+    );
+    const checked = await Promise.allSettled(
+      found.slice(0, 11).map(({ wish, cam }) =>
+        withBudget(verifyFrame(cam), 12_000).then((url) => ({
+          wish,
+          cam,
+          url,
+        })),
+      ),
+    );
+    const live = checked
+      .filter((r) => r.status === 'fulfilled')
+      .map((r) => r.value)
+      .slice(0, 9);
+    return live.map(({ wish, cam, url }, i) => {
+      const daylight = sunElevation(cam.lat, cam.lon, now) > -6;
+      return card(
+        {
+          id: `eye-${cam.id}`,
+          kind: 'camera',
+          family: 'Eyes',
+          band: 'ground',
+          archetype: 'eye',
+          telemetry: `GROUND · CAM ${camCode(cam.id)} · ${up(wish.title).slice(0, 22)} · ${hhmmss(EYE_FRAMES.get(cam.id)?.at || now)}`,
+          title: wish.title,
+          subtitle: `${wish.place} · ${cam.provider}${daylight ? '' : ' · night'} · looking ${compass(cam.heading)}`,
+          place: wish.place,
+          lon: cam.lon,
+          lat: cam.lat,
+          radiusKm: 1,
+          spanKm: 1.5,
+          camera: { height: 600, heading: cam.heading, pitch: -25 },
+          layers: ['cctv'],
+          media: {
+            kind: 'image',
+            url,
+            refreshMs: 30_000,
+            cameraId: cam.id,
+            headingDeg: cam.heading,
+            provider: cam.provider,
+            city: cam.city,
+          },
+          metrics: [
+            { label: 'Looking', value: compass(cam.heading), unit: '' },
+          ],
+          updatedAt: EYE_FRAMES.get(cam.id)?.at || now,
+          source: `${cam.provider} public camera`,
+          severity: 1.4 - i * 0.05 + (daylight ? 0.3 : 0),
+        },
+        { type: 'eye', cameraId: cam.id },
+      );
     });
   });
 
-  // Bundled reconstruction: always present.
-  tryAdd(() => {
-    const ev = ok(flood)?.event;
+  /* ── Worst air quality (modelled) ── */
+  add('air-quality', () => {
+    if (!airQuality?.records.length)
+      throw new Error('air-quality feed unavailable');
+    const worst = airQuality.records.reduce((a, b) => (b.aqi > a.aqi ? b : a));
+    if (worst.aqi < 80) return null;
+    const label =
+      worst.aqi > 200
+        ? 'Very unhealthy air'
+        : worst.aqi > 150
+          ? 'Unhealthy air'
+          : 'Unhealthy air for sensitive groups';
+    return card(
+      {
+        id: `aq-${worst.name.toLowerCase().replace(/\W+/g, '-')}`,
+        kind: 'air-quality',
+        family: 'Hazards',
+        band: 'ground',
+        archetype: 'number',
+        telemetry: `GROUND · PM2.5 ${Math.round(worst.pm25)} µG/M³ · AQI ${Math.round(worst.aqi)} · CAMS`,
+        title: `${label} · ${worst.name}`,
+        subtitle: `PM2.5 AQI ${Math.round(worst.aqi)} · worst of ${airQuality.records.length} major cities (model, not a monitor)`,
+        place: worst.name,
+        lon: worst.lon,
+        lat: worst.lat,
+        radiusKm: 30,
+        spanKm: 700,
+        camera: { height: 60_000, heading: 0, pitch: -45 },
+        layers: ['air-quality', 'fires', 'wind'],
+        metrics: [
+          { label: 'PM2.5 AQI', value: Math.round(worst.aqi), unit: '' },
+          { label: 'PM2.5', value: Math.round(worst.pm25), unit: 'µg/m³' },
+        ],
+        headline: {
+          value: Math.round(worst.aqi),
+          unit: 'AQI',
+          label: 'US air quality index',
+        },
+        series: worst.series,
+        seriesLabel: 'PM2.5 (µg/m³), last 24 h',
+        updatedAt: worst.t,
+        source: airQuality.source,
+        severity: 1.5 + (worst.aqi - 100) / 60,
+      },
+      { type: 'aq', aqi: worst.aqi },
+    );
+  });
+
+  /* ── Volcano (most recently updated open EONET event) ── */
+  add('volcano', () => {
+    const v = eonet?.volcanoes?.slice().sort((a, b) => b.t - a.t)[0];
+    if (!v) return null;
+    return card(
+      {
+        id: `volcano-${v.id}`,
+        kind: 'volcano',
+        family: 'Hazards',
+        band: 'ground',
+        archetype: 'sensor',
+        telemetry: `GROUND · VOLCANO · ${fmtLatLon(v.lat, v.lon).replace(/°/g, '')} · EONET`,
+        title: v.title.replace(/,.*$/, ''),
+        subtitle: `Open eruption event since ${new Date(v.firstT).toISOString().slice(0, 10)} · ${describePlace(v.lat, v.lon)}`,
+        place:
+          v.title.split(',').slice(1).join(',').trim() ||
+          regionOf(v.lat, v.lon),
+        lon: v.lon,
+        lat: v.lat,
+        radiusKm: 12,
+        spanKm: 26,
+        camera: { height: 25_000, heading: 0, pitch: -40 },
+        layers: ['volcanoes'],
+        updatedAt: v.t,
+        source: 'NASA EONET',
+        live: false,
+        severity: 1.3,
+      },
+      { type: 'volcano' },
+    );
+  });
+
+  /* ── Ships at chokepoints (only when AIS is configured) ── */
+  add('chokepoint', async () => {
+    let vessels;
+    try {
+      vessels = await withBudget(feeds.vessels.get(), 6000);
+    } catch (error) {
+      throw new Error(
+        error?.keyRequired
+          ? 'AIS not configured on this server (AISSTREAM_API_KEY)'
+          : 'AIS unavailable',
+      );
+    }
+    const POINTS = [
+      ['Strait of Hormuz', 56.45, 26.55],
+      ['Singapore Strait', 103.85, 1.22],
+      ['Suez Canal', 32.35, 30.6],
+      ['Panama Canal', -79.82, 9.2],
+      ['Strait of Gibraltar', -5.6, 35.95],
+      ['Bab-el-Mandeb', 43.4, 12.6],
+    ];
+    let best = null;
+    for (const [name, lon, lat] of POINTS) {
+      const near = vessels.records.filter(
+        (v) => haversineKm(lat, lon, v.lat, v.lon) < 60,
+      );
+      if (!best || near.length > best.near.length)
+        best = { name, lon, lat, near };
+    }
+    if (!best?.near.length) return null;
+    const slow = best.near.filter((v) => (v.speed ?? 0) < 0.5).length;
+    return card(
+      {
+        id: `choke-${best.name.toLowerCase().replace(/\W+/g, '-')}`,
+        kind: 'vessels',
+        family: 'Sea',
+        band: 'ground',
+        archetype: 'sensor',
+        telemetry: `GROUND · AIS · ${best.near.length} VESSELS · ${slow} AT ANCHOR`,
+        title: best.name,
+        subtitle: `${best.near.length} vessels within 60 km · ${slow} stopped or at anchor`,
+        place: best.name,
+        lon: best.lon,
+        lat: best.lat,
+        radiusKm: 40,
+        spanKm: 120,
+        camera: { height: 120_000, heading: 0, pitch: -55 },
+        layers: ['vessels', 'tankers'],
+        metrics: [
+          { label: 'Vessels', value: best.near.length, unit: '' },
+          { label: 'Stopped', value: slow, unit: '' },
+        ],
+        updatedAt: feeds.vessels.updatedAt,
+        source: vessels.source,
+        severity: 1.5,
+      },
+      {
+        type: 'vessels',
+        vessels: best.near.map((v) => ({
+          lon: v.lon,
+          lat: v.lat,
+          heading: v.heading,
+          speed: v.speed,
+        })),
+      },
+    );
+  });
+
+  /* ── Bundled reconstruction: always present ── */
+  add('bhote-koshi', () => {
+    const ev = flood?.event;
     const vp = ev?.viewpoints?.corridor;
     const lon = vp?.lon ?? 85.3548;
     const lat = vp?.lat ?? 28.207;
     const observed = ev?.observedDate || '2026-08-26';
-    return card({
-      id: 'bhote-koshi-2026',
-      kind: 'reconstruction',
-      family: 'Hazards',
-      section: 'reconstruction',
-      title: ev?.title || 'Bhote Koshi Outburst Flood',
-      subtitle: `Reconstruction · ${ev?.evidenceSpine?.length ?? 0} evidence beats · 2021 vs 2026 imagery`,
-      place: 'Rasuwa, Nepal',
-      lon,
-      lat,
-      radiusKm: 9,
-      camera: {
-        height: vp
-          ? Math.round(
-              (vp.rangeM || 8600) *
-                Math.sin(Math.abs(vp.pitchDeg || 39) * (Math.PI / 180)),
-            )
-          : 5400,
-        heading: vp?.headingDeg ?? 344,
-        pitch: vp?.pitchDeg ?? -39,
-        targetHeight: vp?.targetElevationM ?? 1536,
-      },
-      layers: ['floods'],
-      time: {
-        start: Date.parse(`${observed}T00:00:00Z`),
-        end: Date.parse(`${observed}T12:00:00Z`),
-        at: Date.parse(`${observed}T05:30:00Z`),
-      },
-      metrics: [
-        { label: 'Corridor', value: corridorKm(ev), unit: 'km' },
-        {
-          label: 'Witness anchors',
-          value: ev?.witnessAnchors?.length ?? 0,
-          unit: '',
+    return card(
+      {
+        id: 'bhote-koshi-2026',
+        kind: 'reconstruction',
+        family: 'Hazards',
+        section: 'reconstruction',
+        band: 'ground',
+        archetype: 'sensor',
+        telemetry: `GROUND · RECON · ${corridorKm(ev)} KM CORRIDOR · ${observed.replace(/-/g, '')}`,
+        title: ev?.title || 'Bhote Koshi Outburst Flood',
+        subtitle: `Reconstruction · ${ev?.evidenceSpine?.length ?? 0} evidence beats · 2021 vs 2026 imagery`,
+        place: 'Rasuwa, Nepal',
+        lon,
+        lat,
+        radiusKm: 9,
+        spanKm: 16,
+        camera: {
+          height: vp
+            ? Math.round(
+                (vp.rangeM || 8600) *
+                  Math.sin(Math.abs(vp.pitchDeg || 39) * (Math.PI / 180)),
+              )
+            : 5400,
+          heading: vp?.headingDeg ?? 344,
+          pitch: vp?.pitchDeg ?? -39,
+          targetHeight: vp?.targetElevationM ?? 1536,
         },
-        {
-          label: 'Field reports',
-          value: ev?.fieldReports?.length ?? 0,
-          unit: '',
+        layers: ['floods'],
+        time: {
+          start: Date.parse(`${observed}T00:00:00Z`),
+          end: Date.parse(`${observed}T12:00:00Z`),
+          at: Date.parse(`${observed}T05:30:00Z`),
         },
-      ],
-      updatedAt: Date.parse(observed),
-      live: false,
-      source: 'GeoPera · Vantor Open Data · bundled event pack',
-      severity: 4,
-    });
+        metrics: [
+          { label: 'Corridor', value: corridorKm(ev), unit: 'km' },
+          {
+            label: 'Witness anchors',
+            value: ev?.witnessAnchors?.length ?? 0,
+            unit: '',
+          },
+          {
+            label: 'Field reports',
+            value: ev?.fieldReports?.length ?? 0,
+            unit: '',
+          },
+        ],
+        updatedAt: Date.parse(observed),
+        live: false,
+        source: 'GeoPera · Vantor Open Data · bundled event pack',
+        severity: 4,
+      },
+      {
+        type: 'flood',
+        path: flood?.path || [],
+        corridor: flood?.corridor || null,
+        anchors: (ev?.witnessAnchors || []).map((a) => ({
+          lon: a.lon,
+          lat: a.lat,
+        })),
+      },
+    );
   });
 
-  // Evergreen places.
-  for (const e of EVERGREEN) {
-    tryAdd(() =>
-      card({
-        ...e,
-        id: `always-${e.id}`,
-        kind: 'place',
-        section: 'always',
-        live: false,
-        updatedAt: now,
-        source: 'Bundled place',
-        severity: 0,
-      }),
-    );
+  await Promise.allSettled(tasks);
+  buildSituations.lastOmitted = omitted;
+  buildSituations.lastTimings = timings;
+  return interleave(out);
+}
+
+/**
+ * Severity first, then avoid putting two cards of the same band or archetype
+ * side by side when another card is close behind (DESIGN.md §11.2).
+ */
+function interleave(cards) {
+  const rest = cards.slice().sort((a, b) => b.severity - a.severity);
+  const out = [];
+  while (rest.length) {
+    const prev = out.at(-1);
+    let k = 0;
+    if (prev) {
+      const look = Math.min(rest.length, 6);
+      const differs = (c) =>
+        c.band !== prev.band && c.archetype !== prev.archetype;
+      const half = (c) =>
+        c.band !== prev.band || c.archetype !== prev.archetype;
+      k = rest.slice(0, look).findIndex(differs);
+      if (k < 0) k = rest.slice(0, look).findIndex(half);
+      if (k < 0) k = 0;
+    }
+    out.push(rest.splice(k, 1)[0]);
   }
-
-  const live = out
-    .filter((c) => c.section === 'now')
-    .sort((a, b) => b.severity - a.severity);
-  const rest = out.filter((c) => c.section !== 'now');
-  return [...live, ...rest];
+  return out;
 }
diff --git a/mobile/vision/index.html b/mobile/vision/index.html
index f80ac0f64..02c3534f0 100644
--- a/mobile/vision/index.html
+++ b/mobile/vision/index.html
@@ -578,6 +578,369 @@ input, textarea { font: inherit; color: inherit; }
   *, *::before, *::after { animation-duration: .01ms !important; animation-iteration-count: 1 !important; transition-duration: .12s !important; }
 }
 
+/* =====================================================================================
+   ROUND TWO — God's Eye identity: altitude bands, sensor framing, telemetry voice
+   ===================================================================================== */
+:root {
+  --b-orbit: #B79CFF; --b-sky: #8CD4FF; --b-ground: #FFA53D; --b-inside: #F2CF7A; --harm: #FF3B30;
+  --mono: "JetBrains Mono", ui-monospace, "SF Mono", Menlo, Consolas, "DejaVu Sans Mono", monospace;
+  --bg: #050608; --card: #0B0D11; --card2: #10131a;
+}
+.mono { font-family: var(--mono); letter-spacing: .02em; }
+.tab.on { color: #fff; }
+.tablens { background: rgba(255,255,255,.14); }
+.dot { background: var(--harm); }
+
+/* ---------- hero: the orbit view with a reticle and burned-in telemetry ---------- */
+.now-hero { height: calc(var(--sat) + clamp(330px, 46vh, 440px)); }
+.now-hero .hud { position: absolute; inset: calc(var(--sat) + 8px) 12px auto 12px; height: calc(100% - 150px - var(--sat)); pointer-events: none; }
+.now-hero .hud .wm { position: absolute; left: 6px; top: 4px; font: 800 13px/1 var(--display); letter-spacing: .34em; color: #fff; text-shadow: 0 0 18px rgba(0,0,0,.8); }
+.hb { position: absolute; width: 22px; height: 22px; border: 0 solid rgba(255,255,255,.55); }
+.hb.a { left: 0; top: 26px; border-width: 1.5px 0 0 1.5px; } .hb.b { right: 0; top: 26px; border-width: 1.5px 1.5px 0 0; }
+.hb.c { left: 0; bottom: 0; border-width: 0 0 1.5px 1.5px; } .hb.d { right: 0; bottom: 0; border-width: 0 1.5px 1.5px 0; }
+.xh { position: absolute; left: 50%; top: 52%; width: 46px; height: 46px; margin: -23px; border-radius: 50%; box-shadow: inset 0 0 0 1px rgba(255,255,255,.35); }
+.xh::before, .xh::after { content: ""; position: absolute; background: rgba(255,255,255,.45); }
+.xh::before { left: -14px; right: -14px; top: 50%; height: 1px; } .xh::after { top: -14px; bottom: -14px; left: 50%; width: 1px; }
+.hud-t { position: absolute; left: 30px; right: 30px; bottom: 6px; font-size: 9.5px; color: rgba(220,210,255,.82); letter-spacing: .08em; text-align: center; text-shadow: 0 1px 6px #000; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.now-hero .lt .kicker { font-size: 10.5px; letter-spacing: .12em; color: rgba(255,255,255,.7); }
+.now-hero .lt h1 { font: 800 30px/1.08 var(--display); letter-spacing: -.02em; margin-top: 6px; max-width: 13ch; }
+.counts { display: flex; flex-wrap: wrap; gap: 4px 12px; margin-top: 10px; font-size: 10.5px; letter-spacing: .06em; text-transform: uppercase; color: var(--text3); }
+.counts b { color: var(--text); font-weight: 600; } .counts .w b { color: var(--b-inside); }
+.navbar .wm { font: 800 13px/1 var(--display); letter-spacing: .34em; }
+
+/* ---------- altitude rail (band filter) ---------- */
+.bandrail { position: sticky; top: 0; z-index: 6; display: flex; align-items: stretch; gap: 0; padding: calc(var(--sat) + 8px) 10px 10px; margin-top: -2px; background: linear-gradient(180deg, rgba(5,6,8,.96) 70%, rgba(5,6,8,0)); }
+.bcell { flex: 1; min-width: 0; display: flex; flex-direction: column; align-items: flex-start; gap: 1px; padding: 8px 7px 7px; border-radius: 12px; position: relative; color: var(--text2); transition: background .2s, color .2s; }
+.bcell i { width: 100%; height: 2.5px; border-radius: 2px; background: var(--c); opacity: .45; margin-bottom: 5px; }
+.bcell b { font: 700 10.5px/1.1 var(--mono); letter-spacing: .1em; color: var(--text); }
+.bcell span { font: 600 15px/1.1 var(--display); color: var(--text); }
+.bcell em { font: 500 8.5px/1.2 var(--mono); font-style: normal; letter-spacing: .04em; color: var(--text3); text-transform: uppercase; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; max-width: 100%; }
+.bcell.on { background: color-mix(in oklab, var(--c) 14%, rgba(255,255,255,.04)); box-shadow: inset 0 0 0 1px color-mix(in oklab, var(--c) 55%, transparent); }
+.bcell.on i { opacity: 1; box-shadow: 0 0 10px var(--c); } .bcell.on b { color: var(--c); }
+.rarr { flex: none; width: 6px; align-self: center; height: 1px; background: rgba(255,255,255,.18); }
+.band-h { margin: 2px 16px 10px; padding: 10px 12px; border-radius: 12px; background: color-mix(in oklab, var(--c) 9%, transparent); box-shadow: inset 2px 0 0 var(--c); font-size: 12.5px; color: var(--text2); display: flex; gap: 10px; align-items: baseline; }
+.band-h b { color: var(--c); font: 700 12px var(--mono); letter-spacing: .12em; text-transform: uppercase; }
+.feed-end { text-align: center; font-size: 9.5px; letter-spacing: .1em; color: rgba(246,223,160,.55); padding: 26px 20px 10px; display: flex; gap: 6px; justify-content: center; align-items: center; }
+#feed { display: flex; flex-direction: column; gap: 10px; padding-bottom: 6px; }
+#feed > .fc.wide { margin: 0 12px; }
+
+/* ---------- feed cards: sensor frames ---------- */
+.fc { border-radius: 14px; background: var(--card); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.08); }
+.fc .fr { position: relative; width: 100%; overflow: hidden; background: #06080c; border-radius: 14px 14px 0 0; }
+.fc .fr canvas { position: absolute; inset: 0; width: 100%; height: 100%; display: block; }
+.fc .fr::after { content: ""; position: absolute; inset: 0; pointer-events: none; background: linear-gradient(180deg, rgba(0,0,0,.42), transparent 22%, transparent 74%, rgba(0,0,0,.7)); }
+.bk { position: absolute; z-index: 2; width: 14px; height: 14px; border: 0 solid color-mix(in oklab, var(--c) 85%, white); opacity: .9; pointer-events: none; }
+.bk.a { left: 7px; top: 7px; border-width: 1.5px 0 0 1.5px; } .bk.b { right: 7px; top: 7px; border-width: 1.5px 1.5px 0 0; }
+.bk.c { left: 7px; bottom: 7px; border-width: 0 0 1.5px 1.5px; } .bk.d { right: 7px; bottom: 7px; border-width: 0 1.5px 1.5px 0; }
+.ftop { position: absolute; z-index: 3; left: 14px; right: 14px; top: 11px; display: flex; gap: 6px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .12em; pointer-events: none; }
+.ftop .bt, .tags .bt, .rhead .bt { color: var(--c); padding: 3px 5px 2px; border-radius: 4px; background: rgba(0,0,0,.55); box-shadow: inset 0 0 0 .5px color-mix(in oklab, var(--c) 60%, transparent); font: 700 9px/1 var(--mono); letter-spacing: .12em; }
+.ftop .at { color: rgba(255,255,255,.75); }
+.ftop .lv, .ftop .mine { margin-left: auto; display: inline-flex; gap: 4px; align-items: center; color: #fff; background: rgba(255,59,48,.9); padding: 3px 5px 2px; border-radius: 4px; }
+.ftop .mine { background: var(--b-inside); color: #1b1408; }
+.ftop .lv i { width: 5px; height: 5px; border-radius: 50%; background: #fff; animation: blink 1.2s steps(2) infinite; }
+@keyframes blink { 50% { opacity: 0; } }
+.tele { position: absolute; z-index: 3; left: 14px; right: 14px; bottom: 11px; font: 600 8.5px/1.25 var(--mono); letter-spacing: .07em; color: rgba(255,255,255,.88); text-shadow: 0 1px 3px #000, 0 0 6px #000; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; pointer-events: none; }
+.fc.wide .tele { font-size: 10px; }
+.readout { position: absolute; z-index: 3; left: 14px; bottom: 26px; font: 700 16px/1 var(--mono); letter-spacing: .02em; color: #fff; text-shadow: 0 1px 10px rgba(0,0,0,.9); }
+.a-track.b-sky .readout { color: #fff; } .fc[data-fid="squawk"] .readout { color: #FF6B61; }
+.fseal { position: absolute; z-index: 3; right: 12px; top: 30px; width: 24px; height: 24px; filter: drop-shadow(0 0 8px rgba(233,196,106,.7)); }
+.numov { position: absolute; z-index: 3; inset: auto 14px 26px 14px; }
+.a-number .fr canvas { filter: brightness(.62) saturate(1.1); }
+.numov .big { font: 800 40px/1 var(--display); letter-spacing: -.03em; color: #fff; text-shadow: 0 2px 20px rgba(0,0,0,.8); }
+.numov .big small { font: 600 12px var(--mono); letter-spacing: .06em; color: var(--c); margin-left: 5px; text-transform: uppercase; }
+.numov .nl { font-size: 12px; color: rgba(255,255,255,.82); margin-top: 3px; line-height: 1.25; }
+.numov .nsp { width: 100%; height: 30px; margin-top: 6px; overflow: visible; }
+.r4d { position: absolute; z-index: 3; left: 14px; top: 30px; display: flex; gap: 6px; }
+.fm { padding: 9px 11px 11px; }
+.fm .ttl { font-size: 14.5px; font-weight: 650; line-height: 1.26; letter-spacing: -.01em; display: -webkit-box; -webkit-line-clamp: 3; -webkit-box-orient: vertical; overflow: hidden; }
+.fc.wide .fm .ttl { font-size: 17px; }
+.where { display: flex; flex-wrap: wrap; gap: 2px 8px; margin-top: 6px; font-size: 11.5px; color: var(--text3); }
+.where .d { color: var(--text2); font-weight: 600; font-family: var(--mono); font-size: 10.5px; letter-spacing: .02em; }
+.where span + span::before { content: "·"; margin-right: 8px; color: var(--text4); }
+.soc { display: flex; align-items: center; flex-wrap: wrap; gap: 4px 10px; margin-top: 8px; font-size: 11.5px; color: var(--text3); }
+.soc b { color: var(--text); font-weight: 600; }
+.soc .sl { display: inline-flex; align-items: center; gap: 4px; color: var(--b-inside); } .soc .sl b { color: var(--b-inside); }
+.soc .sl .ic { width: 13px; height: 13px; }
+.who { display: flex; align-items: center; gap: 6px; flex-wrap: wrap; margin-bottom: 6px; font-size: 12px; }
+.who b { font-weight: 650; }
+.bdg { display: inline-flex; align-items: center; gap: 3px; height: 18px; padding: 0 6px; border-radius: 5px; font: 650 9.5px/1 var(--font); letter-spacing: .02em; white-space: nowrap; }
+.bdg .ic { width: 11px; height: 11px; }
+.bdg.there { background: rgba(242,207,122,.16); color: var(--b-inside); box-shadow: inset 0 0 0 .5px rgba(242,207,122,.5); }
+.bdg.sealed { background: rgba(242,207,122,.08); color: var(--gold2); }
+.bdg.local { background: rgba(255,165,61,.12); color: var(--b-ground); }
+.bdg.domain { background: rgba(140,212,255,.12); color: var(--b-sky); }
+.bdg.unv { background: repeating-linear-gradient(135deg, rgba(255,255,255,.06) 0 4px, transparent 4px 8px); color: var(--text3); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.2); }
+.fc .cta { margin-top: 9px; display: inline-flex; align-items: center; gap: 6px; height: 30px; padding: 0 12px; border-radius: 8px; background: color-mix(in oklab, var(--c) 16%, transparent); color: var(--c); font-size: 12.5px; font-weight: 700; box-shadow: inset 0 0 0 .5px color-mix(in oklab, var(--c) 50%, transparent); }
+.fc.mine { box-shadow: inset 0 0 0 1px rgba(242,207,122,.55), 0 0 30px rgba(242,207,122,.12); }
+.fc.flash { animation: flash 1.2s ease; }
+
+/* room card */
+.fc.room { padding: 12px 13px 12px; background: linear-gradient(180deg, rgba(242,207,122,.06), rgba(255,255,255,.015) 40%), var(--card); box-shadow: inset 0 0 0 .5px rgba(242,207,122,.22); }
+.rhead { display: flex; align-items: center; gap: 7px; font-size: 11.5px; color: var(--text2); --c: var(--b-inside); }
+.rtag { display: inline-flex; align-items: center; gap: 4px; font: 700 9px/1 var(--mono); letter-spacing: .12em; color: #1a1306; background: var(--b-inside); padding: 3px 5px 2px; border-radius: 4px; }
+.rtag .ic { width: 11px; height: 11px; stroke-width: 2.4; }
+.lvw { display: inline-flex; align-items: center; gap: 5px; margin-left: 2px; } .lvw b { color: var(--text); }
+.rhead .stack { margin-left: auto; }
+.fc.room h3 { margin: 9px 0 0; font: 750 19px/1.15 var(--display); letter-spacing: -.01em; }
+.claims { margin-top: 10px; display: flex; flex-direction: column; gap: 6px; }
+.cl { display: grid; grid-template-columns: 74px 1fr; gap: 2px 8px; font-size: 13px; line-height: 1.35; color: rgba(240,244,250,.9); }
+.cl b { font: 700 9px/1.9 var(--mono); letter-spacing: .12em; color: var(--text3); }
+.cl.known b { color: var(--b-inside); } .cl.disputed b { color: #FFB25C; } .cl.open b { color: #fff; } .cl.unknown b { color: var(--text3); }
+.cl .cites { grid-column: 2; display: flex; gap: 4px; } .cl .cites i { font: 600 9px/1 var(--mono); font-style: normal; padding: 3px 4px; border-radius: 4px; background: rgba(255,255,255,.07); color: var(--text2); }
+.evs { display: grid; grid-template-columns: repeat(4, 1fr); gap: 6px; margin-top: 12px; }
+.evs .evc { width: 100%; aspect-ratio: 4/3; border-radius: 8px; display: block; background: #06080c; }
+.rfoot { display: flex; justify-content: space-between; align-items: center; margin-top: 11px; font-size: 11.5px; color: var(--text3); }
+.rfoot b { color: var(--text); font-weight: 600; } .rfoot .join { color: var(--b-inside); font-weight: 700; display: inline-flex; gap: 2px; align-items: center; }
+
+/* ---------- sheet: room ---------- */
+.sh-hd .tags { display: flex; gap: 6px; align-items: center; } .sh-hd .tags .age { font-size: 12px; color: var(--text3); }
+.sh-hd .pl b { color: var(--text); font-weight: 600; }
+.presence-row { display: flex; align-items: center; gap: 10px; margin-top: 10px; font-size: 12.5px; color: var(--text2); }
+.presence-row b { color: var(--text); } .presence-row .rate { color: var(--text3); font-family: var(--mono); font-size: 10.5px; }
+.seg2 { display: grid; grid-template-columns: 1fr 1fr; gap: 4px; margin: 12px 0 10px; padding: 3px; border-radius: 12px; background: rgba(255,255,255,.06); }
+.seg2 button { height: 34px; border-radius: 9px; display: flex; align-items: center; justify-content: center; gap: 6px; font-size: 13px; font-weight: 650; color: var(--text2); }
+.seg2 button.on { background: rgba(255,255,255,.14); color: #fff; box-shadow: inset 0 .5px 0 rgba(255,255,255,.3); }
+.seg2 button span { font-size: 11px; color: var(--text3); }
+.synth { border-radius: 14px; padding: 11px 12px 9px; background: linear-gradient(180deg, rgba(183,156,255,.09), rgba(183,156,255,.02)); box-shadow: inset 0 0 0 .5px rgba(183,156,255,.3); }
+.syh { display: flex; align-items: center; gap: 6px; font-size: 11px; color: #CDBBFF; font-weight: 600; }
+.syh span { flex: 1; min-width: 0; }
+.regen { display: inline-flex; gap: 4px; align-items: center; height: 26px; padding: 0 9px; border-radius: 8px; font-size: 11.5px; font-weight: 700; background: rgba(183,156,255,.16); color: #E2D6FF; flex: none; }
+.regen.busy { opacity: .5; }
+.sy { display: grid; grid-template-columns: 74px 1fr; gap: 0 8px; margin-top: 8px; }
+.sy b { font: 700 9px/2.1 var(--mono); letter-spacing: .12em; grid-row: span 9; }
+.sy.kn b { color: var(--b-inside); } .sy.di b { color: #FFB25C; } .sy.un b { color: var(--text3); }
+.sy p { margin: 0 0 4px; font-size: 13px; line-height: 1.38; color: rgba(240,244,250,.9); grid-column: 2; }
+.sy p.none { color: var(--text3); } .sy p.stream { white-space: pre-wrap; font-family: var(--mono); font-size: 11.5px; }
+.syf { margin-top: 6px; font-size: 9.5px; color: var(--text3); letter-spacing: .03em; }
+.cite { display: inline-block; font: 650 9.5px/1 var(--mono); padding: 3px 4px 2px; border-radius: 4px; background: rgba(255,255,255,.08); color: var(--text2); vertical-align: 1px; margin-right: 2px; }
+.cite:active { background: rgba(255,255,255,.2); }
+.sortrow { display: flex; gap: 6px; align-items: center; margin: 14px 0 8px; } .sortrow .sl { font-size: 9.5px; letter-spacing: .12em; color: var(--text3); margin-right: 2px; }
+.chip.sm { height: 28px; padding: 0 11px; font-size: 12.5px; }
+.posts { display: flex; flex-direction: column; gap: 8px; }
+.post { border-radius: 14px; padding: 10px 11px 9px; background: rgba(255,255,255,.035); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.07); transition: box-shadow .4s, background .4s; cursor: pointer; }
+.post.hl { background: rgba(242,207,122,.08); box-shadow: inset 0 0 0 1px rgba(242,207,122,.6); }
+.post.k-question { box-shadow: inset 2px 0 0 #fff, inset 0 0 0 .5px rgba(255,255,255,.07); }
+.post.noted { background: rgba(255,255,255,.02); }
+.post.noted .pt { color: var(--text3); text-decoration: line-through; text-decoration-color: rgba(255,255,255,.25); }
+.post.mine { box-shadow: inset 0 0 0 1px rgba(242,207,122,.45); }
+.ph { display: flex; align-items: flex-start; gap: 8px; }
+.ph .avatar { margin-top: 1px; }
+.pw { flex: 1; min-width: 0; font-size: 12.5px; } .pw b { font-weight: 650; } .pw .pid { font: 600 9.5px var(--mono); color: var(--text3); margin-left: 6px; } .pw .tm { color: var(--text3); margin-left: 6px; font-size: 11.5px; }
+.bds { display: flex; flex-wrap: wrap; gap: 4px; margin-top: 3px; }
+.kind { flex: none; display: inline-flex; align-items: center; gap: 4px; font: 700 9px/1 var(--mono); letter-spacing: .1em; padding: 4px 6px 3px; border-radius: 5px; background: rgba(255,255,255,.07); color: var(--text2); }
+.kind .ic { width: 11px; height: 11px; }
+.kind.k-witness { color: var(--b-inside); background: rgba(242,207,122,.12); } .kind.k-question { color: #fff; background: rgba(255,255,255,.14); }
+.kind.k-correction { color: #FFB25C; background: rgba(255,178,92,.12); } .kind.k-context { color: var(--b-sky); background: rgba(140,212,255,.1); } .kind.k-prediction { color: var(--b-orbit); background: rgba(183,156,255,.12); }
+.pt { margin: 7px 0 0; font-size: 14px; line-height: 1.42; color: rgba(242,245,250,.92); }
+.resolves { display: inline-block; margin-left: 6px; font: 600 9.5px var(--mono); color: var(--b-orbit); letter-spacing: .04em; text-transform: uppercase; }
+.patt { position: relative; margin-top: 8px; border-radius: 10px; overflow: hidden; background: #06080c; aspect-ratio: 16/10; }
+.patt canvas { width: 100%; height: 100%; display: block; }
+.patt .tier { position: absolute; left: 8px; bottom: 8px; display: inline-flex; gap: 4px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .1em; padding: 4px 6px 3px; border-radius: 4px; background: rgba(0,0,0,.6); color: var(--b-inside); }
+.patt .tier .ic { width: 12px; height: 12px; }
+.patt.unverified .tier { color: var(--text2); } .patt.eye .tier { color: var(--b-ground); }
+.patt .plive { position: absolute; right: 8px; top: 8px; display: inline-flex; gap: 5px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .1em; background: rgba(255,59,48,.9); padding: 4px 6px 3px; border-radius: 4px; }
+.patt .plive .dot { background: #fff; width: 5px; height: 5px; }
+.ancs { display: flex; flex-wrap: wrap; gap: 5px; margin-top: 8px; align-items: center; }
+.anc { display: inline-flex; align-items: center; gap: 4px; height: 24px; padding: 0 8px; border-radius: 7px; font-size: 11.5px; font-weight: 600; color: var(--text2); background: rgba(255,255,255,.06); }
+.anc .ic { width: 12px; height: 12px; color: var(--b-ground); }
+.note { margin-top: 9px; border-radius: 10px; padding: 9px 10px; background: rgba(140,212,255,.07); box-shadow: inset 0 0 0 .5px rgba(140,212,255,.3); }
+.note .nh { display: flex; gap: 5px; align-items: center; font-size: 11.5px; font-weight: 700; color: var(--b-sky); }
+.note p { margin: 5px 0 0; font-size: 13px; line-height: 1.4; color: rgba(240,244,250,.92); text-decoration: none; }
+.bridge { margin-top: 8px; display: flex; flex-direction: column; gap: 4px; }
+.br { display: grid; grid-template-columns: 1fr 90px 34px; gap: 8px; align-items: center; font-size: 11px; color: var(--text3); }
+.br b { color: var(--text); font-weight: 600; text-align: right; }
+.br i { height: 5px; border-radius: 3px; background: linear-gradient(90deg, var(--b-sky) calc(var(--v) * 100%), rgba(255,255,255,.1) 0); }
+.note details { margin-top: 6px; font-size: 11.5px; color: var(--text2); } .note summary { cursor: pointer; color: var(--b-sky); font-weight: 600; }
+.note details p { font-size: 12px; color: var(--text2); }
+.answered { margin-top: 8px; display: flex; gap: 5px; align-items: center; font-size: 11.5px; color: var(--b-inside); }
+.answered.open { color: var(--text2); } .answered b { font-weight: 650; }
+.pf { display: flex; align-items: center; gap: 6px; margin-top: 8px; }
+.rxb, .rep { display: inline-flex; align-items: center; gap: 4px; height: 24px; padding: 0 7px; border-radius: 7px; font-size: 11.5px; color: var(--text2); background: rgba(255,255,255,.05); }
+.rcap { margin-left: auto; display: inline-flex; align-items: center; gap: 5px; height: 26px; padding: 0 9px; border-radius: 8px; font-size: 11.5px; font-weight: 700; color: var(--b-inside); background: rgba(242,207,122,.12); }
+.room-srcs { margin-top: 18px; } .room-srcs .h3 { font-size: 11px; font-weight: 700; letter-spacing: .1em; text-transform: uppercase; color: var(--text3); margin-bottom: 4px; }
+.room-srcs .r { grid-template-columns: 30px 1fr; }
+.fine { font-size: 11px; color: var(--text3); margin: 14px 0 90px; }
+/* composer & reactions */
+.roomcomp { position: absolute; z-index: 41; left: 10px; right: 10px; bottom: calc(var(--sab) + 10px); display: none; gap: 8px; align-items: flex-end; }
+.roomcomp.on { display: flex; animation: rise .4s var(--spring); }
+.capbtn { flex: none; width: 66px; height: 58px; border-radius: 18px; display: flex; flex-direction: column; align-items: center; justify-content: center; gap: 2px; background: var(--b-inside); color: #1b1408; font-size: 10.5px; font-weight: 800; box-shadow: 0 8px 30px rgba(242,207,122,.25); }
+.capbtn .ic { width: 22px; height: 22px; stroke-width: 2; }
+.rcin { flex: 1; min-width: 0; border-radius: 18px; padding: 6px; }
+.rcin .kinds { display: none; gap: 4px; overflow-x: auto; scrollbar-width: none; padding: 2px 2px 6px; }
+.roomcomp.typing .kinds { display: flex; }
+.rcin .kinds button { flex: none; display: inline-flex; gap: 4px; align-items: center; height: 26px; padding: 0 9px; border-radius: 8px; font-size: 11.5px; font-weight: 650; color: var(--text2); background: rgba(255,255,255,.06); }
+.rcin .kinds button.on { background: #fff; color: #05070B; }
+.rcrow { display: flex; gap: 6px; align-items: center; }
+.rcrow input { flex: 1; min-width: 0; height: 44px; border: 0; outline: 0; background: transparent; padding: 0 10px; font-size: 15px; }
+.rcrow .send { width: 38px; height: 38px; border-radius: 50%; display: grid; place-items: center; background: rgba(255,255,255,.14); }
+.app[data-mode="situation"] .sheet .sc { padding-bottom: 96px; }
+.rx { position: absolute; z-index: 40; right: 14px; bottom: calc(var(--sab) + 84px); width: 36px; height: 260px; pointer-events: none; display: none; }
+.app[data-mode="situation"] .rx { display: block; }
+.rx span { position: absolute; bottom: 0; left: 6px; animation: floatUp 2.6s ease-out forwards; color: var(--harm); filter: drop-shadow(0 2px 6px rgba(0,0,0,.6)); }
+.rx span:nth-child(3n) { color: var(--b-inside); } .rx span:nth-child(3n+1) { color: #fff; }
+.lbl.speech { padding: 4px 9px 4px 4px; font-size: 11.5px; border-radius: 12px 12px 12px 3px; }
+.lbl.speech .sg { width: 20px; height: 20px; border-radius: 50%; display: grid; place-items: center; background: rgba(255,255,255,.12); color: #fff; }
+.lbl.speech .sg.k-witness { background: var(--b-inside); color: #1b1408; } .lbl.speech .sg.k-question { background: #fff; color: #05070B; }
+.lbl.speech .sg .ic { width: 12px; height: 12px; stroke-width: 2.2; }
+.lbl.speech.hl { box-shadow: inset 0 0 0 1.5px var(--b-inside); }
+@media (min-width: 600px) {
+  .roomcomp { left: 10px; right: auto; width: calc(var(--paneW) - 20px); z-index: 36; }
+  .rx { left: calc(var(--paneW) - 50px); right: auto; z-index: 36; }
+  .bandrail { padding-top: 8px; }
+  .now-hero .hud { display: none; }
+  .now-hero .lt h1 { font-size: 26px; max-width: none; }
+}
+.where { display: block; margin-top: 6px; }
+.where .pl { font-size: 12px; color: var(--text2); white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.where .d { font-size: 9.5px; letter-spacing: .06em; color: var(--text3); margin-top: 2px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.where span + span::before { content: none; }
+.soc span { display: inline-flex; align-items: center; gap: 4px; } .soc .ic { width: 13px; height: 13px; }
+/* accessory: a person live, with a moving thumbnail */
+.accessory .accdot { width: 10px; display: grid; place-items: center; }
+.accessory .accv { width: 54px; height: 30px; border-radius: 6px; flex: none; background: #06080c; }
+/* concept tag sits above the sticky rail on Now */
+.app[data-tab="now"] .concept-tag { top: calc(var(--sat) + 8px); font-size: 8.5px; padding: 2px 6px; }
+.bandrail { padding-top: calc(var(--sat) + 28px); }
+.now-hero .hud { top: calc(var(--sat) + 30px); }
+.now-hero .hud .wm { top: -22px; }
+.hb.a, .hb.b { top: 0; }
+
+/* ---------- capture: dial of four, live, upload, attach ---------- */
+.status .alt { font-size: 10.5px; letter-spacing: .06em; margin-left: 4px; }
+.dial button { padding: 0 2px; }
+.dial { gap: 18px; }
+.livecv { position: absolute; inset: 0; width: 100%; height: 100%; display: none; background: #000; }
+.livecv.on { display: block; }
+.cap-ui.m-live .compass-tape, .cap-ui.m-live .callouts, .cap-ui.m-upload .callouts { display: none; }
+.cap-ui.m-upload::before { content: ""; position: absolute; inset: 0; background: rgba(3,4,7,.62); backdrop-filter: blur(16px); -webkit-backdrop-filter: blur(16px); pointer-events: none; }
+.replyto { position: absolute; top: calc(var(--sat) + 60px); left: 12px; right: 12px; height: 38px; border-radius: 12px; display: flex; align-items: center; gap: 8px; padding: 0 6px 0 12px; font-size: 13px; color: var(--b-inside); }
+.replyto span { flex: 1; } .replyto b { color: #fff; } .replyto button { width: 28px; height: 28px; border-radius: 50%; display: grid; place-items: center; background: rgba(255,255,255,.1); }
+.shutter.s-live i { background: #FF3B30; }
+.shutter.s-live.rec i { border-radius: 8px; transform: scale(.5); }
+.shutter.s-upload i { background: var(--b-inside); }
+#modeHost { position: absolute; inset: 0; pointer-events: none; }
+#modeHost > * { pointer-events: auto; }
+.lv-pre { position: absolute; left: 14px; right: 14px; bottom: calc(var(--sab) + 300px); border-radius: 18px; padding: 14px 15px; font-size: 13.5px; color: var(--text2); }
+.lv-pre b { color: #fff; font-size: 16px; } .lv-pre p { margin: 8px 0 10px; line-height: 1.45; }
+.lvph { display: flex; gap: 10px; align-items: center; }
+.lvnear { display: flex; flex-wrap: wrap; gap: 6px; } .lvnear span { display: inline-flex; gap: 5px; align-items: center; font-size: 12px; height: 26px; padding: 0 9px; border-radius: 8px; background: rgba(242,207,122,.12); color: var(--b-inside); }
+.lvfine { margin-top: 10px; font-size: 9px; letter-spacing: .1em; color: var(--text3); }
+.lv-top { position: absolute; top: calc(var(--sat) + 60px); left: 12px; right: 12px; display: flex; gap: 8px; align-items: center; }
+.lvpill { display: inline-flex; align-items: center; gap: 6px; height: 30px; padding: 0 10px; border-radius: 8px; background: #FF3B30; font: 800 12px/1 var(--mono); letter-spacing: .08em; color: #fff; }
+.lvpill i { width: 7px; height: 7px; border-radius: 50%; background: #fff; animation: blink 1.2s steps(2) infinite; }
+.lvpill.pre { background: rgba(255,255,255,.12); } .lvpill b { font-weight: 700; }
+.lvv { display: inline-flex; align-items: center; gap: 5px; height: 30px; padding: 0 10px; border-radius: 8px; font-size: 13px; }
+.lvseal { margin-left: auto; display: inline-flex; align-items: center; gap: 5px; height: 30px; padding: 0 9px; border-radius: 8px; background: rgba(0,0,0,.45); color: var(--b-inside); font: 700 10px/1 var(--mono); letter-spacing: .1em; }
+.lv-to { position: absolute; top: calc(var(--sat) + 100px); left: 12px; height: 30px; border-radius: 8px; display: inline-flex; align-items: center; gap: 6px; padding: 0 10px; font-size: 12px; color: var(--text2); } .lv-to b { color: var(--b-inside); }
+.lv-chat { position: absolute; left: 12px; right: 70px; bottom: calc(var(--sab) + 330px); display: flex; flex-direction: column; gap: 6px; justify-content: flex-end; mask-image: linear-gradient(to top, #000 70%, transparent); -webkit-mask-image: linear-gradient(to top, #000 70%, transparent); pointer-events: none !important; }
+.lv-chat .bub .bx { padding: 6px 10px; font-size: 12.5px; } .lv-chat .lj { display: flex; gap: 6px; align-items: center; font-size: 11.5px; color: rgba(255,255,255,.75); text-shadow: 0 1px 4px #000; }
+.lvrx { position: absolute; right: 14px; bottom: calc(var(--sab) + 330px); width: 36px; height: 260px; pointer-events: none !important; }
+.lvrx span { position: absolute; bottom: 0; left: 6px; animation: floatUp 2.6s ease-out forwards; color: var(--harm); } .lvrx span:nth-child(2n) { color: #fff; }
+.lv-tele { position: absolute; left: 14px; right: 14px; bottom: calc(var(--sab) + 302px); font-size: 9.5px; letter-spacing: .06em; color: rgba(255,255,255,.88); text-shadow: 0 1px 3px #000; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.lv-chain { position: absolute; left: 0; right: 0; bottom: calc(var(--sab) + 214px); display: flex; align-items: center; gap: 0; overflow-x: auto; padding: 0 14px; scrollbar-width: none; }
+.lv-chain::-webkit-scrollbar { display: none; }
+.lv-chain .seg { flex: none; width: 86px; border-radius: 10px; padding: 5px; background: rgba(8,10,14,.78); box-shadow: inset 0 0 0 .5px rgba(242,207,122,.45); display: flex; flex-direction: column; gap: 3px; }
+.lv-chain .seg img { width: 100%; height: 34px; object-fit: cover; border-radius: 6px; display: block; }
+.lv-chain .seg .si { font-size: 9px; color: var(--text3); } .lv-chain .seg .sh { font-size: 9px; color: var(--b-inside); }
+.lv-chain .seg .sk { display: inline-flex; gap: 3px; align-items: center; font-size: 9px; color: var(--text2); } .lv-chain .seg .sk .ic { width: 11px; height: 11px; }
+.lv-chain .seg.cur { box-shadow: inset 0 0 0 .5px rgba(255,255,255,.25); }
+.lv-chain .seg .fill { height: 34px; border-radius: 6px; background: rgba(255,255,255,.06); overflow: hidden; } .lv-chain .seg .fill i { display: block; height: 100%; width: 0; background: linear-gradient(90deg, rgba(242,207,122,.15), rgba(242,207,122,.45)); }
+.lv-chain .ln { flex: none; width: 12px; height: 2px; background: linear-gradient(90deg, var(--b-inside), rgba(242,207,122,.3)); }
+.lv-chain .seg.flash { animation: flash 1.2s ease; }
+.up { position: absolute; left: 12px; right: 12px; top: calc(var(--sat) + 62px); max-height: calc(100% - var(--sat) - 62px - var(--sab) - 230px); overflow: auto; border-radius: 20px; padding: 14px; font-size: 13.5px; color: var(--text2); scrollbar-width: none; }
+.uph { display: flex; justify-content: space-between; align-items: center; gap: 10px; } .uph b { color: #fff; font-size: 16px; }
+.up p { margin: 8px 0 12px; line-height: 1.45; } .up p b { color: #fff; }
+.tierb { display: inline-flex; gap: 4px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .1em; padding: 4px 6px 3px; border-radius: 4px; background: rgba(0,0,0,.6); color: var(--b-inside); }
+.tierb.unv { color: var(--text2); background: repeating-linear-gradient(135deg, rgba(255,255,255,.08) 0 4px, rgba(0,0,0,.5) 4px 8px); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.25); }
+.drop { display: flex; flex-direction: column; align-items: center; gap: 4px; padding: 22px 12px; border-radius: 16px; border: 1.5px dashed rgba(255,255,255,.22); color: var(--text2); cursor: pointer; margin-bottom: 10px; text-align: center; }
+.drop b { color: #fff; font-size: 15px; } .drop span { font-size: 12px; color: var(--text3); }
+.up .fine { margin: 10px 0 0; font-size: 9px; letter-spacing: .1em; text-align: center; }
+.upimg { position: relative; border-radius: 12px; overflow: hidden; } .upimg img { width: 100%; display: block; max-height: 220px; object-fit: cover; } .upimg .tierb { position: absolute; left: 8px; top: 8px; }
+.exif { display: grid; grid-template-columns: 1fr 1fr; gap: 6px 12px; margin: 10px 0; font-size: 10px; letter-spacing: .03em; }
+.exif div { display: flex; flex-direction: column; gap: 2px; min-width: 0; } .exif span { color: var(--text3); font-size: 8.5px; letter-spacing: .12em; } .exif b { color: #fff; font-weight: 600; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.placer { position: relative; border-radius: 12px; overflow: hidden; touch-action: none; } .placer canvas { width: 100%; display: block; }
+.placer .pin { position: absolute; width: 34px; height: 34px; margin: -34px 0 0 -17px; display: grid; place-items: center; color: #1b1408; background: var(--b-inside); border-radius: 50% 50% 50% 4px; transform: rotate(-45deg); box-shadow: 0 6px 18px rgba(0,0,0,.6); cursor: grab; touch-action: none; }
+.placer .pin .ic { transform: rotate(45deg); }
+.placer .hint { position: absolute; left: 8px; bottom: 8px; font-size: 9.5px; letter-spacing: .06em; color: #fff; background: rgba(0,0,0,.6); padding: 4px 6px; border-radius: 4px; }
+.uptime { display: grid; grid-template-columns: auto 1fr auto; gap: 10px; align-items: center; margin: 12px 0; font-size: 12px; } .uptime input { accent-color: var(--b-inside); } .uptime b { color: #fff; font-size: 11.5px; }
+.attach-ov { position: absolute; inset: 0; z-index: 78; display: none; align-items: flex-end; justify-content: center; background: rgba(0,0,0,.5); }
+.attach-ov.on { display: flex; animation: viewIn .3s var(--out); }
+.att { width: 100%; max-width: 560px; max-height: 92%; overflow: auto; border-radius: 28px 28px 0 0; padding: 6px 16px calc(var(--sab) + 16px); scrollbar-width: none; }
+.att .grab { height: 18px; display: grid; place-items: center; } .att .grab::before { content: ""; width: 38px; height: 5px; border-radius: 3px; background: rgba(255,255,255,.3); }
+.ath { display: grid; grid-template-columns: 112px 1fr; gap: 12px; align-items: center; }
+.atimg { position: relative; border-radius: 12px; overflow: hidden; aspect-ratio: 4/3; background: #06080c; } .atimg img { width: 100%; height: 100%; object-fit: cover; display: block; } .atimg .tierb { position: absolute; left: 6px; bottom: 6px; font-size: 7.5px; }
+.ath h2 { margin: 0; font: 750 21px/1.15 var(--display); } .ath p { margin: 4px 0 0; font-size: 10.5px; color: var(--text3); letter-spacing: .02em; }
+.ath2 { margin: 14px 0 7px; font-size: 11px; font-weight: 700; letter-spacing: .08em; text-transform: uppercase; color: var(--text3); }
+.sugs { display: flex; flex-direction: column; gap: 6px; }
+.sug { display: flex; align-items: center; gap: 10px; padding: 10px 12px; border-radius: 14px; background: rgba(255,255,255,.05); text-align: left; box-shadow: inset 0 0 0 .5px rgba(255,255,255,.08); }
+.sug i { width: 9px; height: 9px; border-radius: 50%; background: var(--c); box-shadow: 0 0 10px var(--c); flex: none; }
+.sug span { flex: 1; min-width: 0; } .sug b { display: block; font-size: 14.5px; } .sug small { font-size: 12px; color: var(--text3); }
+.sug em { width: 22px; height: 22px; border-radius: 50%; display: grid; place-items: center; box-shadow: inset 0 0 0 1.5px rgba(255,255,255,.25); color: transparent; flex: none; }
+.sug.on { background: rgba(242,207,122,.1); box-shadow: inset 0 0 0 1px rgba(242,207,122,.55); } .sug.on em { background: var(--b-inside); color: #1b1408; box-shadow: none; }
+.kinds2, .prec { display: flex; gap: 6px; flex-wrap: wrap; }
+.kinds2 button, .prec button { height: 32px; padding: 0 12px; border-radius: 10px; font-size: 13px; font-weight: 650; color: var(--text2); background: rgba(255,255,255,.06); }
+.kinds2 button.on, .prec button.on { background: #fff; color: #05070B; }
+.prec { display: grid; grid-template-columns: repeat(3, 1fr); }
+.att textarea { width: 100%; margin-top: 10px; border: 0; outline: 0; resize: none; border-radius: 12px; padding: 10px 12px; background: rgba(255,255,255,.06); font-size: 14.5px; }
+.fine2 { font-size: 11.5px; color: var(--text3); margin: 7px 2px 0; line-height: 1.4; } .fine2.priv { display: flex; gap: 6px; align-items: flex-start; margin: 10px 2px 12px; }
+.att .row2.holo { margin-top: 10px; border-radius: 14px; background: rgba(255,255,255,.04); }
+.lbl.eyelbl { font-size: 11px; padding: 4px 9px 4px 4px; }
+.lbl.eyelbl .ei { width: 20px; height: 20px; border-radius: 50%; display: grid; place-items: center; background: var(--b-inside); color: #1b1408; }
+.lbl.eyelbl .ei.k-cctv { background: var(--b-ground); } .lbl.eyelbl.k-you { box-shadow: inset 0 0 0 1.5px var(--b-inside), 0 0 24px rgba(242,207,122,.35); }
+.app[data-tab="capture"] .concept-tag { top: auto; bottom: calc(var(--sab) + 200px); left: 14px; right: auto; }
+.cap-top .st { white-space: nowrap; overflow: hidden; text-overflow: ellipsis; min-width: 0; }
+.cap-top .st:first-child { flex: 1 1 auto; } .cap-top .st:last-child { flex: 0 1 auto; }
+.lv-chat { right: 120px; } .lv-chat .bub { max-width: 100%; }
+.att { background: linear-gradient(180deg, rgba(255,255,255,.05), rgba(255,255,255,.01)), rgba(13,16,22,.97); }
+
+/* ---------- cold open: the descent ---------- */
+.cold { justify-content: center; padding: 0; background: radial-gradient(120% 80% at 50% 50%, transparent 40%, rgba(0,0,0,.55)); }
+.ladder { position: absolute; left: 16px; top: 50%; transform: translateY(-50%); height: 300px; width: 120px; display: flex; flex-direction: column; justify-content: space-between; opacity: 0; transition: opacity .6s; }
+.cold.s0 .ladder { opacity: 1; }
+.ladder::before { content: ""; position: absolute; left: 4px; top: 6px; bottom: 6px; width: 1px; background: linear-gradient(var(--b-orbit), var(--b-sky), var(--b-ground), var(--b-inside)); opacity: .5; }
+.lr { position: relative; padding-left: 18px; display: flex; flex-direction: column; gap: 2px; opacity: .38; transition: opacity .4s; }
+.lr i { position: absolute; left: 0; top: 3px; width: 9px; height: 9px; border-radius: 50%; box-shadow: inset 0 0 0 1.5px var(--c); }
+.lr b { font: 700 11px/1 var(--mono); letter-spacing: .16em; color: var(--c); } .lr span { font: 500 9px/1 var(--mono); letter-spacing: .06em; color: rgba(255,255,255,.6); }
+.lr.on { opacity: 1; } .lr.on i { background: var(--c); box-shadow: 0 0 12px var(--c); }
+.lmark { position: absolute; left: -3px; width: 15px; height: 2px; background: #fff; box-shadow: 0 0 10px #fff; top: 0; transition: top .15s linear; }
+.calt { position: absolute; left: 16px; top: calc(50% + 172px); font-size: 22px; font-weight: 700; letter-spacing: .02em; color: #fff; text-shadow: 0 2px 16px #000; opacity: 0; transition: opacity .5s; }
+.cold.s0 .calt { opacity: 1; }
+.ccap { position: absolute; left: 16px; right: 16px; bottom: calc(var(--sab) + 40px); font-size: 11px; letter-spacing: .12em; color: rgba(255,255,255,.85); text-shadow: 0 1px 8px #000; }
+.cwit { position: absolute; left: 50%; top: 50%; width: min(78vw, 360px); aspect-ratio: 440/560; transform: translate(-50%, -50%) scale(1.25); opacity: 0; border-radius: 6px; overflow: hidden; transition: opacity .7s ease, transform 1.4s var(--out); --c: var(--b-inside); box-shadow: 0 30px 80px rgba(0,0,0,.6); }
+.cwit canvas { width: 100%; height: 100%; display: block; }
+.cwit .tele { position: absolute; left: 14px; right: 14px; bottom: 11px; font: 600 9.5px/1.2 var(--mono); letter-spacing: .08em; color: #fff; text-shadow: 0 1px 4px #000; }
+.cold.s3 .cwit { opacity: 1; transform: translate(-50%, -58%) scale(1); }
+.cold.s3 .ladder, .cold.s3 .calt { opacity: .0; }
+.cttl { position: absolute; left: 0; right: 0; bottom: calc(var(--sab) + 9vh); text-align: center; }
+.cttl .word { font: 800 34px/1 var(--display); letter-spacing: .3em; margin-left: .3em; opacity: 0; transition: opacity 1s ease, letter-spacing 1.8s var(--out); }
+.cttl .tag { font: 600 12px/1.4 var(--mono); letter-spacing: .2em; text-transform: uppercase; color: var(--b-inside); margin-top: 12px; opacity: 0; transition: opacity 1s ease .3s; }
+.cold.s4 .cttl .word { opacity: 1; letter-spacing: .2em; } .cold.s4 .cttl .tag { opacity: 1; }
+.cold.s3 .ccap { opacity: 0; }
+.rooms-why { margin: 8px 20px 4px; font-size: 13px; line-height: 1.45; color: var(--text2); }
+.rooms-why b { color: var(--text); font-weight: 600; }
+.rooms-live { display: flex; flex-direction: column; gap: 10px; padding: 0 12px; }
+@media (min-width: 600px) {
+  .now-hero { height: auto; padding-top: calc(var(--sat) + 46px); }
+  .now-hero .hud { display: block; position: absolute; top: calc(var(--sat) + 30px); left: 20px; right: 20px; height: 1px; }
+  .now-hero .hud .hb, .now-hero .hud .xh, .now-hero .hud .hud-t { display: none; }
+  .now-hero .hud .wm { left: 0; top: -14px; }
+  .concept-tag, .app[data-tab] .concept-tag, .app[data-mode="situation"] .concept-tag { top: calc(var(--sat) + 62px); right: 66px; left: auto; bottom: auto; }
+  .app[data-tab="now"] .concept-tag { top: calc(var(--sat) + 62px); }
+}
+/* LIVE is not harm: hazard red stays reserved for things that hurt people */
+.dot { background: #fff; }
+@keyframes pulse { 0% { box-shadow: 0 0 0 0 rgba(255,255,255,.55); } 70% { box-shadow: 0 0 0 7px rgba(255,255,255,0); } 100% { box-shadow: 0 0 0 0 rgba(255,255,255,0); } }
+.ftop .lv, .patt .plive { background: rgba(255,255,255,.94); color: #05070B; }
+.ftop .lv i, .patt .plive .dot { background: #05070B; }
+.lvpill { background: #fff; color: #05070B; } .lvpill i { background: #FF3B30; }
+.ribbon .nowbtn.live { background: rgba(255,255,255,.14); color: #fff; }
+.ribbon.breath::before { animation: none; }
+.badge.live .dot { background: #fff; }
+/* instrument readouts in the brief */
+.metric .v { font: 700 21px/1.1 var(--mono); letter-spacing: -.02em; }
+.metric .v small { font-family: var(--font); }
+.metric .l { font-size: 11.5px; } .metric .s { font-family: var(--mono); font-size: 9.5px; letter-spacing: .03em; }
+
 </style>
 <svg width="0" height="0" style="position:absolute" aria-hidden="true">
   <defs>
@@ -705,6 +1068,8 @@ input, textarea { font: inherit; color: inherit; }
   <button class="backbtn circ glass" id="back" aria-label="Back"><svg class="ic"><use href="#i-chevl"/></svg></button>
   <div class="sitbtns" id="sitbtns"><button class="circ glass" id="sitFollow" aria-label="Follow"><svg class="ic"><use href="#i-bellplus"/></svg></button><button class="circ glass" id="sitShare" aria-label="Share"><svg class="ic"><use href="#i-share"/></svg></button></div>
   <div class="sheet glass strong" id="sheet"><div class="grab" id="grab"></div><div class="sc" id="sheetC"></div></div>
+  <div class="rx" id="rx" aria-hidden="true"></div>
+  <div class="roomcomp" id="roomComp"></div>
 
   <div class="ride" id="ride"></div>
   <section id="v-capture" class="view" aria-label="Capture"></section>
@@ -718,7 +1083,7 @@ input, textarea { font: inherit; color: inherit; }
       <button class="tab on" data-tab="now" role="tab"><svg class="ic"><use href="#i-radiowaves"/></svg><span>Now</span></button>
       <button class="tab" data-tab="globe" role="tab"><svg class="ic"><use href="#i-globe"/></svg><span>Globe</span></button>
       <button class="tab" data-tab="capture" role="tab"><svg class="ic"><use href="#i-viewfinder"/></svg><span>Capture</span></button>
-      <button class="tab" data-tab="threads" role="tab"><svg class="ic"><use href="#i-threads"/></svg><span>Threads</span></button>
+      <button class="tab" data-tab="threads" role="tab"><svg class="ic"><use href="#i-threads"/></svg><span>Rooms</span></button>
       <button class="tab" data-tab="you" role="tab"><svg class="ic"><use href="#i-person"/></svg><span>You</span></button>
     </div>
     <button class="accessory glass" id="accMini"></button>
@@ -727,14 +1092,17 @@ input, textarea { font: inherit; color: inherit; }
 
   <div class="morph" id="morph"></div>
   <div class="seal-ov" id="sealOv"></div>
+  <div class="attach-ov" id="attachOv"></div>
   <div class="inspector" id="inspector"></div>
   <div class="toastp glass" id="toast"></div>
   <div class="concept-tag">Concept · illustrative data</div>
   <div class="cold" id="cold">
     <button class="skip glass" id="skip">Skip</button>
-    <svg class="eye" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.1"><path d="M2.6 12S6 5.6 12 5.6 21.4 12 21.4 12 18 18.4 12 18.4 2.6 12 2.6 12Z"/><circle cx="12" cy="12" r="3.6"/><circle cx="12" cy="12" r="1.2" fill="currentColor"/></svg>
-    <div class="word">God’s Eye</div>
-    <div class="tag">The window to the world.</div>
+    <div class="ladder" id="ladder"><div class="lr" data-b="orbit" style="--c:var(--b-orbit)"><i></i><b>ORBIT</b><span>36,000–400 KM</span></div><div class="lr" data-b="sky" style="--c:var(--b-sky)"><i></i><b>SKY</b><span>15 KM</span></div><div class="lr" data-b="ground" style="--c:var(--b-ground)"><i></i><b>GROUND</b><span>0 M</span></div><div class="lr" data-b="inside" style="--c:var(--b-inside)"><i></i><b>INSIDE</b><span>A WITNESS</span></div><div class="lmark" id="lmark"></div></div>
+    <div class="calt mono" id="coldAlt">ALT 35,786 KM</div>
+    <div class="ccap mono" id="coldCap"></div>
+    <div class="cwit" id="coldWit"><canvas id="coldCv" width="440" height="560"></canvas><i class="bk a"></i><i class="bk b"></i><i class="bk c"></i><i class="bk d"></i><svg class="fseal"><use href="#i-seal"/></svg><div class="tele mono" id="coldTele">WITNESS · SEALED · ±4 M</div></div>
+    <div class="cttl"><div class="word">GOD’S EYE</div><div class="tag">From orbit to the witness.</div></div>
   </div>
 </div>
 <script>window.__GE_TEX={"clouds":"data:image/webp;base64,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","day":"data:image/webp;base64,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","night":"data:image/webp;base64,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","topo":"data:image/webp;base64,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","water":"data:image/webp;base64,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"};</script>
@@ -1265,6 +1633,24 @@ const PEOPLE = {
   crowd: { h: 'row_m_seat14', name: 'Lena', hue: 300 },
   news: { h: 'chopper_cam9', name: 'Desk 9', hue: 10 },
   ai: { h: 'claude', name: 'AI (proposal)', hue: 260, ai: true },
+  // round two: people across the bands (all fictional)
+  nadia: { h: 'nadia_basco', name: 'Nadia R.', hue: 18, home: [20.45, 121.97], where: 'Basco, Batanes' },
+  rafa: { h: 'rafa_aparri', name: 'Rafael D.', hue: 140, home: [18.36, 121.64], where: 'Aparri' },
+  mei: { h: 'mei_taitung', name: 'Mei-Ling C.', hue: 345, home: [22.76, 121.14], where: 'Taitung' },
+  joon: { h: 'joon_pilotboat', name: 'Joon-ho P.', hue: 190, domain: 'Mariner', home: [22.61, 120.28], where: 'Kaohsiung' },
+  lin: { h: 'lin_forecasts', name: 'Lin W.', hue: 225, domain: 'Met', where: 'Taipei' },
+  repost: { h: 'breaking_now_24', name: 'breaking_now_24', hue: 0 },
+  aiko: { h: 'aiko_sendai', name: 'Aiko S.', hue: 300, home: [38.27, 140.87], where: 'Sendai' },
+  tetsu: { h: 'tetsu_rail', name: 'Tetsuya O.', hue: 60, domain: 'Rail ops', where: 'Fukushima' },
+  tomas: { h: 'tomas_atc', name: 'Tomás V.', hue: 205, domain: 'Pilot', where: 'Reykjavík' },
+  seat: { h: 'seat_23F', name: 'Passenger, 23F', hue: 40 },
+  ines: { h: 'ines_coimbra', name: 'Inês M.', hue: 330, home: [40.2, -8.42], where: 'Coimbra' },
+  bomb: { h: 'bombeiro_ruiz', name: 'Cpt. Ruiz', hue: 8, domain: 'First responder', home: [40.1, -8.0], where: 'Pampilhosa' },
+  carla: { h: 'carla_avellaneda', name: 'Carla G.', hue: 280, home: [-34.66, -58.37], where: 'Avellaneda' },
+  dev: { h: 'dev_storms', name: 'Devansh K.', hue: 110, domain: 'Storm spotter', where: 'Arlington, TX' },
+  yuki: { h: 'yuki_kagoshima', name: 'Yuki T.', hue: 170, home: [31.6, 130.56], where: 'Kagoshima' },
+  ola: { h: 'ola_tromso', name: 'Ola B.', hue: 150, home: [69.65, 18.96], where: 'Tromsø' },
+  amara: { h: 'amara_lakefront', name: 'Amara J.', hue: 25, home: [41.88, -87.62], where: 'Chicago' },
 };
 
 Object.assign(GE, { AP, apByIata, FLIGHTS, flightAt, OPNAME, LANES, LANE_V, SHIPS, shipAt, SATS, ISS, CSS, satAt, QUAKES, BIGQ, FIRES, FIRE_CLUSTERS, CYCLONE, CITY_V, PEOPLE });
@@ -2475,6 +2861,9 @@ W.updateDynamic = function () {
   if (W.on('wind')) for (const w of WIND) { const age = ((t / w.life + w.ph) % 1 + 1) % 1; let la = w.lat, lo = w.lon; const steps = 4, dtH = (age * w.life) / 3600 / steps; for (let k = 0; k < steps; k++) { const [u, v] = windVel(la, lo, t); la += v * dtH; lo += u * dtH; } const [u, v] = windVel(la, lo, t); const fade = Math.sin(age * Math.PI); pushSpr(a, geo.vec(la, lo, 3), [0.75, 0.85, 1, 0.55 * fade], 14, 15, Math.atan2(u * Math.cos(la * D2R), v), -1e9, 1e9, 0, 0, 0.1); }
   for (const hh of W.userHolos) pushSpr(a, geo.vec(hh.lat, hh.lon, 0.06), [1, 0.85, 0.45, 1], 24, 6, -10, -1e9, 1e9, 0, 0.2, 0.4);
   if (W.activeExtrasId === 'climb') { const f = clamp((W.simMs - GE.T_CLIMB) / (2.23 * 3600000), 0, 1); const [la, lo] = geo.offset(40.7553, -73.9838, 16, 23.5); pushSpr(a, geo.vec(la, lo, (12 + f * 372) / 1000), [1, 0.3, 0.3, 1], 16, 9, -10, -1e9, 1e9, 0, 0.7, 0.9); }
+  for (const sp of W.extraSprites || []) pushSpr(a, sp.v, sp.col, sp.size || 24, sp.glyph ?? 9, -10, -1e9, 1e9, 0, sp.seed || 0.3, 0.8);
+  // eyes: people and cameras looking right now
+  if (W.on('cctv') || W.on('signed') || W.on('streams')) for (const e of GE.EYES || []) pushSpr(a, geo.vec(e.lat, e.lon, 0.05), e.kind === 'you' ? [1, 0.9, 0.55, 1] : e.kind === 'cctv' ? [1, 0.66, 0.26, 1] : [0.96, 0.82, 0.48, 1], e.kind === 'you' ? 26 : 15, 9, -10, -1e9, 1e9, 0, e.lat * 0.1, 0.6);
   // situation pins
   for (const p of W.situationPins) pushSpr(a, geo.vec(p.lat, p.lon, 0.2), p.col, p.size || 16, 9, -10, -1e9, 1e9, 0, p.seed || 0, 0.6);
   // selection highlight
@@ -2491,6 +2880,7 @@ W.updateDynamic = function () {
   }
   if (W.selRoute) pushPolyline(ln, W.selRoute, [1, 0.85, 0.45, 0.8], 1);
   for (const extra of W.extraLines) pushPolyline(ln, extra.pts, extra.col, extra.dashed || 0);
+  if (GE.eyeLines && (W.on('cctv') || W.on('signed') || W.on('streams'))) for (const ex of GE.eyeLines(W.lastRange)) pushPolyline(ln, ex.pts, ex.col, ex.dashed || 0);
   for (const hh of W.userHolos) pushPolyline(ln, [geo.vec(hh.lat, hh.lon, 0), geo.vec(hh.lat, hh.lon, 0.06)], [1, 0.85, 0.5, 0.9]);
   uploadDyn('dynLineBuf', 'dynLineVao', 'dynLineCap', 'dynLineCount', ln, 'line');
 };
@@ -2681,14 +3071,14 @@ W.post = function (chain, outFb, outW, outH, mode, opts) {
   gl.viewport(0, 0, opts.vpW ?? (outFb ? outW : gl.drawingBufferWidth), opts.vpH ?? (outFb ? outH : gl.drawingBufferHeight));
   GL.bindTex(Cp, 'uScene', chain.scene.tex, 0); GL.bindTex(Cp, 'uBloom', bloomOn ? lv[0].b.tex : lv[0].a.tex, 1);
   gl.uniform2f(Cp.u.uTexel, 1 / chain.w, 1 / chain.h);
-  gl.uniform1f(Cp.u.uExposure, (opts.exposure ?? 1) * (mode === 2 ? 1.25 : 0.62));
+  gl.uniform1f(Cp.u.uExposure, (opts.exposure ?? 1) * (mode === 2 ? 1.25 : mode === 0 ? 0.58 : 0.62));
   gl.uniform1f(Cp.u.uBloomK, bloomOn ? (mode === 4 ? 0.3 : 0.16) : 0);
   gl.uniform1f(Cp.u.uVig, opts.vig ?? (mode === 1 ? 0.25 : 0.9));
   gl.uniform1f(Cp.u.uGrain, (opts.grain ?? W.quality.grain) && mode !== 1 ? 0.022 : 0);
   gl.uniform1f(Cp.u.uT, performance.now() / 1000 % 100);
   gl.uniform1f(Cp.u.uFade, opts.fade ?? 1);
   gl.uniform1f(Cp.u.uFxaa, 1);
-  gl.uniform1f(Cp.u.uSat, mode === 1 ? 1.0 : 1.08);
+  gl.uniform1f(Cp.u.uSat, mode === 1 ? 1.0 : 1.12);
   gl.uniform1i(Cp.u.uMode, mode);
   gl.uniform3fv(Cp.u.uLift, [0.00017, 0.00038, 0.001]);
   gl.uniform3fv(Cp.u.uGain, mode === 0 ? [1.02, 1.0, 0.97] : [1, 1, 1]);
@@ -2976,6 +3366,755 @@ SC.draw = function (sc, view, { sun, t, eye, opts }) {
 // ground height (m) at lat/lon for scenes with terrain
 SC.groundAt = function (lat, lon) { const sc = SC.byId.koshi; if (!sc.height) return 0; const [x, y] = enuOf(sc, lat, lon); return sc.height(x, y); };
 
+// ---- 36-paint.js
+/* Painters — procedural sensor frames. Every feed card, room attachment and capture scene is drawn
+   here as the instrument that saw it would show it: IR cloud tops with an enhancement table, radar
+   reflectivity in dBZ bins over a street grid, CCTV frames with burned-in OSD, SAR speckle, shake maps,
+   long-exposure launch arcs. Geography comes from the bundled NASA masks; weather and people are
+   synthetic (Concept · illustrative data). */
+const PT = (GE.paint = {});
+const MONO = 'ui-monospace, "SF Mono", "JetBrains Mono", Menlo, Consolas, "DejaVu Sans Mono", monospace';
+PT.MONO = MONO;
+const hexrgb = (s) => [parseInt(s.slice(1, 3), 16), parseInt(s.slice(3, 5), 16), parseInt(s.slice(5, 7), 16)];
+const mk = (w, h) => { const c = document.createElement('canvas'); c.width = Math.max(1, w | 0); c.height = Math.max(1, h | 0); return c; };
+PT.mk = mk;
+
+/* ---------- value noise + fbm ---------- */
+function noiseGen(seed) {
+  const r = rng(seed * 7919 + 13); const p = new Uint8Array(512); const v = new Float32Array(256);
+  for (let i = 0; i < 256; i++) { p[i] = i; v[i] = r(); }
+  for (let i = 255; i > 0; i--) { const j = Math.floor(r() * (i + 1)); const t = p[i]; p[i] = p[j]; p[j] = t; }
+  for (let i = 0; i < 256; i++) p[i + 256] = p[i];
+  const n = (x, y) => {
+    const xi = Math.floor(x), yi = Math.floor(y), xf = x - xi, yf = y - yi, X = xi & 255, Y = yi & 255;
+    const u = xf * xf * (3 - 2 * xf), w = yf * yf * (3 - 2 * yf);
+    const a = v[p[p[X] + Y]], b = v[p[p[X + 1] + Y]], c = v[p[p[X] + Y + 1]], d = v[p[p[X + 1] + Y + 1]];
+    return a + (b - a) * u + (c - a) * w + (a - b - c + d) * u * w;
+  };
+  n.fbm = (x, y, o = 5, g = 0.5, l = 2.03) => { let s = 0, a = 0.5, f = 1, t = 0; for (let i = 0; i < o; i++) { s += a * n(x * f + i * 17.3, y * f - i * 9.1); t += a; a *= g; f *= l; } return s / t; };
+  n.ridge = (x, y, o = 5) => { let s = 0, a = 0.5, f = 1, t = 0; for (let i = 0; i < o; i++) { const q = 1 - Math.abs(n(x * f + i * 5.2, y * f + i * 1.7) * 2 - 1); s += a * q * q; t += a; a *= 0.5; f *= 2.1; } return s / t; };
+  return n;
+}
+PT.noise = noiseGen;
+
+/* ---------- colour ramps → 256 LUT ---------- */
+function lut(stops) {
+  const L = new Uint8ClampedArray(256 * 3); const S = stops.map(([t, c]) => [t, hexrgb(c)]);
+  for (let i = 0; i < 256; i++) { const t = i / 255; let k = 1; while (k < S.length - 1 && S[k][0] < t) k++; const a = S[k - 1], b = S[k]; const f = clamp((t - a[0]) / (b[0] - a[0] || 1), 0, 1); for (let j = 0; j < 3; j++) L[i * 3 + j] = a[1][j] + (b[1][j] - a[1][j]) * f; }
+  return L;
+}
+const LUT = {
+  inferno: lut([[0, '#000004'], [0.15, '#1f0c48'], [0.3, '#550f6d'], [0.45, '#88226a'], [0.6, '#ba3655'], [0.72, '#e35933'], [0.84, '#f98e09'], [0.94, '#f6d746'], [1, '#fcffa4']]),
+  mmi: lut([[0, '#bfccff'], [0.14, '#a0e6ff'], [0.28, '#80ffff'], [0.42, '#7aff93'], [0.56, '#ffff00'], [0.7, '#ffc800'], [0.84, '#ff6a00'], [1, '#c80000']]),
+};
+PT.LUT = LUT;
+// IR enhancement (BD-style): warm = dark grey; cold cloud tops step through cyan, blue, green, yellow, red, black, white
+function irColor(T, out) {
+  if (T > -30) { const g = clamp(lerp(28, 196, (30 - T) / 60), 0, 255); out[0] = g; out[1] = g; out[2] = g + 4; return; }
+  const st = [[-30, [150, 222, 245]], [-38, [52, 150, 225]], [-44, [28, 70, 200]], [-50, [40, 190, 70]], [-56, [235, 232, 70]], [-61, [246, 150, 40]], [-66, [226, 46, 30]], [-71, [120, 14, 18]], [-75, [12, 12, 14]], [-79, [96, 96, 100]], [-83, [236, 236, 240]], [-95, [255, 255, 255]]];
+  for (let i = 1; i < st.length; i++) if (T >= st[i][0]) { const a = st[i - 1], b = st[i]; const f = (a[0] - T) / (a[0] - b[0]); for (let j = 0; j < 3; j++) out[j] = a[1][j] + (b[1][j] - a[1][j]) * f; return; }
+  out[0] = out[1] = out[2] = 255;
+}
+const DBZ = [[18, '#03b33a'], [25, '#02d802'], [30, '#019a00'], [35, '#f4ec00'], [40, '#e4b800'], [45, '#fd8e00'], [50, '#fb0d00'], [55, '#cf0000'], [60, '#a80000'], [65, '#f400f6'], [70, '#9a52cc'], [75, '#ffffff']].map(([d, c]) => [d, hexrgb(c)]);
+function dbzColor(z, out) { if (z < 18) { out[3] = 0; return; } let k = 0; while (k < DBZ.length - 1 && DBZ[k + 1][0] <= z) k++; const c = DBZ[k][1]; out[0] = c[0]; out[1] = c[1]; out[2] = c[2]; out[3] = 225; }
+
+/* ---------- raster helpers ---------- */
+// fn(u, v, out, x, y) fills out[0..3] for each cell of a w/k × h/k field; drawn scaled onto ctx
+function field(ctx, w, h, k, fn, smoothOn = true, comp) {
+  const fw = Math.max(1, Math.round(w / k)), fh = Math.max(1, Math.round(h / k));
+  const c = mk(fw, fh), cx = c.getContext('2d'); const id = cx.createImageData(fw, fh); const d = id.data; const out = [0, 0, 0, 255];
+  for (let y = 0; y < fh; y++) for (let x = 0; x < fw; x++) { out[3] = 255; fn(x / fw, y / fh, out, x, y, fw, fh); const o = (y * fw + x) * 4; d[o] = out[0]; d[o + 1] = out[1]; d[o + 2] = out[2]; d[o + 3] = out[3]; }
+  cx.putImageData(id, 0, 0);
+  ctx.save(); if (comp) ctx.globalCompositeOperation = comp; ctx.imageSmoothingEnabled = smoothOn; ctx.imageSmoothingQuality = 'high'; ctx.drawImage(c, 0, 0, w, h); ctx.restore();
+}
+PT.field = field;
+let GRAIN = null;
+function grain(ctx, w, h, a = 0.07) {
+  if (!GRAIN) { GRAIN = mk(192, 192); const g = GRAIN.getContext('2d'); const id = g.createImageData(192, 192); const r = rng(99); for (let i = 0; i < id.data.length; i += 4) { const v = r() * 255; id.data[i] = id.data[i + 1] = id.data[i + 2] = v; id.data[i + 3] = 255; } g.putImageData(id, 0, 0); }
+  ctx.save(); ctx.globalAlpha = a; ctx.globalCompositeOperation = 'overlay'; ctx.fillStyle = ctx.createPattern(GRAIN, 'repeat'); const ox = (Math.random() * 192) | 0, oy = (Math.random() * 192) | 0; ctx.translate(-ox, -oy); ctx.fillRect(0, 0, w + 192, h + 192); ctx.restore();
+}
+function vignette(ctx, w, h, a = 0.55, inner = 0.35) { const g = ctx.createRadialGradient(w / 2, h / 2, Math.min(w, h) * inner, w / 2, h / 2, Math.hypot(w, h) * 0.6); g.addColorStop(0, 'rgba(0,0,0,0)'); g.addColorStop(1, `rgba(0,0,0,${a})`); ctx.fillStyle = g; ctx.fillRect(0, 0, w, h); }
+function scan(ctx, w, h, a = 0.08, step = 3) { ctx.save(); ctx.fillStyle = `rgba(0,0,0,${a})`; for (let y = 0; y < h; y += step) ctx.fillRect(0, y, w, 1); ctx.restore(); }
+function glow(ctx, x, y, r, col, a = 1) { const g = ctx.createRadialGradient(x, y, 0, x, y, r); g.addColorStop(0, col.replace('A', a)); g.addColorStop(0.35, col.replace('A', a * 0.35)); g.addColorStop(1, col.replace('A', 0)); ctx.fillStyle = g; ctx.fillRect(x - r, y - r, r * 2, r * 2); }
+// OSD text, camera style
+function osd(ctx, txt, x, y, px, align = 'left', col = 'rgba(255,255,255,.92)', base = 'top') {
+  ctx.save(); ctx.font = `600 ${px}px ${MONO}`; ctx.textAlign = align; ctx.textBaseline = base; ctx.lineJoin = 'round';
+  ctx.lineWidth = Math.max(2, px / 3.4); ctx.strokeStyle = 'rgba(0,0,0,.72)'; ctx.strokeText(txt, x, y); ctx.fillStyle = col; ctx.fillText(txt, x, y); ctx.restore();
+}
+function label(ctx, txt, x, y, px, col = 'rgba(235,240,248,.75)', align = 'left') { ctx.save(); ctx.font = `600 ${px}px ${MONO}`; ctx.textAlign = align; ctx.textBaseline = 'middle'; ctx.fillStyle = col; ctx.shadowColor = 'rgba(0,0,0,.9)'; ctx.shadowBlur = 4; ctx.fillText(txt, x, y); ctx.restore(); }
+Object.assign(PT, { grain, vignette, scan, glow, osd, label, lut, irColor });
+const z2 = (n) => String(n).padStart(2, '0');
+PT.stamp = (ms, sep = ' ') => { const d = new Date(ms); return `${d.getUTCFullYear()}-${z2(d.getUTCMonth() + 1)}-${z2(d.getUTCDate())}${sep}${z2(d.getUTCHours())}:${z2(d.getUTCMinutes())}:${z2(d.getUTCSeconds())}`; };
+
+/* ---------- maps (equirectangular, square km pixels) ---------- */
+function mapView(lat0, lon0, spanLon, w, h) {
+  const spanLat = spanLon * Math.cos(lat0 * D2R) * (h / w);
+  return { lat0, lon0, spanLon, spanLat, w, h, X: (lon) => ((((lon - lon0) + 540) % 360) - 180) / spanLon * w + w / 2, Y: (lat) => h / 2 - ((lat - lat0) / spanLat) * h, lon: (x) => lon0 + ((x - w / 2) / w) * spanLon, lat: (y) => lat0 + ((h / 2 - y) / h) * spanLat, kmPx: (spanLon * 111.32 * Math.cos(lat0 * D2R)) / w };
+}
+PT.mapView = mapView;
+const cropCache = new Map();
+function cropData(name, mv, w, h) {
+  const key = [name, mv.lat0.toFixed(3), mv.lon0.toFixed(3), mv.spanLon.toFixed(3), w, h].join('|');
+  if (cropCache.has(key)) return cropCache.get(key);
+  const img = GE.world.img && GE.world.img[name]; const c = mk(w, h), cx = c.getContext('2d', { willReadFrequently: true });
+  if (img) { cx.imageSmoothingQuality = 'high'; const iw = img.width, ih = img.height; const sx = ((mv.lon0 - mv.spanLon / 2 + 180) / 360) * iw, sy = ((90 - (mv.lat0 + mv.spanLat / 2)) / 180) * ih; cx.drawImage(img, sx, sy, (mv.spanLon / 360) * iw, (mv.spanLat / 180) * ih, 0, 0, w, h); }
+  const d = cx.getImageData(0, 0, w, h).data; if (cropCache.size > 40) cropCache.clear(); cropCache.set(key, d); return d;
+}
+PT.cropData = cropData;
+// dark instrument map: land/sea from the water mask, optional relief (topo) and night lights
+function mapBase(ctx, mv, o = {}) {
+  const { w, h } = mv; const k = o.k || 1; const fw = Math.round(w / k), fh = Math.round(h / k);
+  const wm = cropData('water', mv, fw, fh); const tp = o.relief ? cropData('topo', mv, fw, fh) : null; const nl = o.lights ? cropData('night', mv, fw, fh) : null;
+  const land = hexrgb(o.land || '#121922'), sea = hexrgb(o.sea || '#05080c'), coast = hexrgb(o.coast || '#46566c');
+  field(ctx, w, h, k, (u, v, out, x, y) => {
+    const i = (y * fw + x) * 4; const m = wm[i] / 255; const l = smooth(0.62, 0.38, m);
+    let r = lerp(sea[0], land[0], l), g = lerp(sea[1], land[1], l), b = lerp(sea[2], land[2], l);
+    if (tp && l > 0.3) { const e0 = tp[i], ex = tp[Math.min(i + 4, tp.length - 4)] - tp[Math.max(i - 4, 0)], ey = tp[Math.min(i + fw * 4, tp.length - 4)] - tp[Math.max(i - fw * 4, 0)]; const s = clamp(1 + (ey - ex) * 0.035 * (o.relief || 1) + e0 / 255 * 0.5, 0.55, 1.9); r *= s; g *= s; b *= s; }
+    if (nl) { const L = Math.max(0, nl[i + 1] - 10) / 245 * o.lights; r += L * 255; g += L * 190; b += L * 110; }
+    const e = smooth(0.6, 0.95, 1 - Math.abs(m - 0.5) * 2) * (o.coastA ?? 1); r = lerp(r, coast[0], e); g = lerp(g, coast[1], e); b = lerp(b, coast[2], e);
+    out[0] = r; out[1] = g; out[2] = b;
+  });
+}
+PT.mapBase = mapBase;
+function graticule(ctx, mv, step, col = 'rgba(160,190,230,.10)') {
+  ctx.save(); ctx.strokeStyle = col; ctx.lineWidth = 1; ctx.setLineDash([2, 4]);
+  for (let lo = Math.ceil((mv.lon0 - mv.spanLon / 2) / step) * step; lo < mv.lon0 + mv.spanLon / 2; lo += step) { const x = mv.X(lo); ctx.beginPath(); ctx.moveTo(x, 0); ctx.lineTo(x, mv.h); ctx.stroke(); }
+  for (let la = Math.ceil((mv.lat0 - mv.spanLat / 2) / step) * step; la < mv.lat0 + mv.spanLat / 2; la += step) { const y = mv.Y(la); ctx.beginPath(); ctx.moveTo(0, y); ctx.lineTo(mv.w, y); ctx.stroke(); }
+  ctx.restore();
+}
+function scaleBar(ctx, mv, km, x, y, col = 'rgba(235,240,248,.8)') { const px = km / mv.kmPx; ctx.save(); ctx.strokeStyle = col; ctx.lineWidth = 1.5; ctx.beginPath(); ctx.moveTo(x, y - 4); ctx.lineTo(x, y); ctx.lineTo(x + px, y); ctx.lineTo(x + px, y - 4); ctx.stroke(); ctx.restore(); label(ctx, km + ' KM', x + px + 5, y - 2, Math.max(8, mv.w / 42), col); }
+function plane(ctx, x, y, hdg, s, col) { ctx.save(); ctx.translate(x, y); ctx.rotate(hdg); ctx.scale(s / 24, s / 24); ctx.translate(-12, -12); ctx.fillStyle = col; ctx.fill(new Path2D('M12 2.8c.9 0 1.4.9 1.4 2v4.6l7.1 4.2v1.9l-7.1-2.1v4.4l2.2 1.7v1.6L12 20.2l-3.6.9v-1.6l2.2-1.7v-4.4l-7.1 2.1v-1.9l7.1-4.2V4.8c0-1.1.5-2 1.4-2Z')); ctx.restore(); }
+function cross(ctx, x, y, r, col, lw = 1.4) { ctx.save(); ctx.strokeStyle = col; ctx.lineWidth = lw; ctx.beginPath(); ctx.moveTo(x - r, y); ctx.lineTo(x + r, y); ctx.moveTo(x, y - r); ctx.lineTo(x, y + r); ctx.stroke(); ctx.restore(); }
+function poly(ctx, pts, close) { ctx.beginPath(); pts.forEach((p, i) => (i ? ctx.lineTo(p[0], p[1]) : ctx.moveTo(p[0], p[1]))); if (close) ctx.closePath(); }
+Object.assign(PT, { graticule, scaleBar, plane, cross, poly });
+
+/* =====================================================================================
+   ORBIT
+   ===================================================================================== */
+// IR cloud tops of a tropical cyclone with eyewall lightning and the advisory track
+PT.ir = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 3);
+  const C = GE.CYCLONE.at(0); const mv = mapView(C.lat + (o.dy ?? 0.6), C.lon + (o.dx ?? -0.8), o.span || 13, w, h);
+  const k = 2, fw = Math.round(w / k), fh = Math.round(h / k); const wm = cropData('water', mv, fw, fh); const col = [0, 0, 0];
+  const cl = Math.cos(C.lat * D2R);
+  field(ctx, w, h, k, (u, v, out, x, y) => {
+    const lat = mv.lat(v * h), lon = mv.lon(u * w); const dx = (lon - C.lon) * cl / 1.7, dy = (lat - C.lat) / 1.7; const r = Math.hypot(dx, dy), th = Math.atan2(dy, dx);
+    const wn = N.fbm(dx * 0.8 + 11, dy * 0.8 + 3, 4);
+    const arms = 0.5 + 0.5 * Math.sin(3 * (th - 2.1 * Math.log(r + 0.15)) + wn * 5.5);
+    const conv = N.fbm(dx * 1.9 + 4, dy * 1.9 - 2, 5);
+    const cdo = smooth(2.3, 0.9, r + (wn - 0.5) * 0.9), eye = smooth(0.16, 0.34, r), wall = Math.exp(-(((r - 0.4) / 0.15) ** 2));
+    let c = Math.max(cdo * (0.8 + 0.22 * conv), arms * smooth(7.5, 1.8, r) * (0.3 + 0.7 * conv) * smooth(0.28, 0.62, conv));
+    c = Math.max(c, wall * 0.97) * eye;
+    const bg = smooth(0.64, 0.86, N.fbm(dx * 0.55 + 40, dy * 0.55 + 9, 5)) * 0.62; c = Math.max(c, bg * (1 - cdo) * smooth(1.5, 4, r));
+    c += wall * smooth(0.6, 0.95, N(dx * 8, dy * 8)) * 0.12 + cdo * smooth(0.72, 0.98, N(dx * 5 + 3, dy * 5)) * 0.08;
+    const i = (y * fw + x) * 4; const land = 1 - wm[i] / 255;
+    irColor(26 - c * 114 + (c < 0.2 ? land * -10 : 0), col);
+    const edge = smooth(0.62, 0.95, 1 - Math.abs(wm[i] / 255 - 0.5) * 2) * (c < 0.55 ? 0.9 : 0.35);
+    out[0] = lerp(col[0], 236, edge); out[1] = lerp(col[1], 214, edge); out[2] = lerp(col[2], 96, edge);
+  });
+  graticule(ctx, mv, 5, 'rgba(255,255,255,.16)');
+  // advisory track: past (solid dots), forecast (dashed + cone)
+  const tr = GE.CYCLONE.track; ctx.save(); ctx.lineWidth = Math.max(1.2, w / 260);
+  const P = (q) => [mv.X(q[2]), mv.Y(q[1])];
+  ctx.strokeStyle = 'rgba(255,255,255,.85)'; poly(ctx, tr.filter((q) => q[0] <= 0).map(P)); ctx.stroke();
+  ctx.setLineDash([4, 4]); poly(ctx, tr.filter((q) => q[0] >= 0).map(P)); ctx.stroke(); ctx.setLineDash([]);
+  const fut = tr.filter((q) => q[0] >= 0); const L = [], Rr = [];
+  for (let i = 0; i < fut.length; i++) { const q = fut[i], n = fut[Math.min(i + 1, fut.length - 1)], p0 = fut[Math.max(i - 1, 0)]; const b = geo.bearing(p0[1], p0[2], n[1], n[2]); const km = GE.CYCLONE.cone(q[0]); const a = geo.dest(q[1], q[2], b - Math.PI / 2, km), c2 = geo.dest(q[1], q[2], b + Math.PI / 2, km); L.push([mv.X(a[1]), mv.Y(a[0])]); Rr.push([mv.X(c2[1]), mv.Y(c2[0])]); }
+  ctx.strokeStyle = 'rgba(255,255,255,.5)'; ctx.lineWidth = 1; poly(ctx, [...L, ...Rr.reverse()], true); ctx.stroke();
+  for (const q of tr) { const [x, y] = P(q); ctx.beginPath(); ctx.arc(x, y, q[0] === 0 ? w / 70 : w / 150, 0, TAU); ctx.fillStyle = q[0] < 0 ? '#fff' : q[0] === 0 ? 'rgba(0,0,0,0)' : 'rgba(255,255,255,.4)'; ctx.fill(); if (q[0] === 0) { ctx.strokeStyle = '#fff'; ctx.lineWidth = 1.5; ctx.stroke(); } }
+  ctx.restore();
+  // lightning in the eyewall and bands
+  const R = rng(o.seed || 5); const cx0 = mv.X(C.lon), cy0 = mv.Y(C.lat); const pxDeg = w / mv.spanLon;
+  ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let i = 0; i < (o.flashes ?? 34); i++) { const rr = (i < 12 ? 0.35 + R() * 0.25 : 0.7 + R() * 3.2) * 1.7, a = R() * TAU; const x = cx0 + Math.cos(a) * rr * pxDeg, y = cy0 - Math.sin(a) * rr * pxDeg; glow(ctx, x, y, w / (i < 4 ? 9 : 26), 'rgba(200,230,255,A)', i < 4 ? 0.55 : 0.4); cross(ctx, x, y, w / 90, 'rgba(255,255,255,.95)', 1.2); }
+  ctx.restore();
+  label(ctx, 'IR 10.4 µm', w * 0.05, h * PT.topY, Math.max(9, w / 34), 'rgba(255,255,255,.85)');
+  // enhancement legend
+  const lx = w * 0.6, ly = h * PT.botY, lw = w * 0.34, lh = Math.max(4, h / 90);
+  for (let i = 0; i < 60; i++) { irColor(10 - (i / 59) * 100, col); ctx.fillStyle = `rgb(${col[0]},${col[1]},${col[2]})`; ctx.fillRect(lx + (i / 60) * lw, ly, lw / 60 + 0.5, lh); }
+  label(ctx, '+10', lx, ly - lh, Math.max(7, w / 48), 'rgba(255,255,255,.7)'); label(ctx, '−90 °C', lx + lw, ly - lh, Math.max(7, w / 48), 'rgba(255,255,255,.7)', 'right');
+};
+
+// ISS external camera: the night side raycast from 418 km, airglow on the limb, truss in frame
+PT.isscam = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const lat0 = o.lat ?? 25.5, lon0 = o.lon ?? 31.0; const altKm = 418;
+  const reg = mapView(lat0 + 14, lon0 + 2, 46, 900, 900 * 0.75);
+  const RW = 900, RH = Math.round(900 * 0.75); const night = cropData('night', reg, RW, RH), clouds = cropData('clouds', reg, RW, RH), day = cropData('day', reg, RW, RH);
+  const en = geo.enu(lat0, lon0); const eye = geo.vec(lat0, lon0, altKm); const hd = (o.hdg ?? 8) * D2R, pitch = (o.pitch ?? 24) * D2R;
+  const fwdH = v3.add(v3.scale(en.north, Math.cos(hd)), v3.scale(en.east, Math.sin(hd)));
+  const fwd = v3.norm(v3.add(v3.scale(fwdH, Math.cos(pitch)), v3.scale(en.up, -Math.sin(pitch))));
+  const right = v3.norm(v3.cross(fwd, en.up)), up = v3.cross(right, fwd); const tanF = Math.tan((o.fov ?? 64) * D2R / 2), asp = w / h;
+  const N = noiseGen(31); const R2 = rng(4);
+  const samp = (D, lat, lon) => { const x = clamp(Math.round(((lon - (reg.lon0 - reg.spanLon / 2)) / reg.spanLon) * RW), 0, RW - 1), y = clamp(Math.round((((reg.lat0 + reg.spanLat / 2) - lat) / reg.spanLat) * RH), 0, RH - 1); return (y * RW + x) * 4; };
+  field(ctx, w, h, 2, (u, v, out) => {
+    const sx = (u * 2 - 1) * tanF * asp, sy = (1 - v * 2) * tanF; const d = v3.norm(v3.add(fwd, v3.add(v3.scale(right, sx), v3.scale(up, sy))));
+    const b = v3.dot(eye, d), c = v3.dot(eye, eye) - 1, disc = b * b - c;
+    if (disc > 0 && -b - Math.sqrt(disc) > 0) {
+      const t = -b - Math.sqrt(disc); const p = v3.madd(eye, d, t); const [la, lo] = geo.ll(p); const i = samp(null, la, lo);
+      const graz = clamp(-v3.dot(d, v3.norm(p)), 0, 1); const haze = Math.pow(1 - graz, 3);
+      const L = Math.pow(night[i + 1] / 255, 1.25) * 1.5; const cl = clouds[i] / 255;
+      out[0] = clamp(L * 255 * 1.05 + day[i] * 0.03 + cl * 14 + haze * 24, 0, 255); out[1] = clamp(L * 190 + day[i + 1] * 0.035 + cl * 18 + haze * 34, 0, 255); out[2] = clamp(L * 95 + day[i + 2] * 0.05 + cl * 26 + haze * 56, 0, 255);
+      const lit = (1 - cl * 0.6); out[0] *= lit; out[1] *= lit; out[2] *= lit; out[0] += cl * 10; out[1] += cl * 12; out[2] += cl * 20;
+    } else {
+      const tc = Math.max(0, -b); const cp = v3.madd(eye, d, tc); const a = (v3.len(cp) - 1) * EARTH_KM;
+      const glowG = Math.exp(-(((a - 92) / 9) ** 2)) * 0.95, glowR = Math.exp(-(((a - 110) / 14) ** 2)) * 0.35, sc = Math.exp(-Math.max(0, a) / 18) * 0.55;
+      out[0] = clamp(glowR * 150 + sc * 40, 0, 255); out[1] = clamp(glowG * 150 + sc * 70, 0, 255); out[2] = clamp(glowG * 70 + sc * 120 + 6, 0, 255);
+      if (a > 140 && R2() < 0.006) { const s = 120 + R2() * 135; out[0] = s; out[1] = s; out[2] = s + 10; }
+    }
+  });
+  // a lightning flash under cloud near the horizon
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, w * 0.28, h * 0.36, w * 0.12, 'rgba(170,200,255,A)', 0.7); glow(ctx, w * 0.31, h * 0.37, w * 0.05, 'rgba(240,248,255,A)', 0.8); ctx.restore();
+  // truss & solar array in the corner, rim-lit
+  ctx.save(); ctx.translate(w * 0.98, h * 0.02); ctx.rotate(0.42); ctx.fillStyle = '#07080b';
+  ctx.fillRect(-w * 0.62, -h * 0.07, w * 0.9, h * 0.1); ctx.strokeStyle = 'rgba(214,170,90,.55)'; ctx.lineWidth = 1;
+  for (let i = 0; i < 16; i++) { ctx.beginPath(); ctx.moveTo(-w * 0.62 + i * w * 0.056, -h * 0.07); ctx.lineTo(-w * 0.62 + i * w * 0.056, h * 0.03); ctx.stroke(); }
+  ctx.strokeStyle = 'rgba(255,214,140,.7)'; ctx.beginPath(); ctx.moveTo(-w * 0.62, h * 0.03); ctx.lineTo(w * 0.3, h * 0.03); ctx.stroke(); ctx.restore();
+  vignette(ctx, w, h, 0.45, 0.4); grain(ctx, w, h, 0.09);
+  osd(ctx, `ISS EXT CAM 2 · ${altKm} KM`, w * 0.05, h * PT.topY, Math.max(9, w / 36));
+};
+
+// your sky: the station's pass drawn as an arc on an alt-az chart
+PT.skychart = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const cx = w / 2, cy = h * 0.47, R = Math.min(w, h) * 0.4;
+  const g = ctx.createRadialGradient(cx, cy, 0, cx, cy, Math.max(w, h)); g.addColorStop(0, '#0d1430'); g.addColorStop(0.55, '#070a18'); g.addColorStop(1, '#020308'); ctx.fillStyle = g; ctx.fillRect(0, 0, w, h);
+  const r = rng(o.seed || 12); ctx.save();
+  for (let i = 0; i < 420; i++) { const a = r() * TAU, d = Math.sqrt(r()) * R * 1.35; const x = cx + Math.cos(a) * d, y = cy + Math.sin(a) * d; const m = Math.pow(r(), 6); ctx.fillStyle = `rgba(${220 + m * 35},${225 + m * 30},255,${0.25 + m * 0.75})`; ctx.fillRect(x, y, 1 + m * 2, 1 + m * 2); }
+  // a dipper-shaped asterism
+  const ast = [[-0.62, 0.3], [-0.48, 0.25], [-0.34, 0.29], [-0.22, 0.37], [-0.18, 0.51], [-0.02, 0.53], [0.02, 0.39]].map(([a, b]) => [cx + a * R, cy + b * R]);
+  ctx.strokeStyle = 'rgba(160,190,255,.22)'; ctx.lineWidth = 1; poly(ctx, ast); ctx.stroke(); for (const [x, y] of ast) { ctx.fillStyle = '#fff'; ctx.beginPath(); ctx.arc(x, y, w / 200 + 0.8, 0, TAU); ctx.fill(); }
+  ctx.strokeStyle = 'rgba(183,156,255,.28)'; ctx.setLineDash([2, 4]);
+  for (const k of [1, 2 / 3, 1 / 3]) { ctx.beginPath(); ctx.arc(cx, cy, R * k, 0, TAU); ctx.stroke(); }
+  ctx.setLineDash([]); ctx.strokeStyle = 'rgba(183,156,255,.6)'; ctx.lineWidth = 1.4; ctx.beginPath(); ctx.arc(cx, cy, R, 0, TAU); ctx.stroke();
+  const fs = Math.max(9, w / 30); for (const [t, a] of [['N', -90], ['E', 0], ['S', 90], ['W', 180]]) label(ctx, t, cx + Math.cos(a * D2R) * (R + fs * 0.9), cy + Math.sin(a * D2R) * (R + fs * 0.9), fs, t === 'N' ? '#FF6A3D' : 'rgba(220,210,255,.8)', 'center');
+  label(ctx, '30°', cx + 3, cy - R * 2 / 3 + 7, fs * 0.72, 'rgba(183,156,255,.6)'); label(ctx, '60°', cx + 3, cy - R / 3 + 7, fs * 0.72, 'rgba(183,156,255,.6)');
+  // the pass: rises WSW, culminates ~54°, sets ENE
+  const az0 = 245 * D2R, az1 = 62 * D2R, maxEl = (o.max ?? 54) * D2R; const pts = [];
+  for (let i = 0; i <= 60; i++) { const f = i / 60; let az = az0 + (((az1 - az0 + TAU * 1.5) % TAU) - Math.PI) * 0 + f * (((az1 - az0 + 3 * Math.PI) % TAU) - Math.PI); const el = Math.sin(f * Math.PI) * maxEl; const rr = R * (1 - el / (Math.PI / 2)); pts.push([cx + Math.sin(az) * rr, cy - Math.cos(az) * rr, f]); }
+  ctx.lineWidth = Math.max(2, w / 120); const gr = ctx.createLinearGradient(pts[0][0], pts[0][1], pts[60][0], pts[60][1]); gr.addColorStop(0, 'rgba(201,167,255,.25)'); gr.addColorStop(0.5, 'rgba(230,214,255,1)'); gr.addColorStop(1, 'rgba(201,167,255,.25)'); ctx.strokeStyle = gr; poly(ctx, pts); ctx.stroke();
+  const p0 = o.at ?? Date.now() + 3.2 * 3600000;
+  for (const k of [0, 20, 30, 40, 60]) { const [x, y] = pts[k]; ctx.fillStyle = '#E6D6FF'; ctx.beginPath(); ctx.arc(x, y, k === 30 ? w / 60 : w / 120, 0, TAU); ctx.fill(); if (k % 20 === 0 || k === 30) label(ctx, fmt.hm(p0 + (k / 60) * 6.5 * 60000), x + 7, y - 9, fs * 0.8, 'rgba(240,232,255,.9)'); }
+  ctx.globalCompositeOperation = 'lighter'; glow(ctx, pts[30][0], pts[30][1], w / 10, 'rgba(200,170,255,A)', 0.55); ctx.restore();
+  // moon
+  ctx.save(); ctx.translate(cx + R * 0.62, cy + R * 0.45); ctx.fillStyle = '#E8E4D8'; ctx.beginPath(); ctx.arc(0, 0, w / 40, 0, TAU); ctx.fill(); ctx.fillStyle = '#070a18'; ctx.beginPath(); ctx.arc(w / 110, -w / 160, w / 42, 0, TAU); ctx.fill(); ctx.restore();
+  label(ctx, `MAX ${Math.round(maxEl * R2D)}°`, pts[30][0], pts[30][1] + fs * 1.6, fs * 0.85, '#E6D6FF', 'center');
+};
+
+// long-range tracking camera: launch arc + sunlit "jellyfish" plume in twilight
+PT.plume = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const r = rng(o.seed || 21); const N = noiseGen(8);
+  const hz = h * 0.78; const sky = ctx.createLinearGradient(0, 0, 0, hz);
+  sky.addColorStop(0, '#02040c'); sky.addColorStop(0.45, '#0a1638'); sky.addColorStop(0.78, '#1d3a6a'); sky.addColorStop(0.93, '#5a5e7a'); sky.addColorStop(1, '#c47b4a');
+  ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz);
+  for (let i = 0; i < 260; i++) { const y = r() * hz * 0.7; ctx.fillStyle = `rgba(255,255,255,${0.15 + r() * 0.6 * (1 - y / hz)})`; ctx.fillRect(r() * w, y, 1, 1); }
+  // arc: pad at lower left, pitching over to the right
+  const pad = [w * 0.16, hz - 2]; const top = [w * 0.66, h * 0.22]; const ctrl = [w * 0.2, h * 0.18];
+  const B = (t) => [(1 - t) ** 2 * pad[0] + 2 * (1 - t) * t * ctrl[0] + t * t * top[0], (1 - t) ** 2 * pad[1] + 2 * (1 - t) * t * ctrl[1] + t * t * top[1]];
+  // sunlit plume (behind the arc): dome expanding up/right, iridescent rim
+  const pc = B(0.86); ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let i = 0; i < 90; i++) { const t = 0.55 + (i / 90) * 0.45; const p = B(t); const s = (t - 0.55) * w * 0.95; const a = (0.022 + 0.02 * N(i * 0.3, 2)) * (t > 0.7 ? 1 : (t - 0.55) / 0.15);
+    const g = ctx.createRadialGradient(p[0] + s * 0.25, p[1] - s * 0.2, s * 0.05, p[0] + s * 0.25, p[1] - s * 0.2, s * 0.85); g.addColorStop(0, `rgba(210,235,255,${a * 1.2})`); g.addColorStop(0.55, `rgba(120,190,255,${a * 0.7})`); g.addColorStop(0.85, `rgba(255,160,120,${a * 0.35})`); g.addColorStop(1, 'rgba(0,0,0,0)'); ctx.fillStyle = g; ctx.fillRect(0, 0, w, h); }
+  // jellyfish tendrils
+  ctx.strokeStyle = 'rgba(190,225,255,.22)'; ctx.lineWidth = 1;
+  for (let i = 0; i < 26; i++) { const a = -0.3 + (i / 25) * 2.2; ctx.beginPath(); ctx.moveTo(pc[0], pc[1]); for (let k = 1; k <= 12; k++) { const d = k * w * 0.028; ctx.lineTo(pc[0] + Math.cos(a) * d + N(i, k * 0.4) * 10, pc[1] + Math.sin(a) * d * 0.6 + k * k * 0.5); } ctx.stroke(); }
+  ctx.restore();
+  // the long-exposure streak
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; ctx.lineCap = 'round';
+  for (const [lw, col] of [[w / 22, 'rgba(255,120,40,.10)'], [w / 50, 'rgba(255,150,60,.35)'], [w / 120, 'rgba(255,220,170,.95)'], [w / 300, 'rgba(255,255,255,1)']]) {
+    ctx.lineWidth = lw; ctx.strokeStyle = col; ctx.beginPath(); for (let i = 0; i <= 80; i++) { const t = i / 80; const p = B(t * 0.88); i ? ctx.lineTo(p[0], p[1]) : ctx.moveTo(p[0], p[1]); } ctx.stroke(); }
+  glow(ctx, pad[0], pad[1], w * 0.2, 'rgba(255,150,70,A)', 0.55); ctx.restore();
+  // coast: land silhouette with lights, water reflecting the streak
+  ctx.fillStyle = '#040508'; ctx.beginPath(); ctx.moveTo(0, hz); for (let x = 0; x <= w; x += 6) ctx.lineTo(x, hz - 3 - N.fbm(x / 60, 1, 3) * 12 * (x < w * 0.5 ? 1 : 0.4)); ctx.lineTo(w, hz + 8); ctx.lineTo(0, hz + 8); ctx.fill();
+  for (let i = 0; i < 70; i++) { const x = r() * w; ctx.fillStyle = `rgba(255,${190 + r() * 50},${120 + r() * 60},${0.5 + r() * 0.5})`; ctx.fillRect(x, hz - 2 - r() * 6, 1.4, 1.4); }
+  const wg = ctx.createLinearGradient(0, hz, 0, h); wg.addColorStop(0, '#0d1424'); wg.addColorStop(1, '#030407'); ctx.fillStyle = wg; ctx.fillRect(0, hz + 6, w, h - hz);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; for (let y = hz + 8; y < h; y += 2) { const f = (y - hz) / (h - hz); const jit = (N(y * 0.2, 3) - 0.5) * 18 * f; ctx.fillStyle = `rgba(255,140,60,${0.35 * (1 - f)})`; ctx.fillRect(pad[0] - 4 - f * 10 + jit, y, 8 + f * 22, 1.4); ctx.fillStyle = `rgba(150,190,255,${0.08 * (1 - f)})`; ctx.fillRect(w * 0.5 + jit * 2, y, w * 0.3, 1); } ctx.restore();
+  vignette(ctx, w, h, 0.4); grain(ctx, w, h, 0.1);
+  osd(ctx, 'TRK CAM 3 · 400 MM · LONG EXPOSURE', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.8)');
+};
+
+// active fire seen from orbit: hillshaded terrain, burn scar, front, hotspot pixels, smoke plume
+PT.firesat = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 17); const s = 2.1 / w;
+  const scarC = [w * 0.62, h * 0.6], scarR = w * 0.26; const front = [];
+  const H = (x, y) => N.ridge(x * s, y * s, 5) * 0.9 + N.fbm(x * s * 0.4 + 5, y * s * 0.4, 3) * 0.6;
+  const scarAt = (x, y) => { const dx = x - scarC[0], dy = (y - scarC[1]) * 1.35; const a = Math.atan2(dy, dx); const rr = scarR * (0.75 + 0.45 * N(Math.cos(a) * 1.4 + 3, Math.sin(a) * 1.4 + 7)); return Math.hypot(dx, dy) / rr; };
+  field(ctx, w, h, 2, (u, v, out) => {
+    const x = u * w, y = v * h; const e = 2.2; const hc = H(x, y), hx = H(x + e, y), hy = H(x, y + e); const shade = clamp(0.82 + (hc - hx) * 15 - (hc - hy) * 11, 0.45, 1.35);
+    const veg = smooth(0.42, 0.7, N.fbm(x * s * 1.8 + 30, y * s * 1.8, 4));
+    let r = lerp(150, 62, veg), g = lerp(132, 82, veg), b = lerp(88, 48, veg);
+    const fld = N(x * s * 6 + 70, y * s * 6) > 0.72 && hc < 0.55 ? 1 : 0; if (fld) { r = 168; g = 150; b = 98; }
+    r *= shade; g *= shade; b *= shade;
+    const sc = scarAt(x, y); const burnt = smooth(1.02, 0.94, sc); const rim = Math.exp(-(((sc - 1) / 0.05) ** 2));
+    r = lerp(r, 34 + hc * 18, burnt); g = lerp(g, 30 + hc * 14, burnt); b = lerp(b, 28 + hc * 12, burnt);
+    r = lerp(r, 92, rim * 0.6); g = lerp(g, 60, rim * 0.6); b = lerp(b, 40, rim * 0.6);
+    out[0] = r; out[1] = g; out[2] = b;
+  });
+  // river & roads & a village
+  ctx.save(); ctx.strokeStyle = 'rgba(40,70,90,.9)'; ctx.lineWidth = w / 120; ctx.beginPath(); for (let i = 0; i <= 40; i++) { const t = i / 40; const x = t * w, y = h * 0.18 + Math.sin(t * 5) * h * 0.05 + N(t * 4, 9) * h * 0.08; i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke();
+  ctx.strokeStyle = 'rgba(225,215,190,.45)'; ctx.lineWidth = w / 260; for (const k of [0, 1, 2]) { ctx.beginPath(); for (let i = 0; i <= 30; i++) { const t = i / 30; const x = t * w, y = h * (0.35 + k * 0.28) + Math.sin(t * 3 + k) * h * 0.06 + N(t * 3, k * 5) * 20; i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke(); }
+  const vr = rng(3); for (let i = 0; i < 55; i++) { ctx.fillStyle = `rgba(${200 + vr() * 40},${190 + vr() * 30},${170 + vr() * 30},.8)`; ctx.fillRect(w * 0.2 + vr.gauss() * w * 0.04, h * 0.42 + vr.gauss() * h * 0.03, 2, 2); }
+  ctx.restore();
+  // fire front on the downwind (west) edge + hotspot pixels
+  const R = rng(9); ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let i = 0; i < 160; i++) { const a = Math.PI * (0.55 + R() * 0.95); let lo = 0.5, hi = 1.6; for (let k = 0; k < 14; k++) { const m = (lo + hi) / 2; const x = scarC[0] + Math.cos(a) * scarR * m, y = scarC[1] + (Math.sin(a) * scarR * m) / 1.35; if (scarAt(x, y) < 1) lo = m; else hi = m; } const x = scarC[0] + Math.cos(a) * scarR * lo, y = scarC[1] + (Math.sin(a) * scarR * lo) / 1.35; front.push([x, y]); glow(ctx, x, y, w / 36, 'rgba(255,90,20,A)', 0.4); }
+  for (const [x, y] of front) { const q = R(); const ps = Math.max(2, w / 110); ctx.fillStyle = q > 0.8 ? 'rgba(255,240,150,.95)' : q > 0.4 ? 'rgba(255,140,30,.9)' : 'rgba(230,40,20,.85)'; ctx.fillRect(Math.round(x / ps) * ps, Math.round(y / ps) * ps, ps, ps); }
+  ctx.restore();
+  // smoke: drifts WNW from the front
+  const src = [scarC[0] - scarR * 0.85, scarC[1] - scarR * 0.1], dir = v3.norm([-1, -0.55, 0]);
+  field(ctx, w, h, 3, (u, v, out) => {
+    const x = u * w - src[0], y = v * h - src[1]; const al = x * dir[0] + y * dir[1], ac = -x * dir[1] + y * dir[0]; if (al < -20) { out[3] = 0; return; }
+    const wd = 16 + Math.max(0, al) * 0.5; const n = N.fbm(al / 46 + 4, ac / 22, 5); const dn = Math.exp(-((ac / wd) ** 2) * (1.4 - n)) * smooth(-20, 30, al) * Math.exp(-Math.max(0, al) / (w * 2.6)) * (0.5 + 0.8 * n);
+    const a = clamp(dn * 1.1, 0, 0.92); out[0] = lerp(215, 160, n); out[1] = lerp(212, 160, n); out[2] = lerp(206, 170, n); out[3] = a * 255;
+  }, true);
+  label(ctx, 'VIIRS-CLASS 375 M · FRP 840 MW', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+  const mv = { kmPx: 18 / w, w }; scaleBar(ctx, mv, 5, w * 0.06, h * PT.botY);
+  // wind arrow
+  ctx.save(); ctx.translate(w * 0.86, h * PT.botY - 6); ctx.rotate(Math.atan2(dir[1], dir[0])); ctx.strokeStyle = 'rgba(255,255,255,.85)'; ctx.lineWidth = 1.5; ctx.beginPath(); ctx.moveTo(-14, 0); ctx.lineTo(14, 0); ctx.lineTo(8, -5); ctx.moveTo(14, 0); ctx.lineTo(8, 5); ctx.stroke(); ctx.restore();
+};
+
+// synthetic-aperture radar pass over an anchorage: speckle, bright hull returns with sidelobes
+PT.sar = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 23); const R = rng(o.seed || 23);
+  const coast = (v) => w * (0.3 + 0.08 * Math.sin(v * 5) + 0.06 * N(v * 4, 2));
+  field(ctx, w, h, 1.5, (u, v, out) => {
+    const x = u * w, cxl = coast(v); const sea = smooth(cxl - 3, cxl + 3, x); const sp = -Math.log(Math.max(1e-4, R())) * 0.55;
+    const fieldsTex = N(u * 26, v * 26) > 0.55 ? 0.22 : 0; const town = Math.exp(-(((u - 0.12) / 0.08) ** 2 + ((v - 0.62) / 0.12) ** 2)) * (N(u * 90, v * 90) > 0.5 ? 0.9 : 0.25);
+    const land = (0.26 + N.fbm(u * 10, v * 10, 5) * 0.36 + fieldsTex + town) * (0.55 + sp * 0.6);
+    const wave = (0.035 + N.fbm(u * 24 + 2, v * 6, 3) * 0.05) * (0.3 + sp * 1.3) + Math.exp(-(((x - cxl) / 7) ** 2)) * 0.25;
+    const g = clamp(lerp(land, wave, sea), 0, 1) * 255; out[0] = g * 0.93; out[1] = g * 0.97; out[2] = g;
+  }, false);
+  // dredged channel + breakwater
+  ctx.save(); ctx.strokeStyle = 'rgba(0,0,0,.75)'; ctx.lineWidth = w / 60; ctx.beginPath(); ctx.moveTo(coast(0.05) + 4, 0); ctx.lineTo(w * 0.42, h * 0.45); ctx.stroke(); ctx.strokeStyle = 'rgba(255,255,255,.8)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(coast(0.5), h * 0.5); ctx.lineTo(w * 0.5, h * 0.47); ctx.stroke(); ctx.restore();
+  // anchorage: hull returns with cross-shaped sidelobes
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; const n = o.ships || 48;
+  for (let i = 0; i < n; i++) { const cl = i % 3; const x = w * ([0.62, 0.78, 0.56][cl] + R.gauss() * 0.08), y = h * ([0.3, 0.55, 0.78][cl] + R.gauss() * 0.07); const L = w / 30 * (0.6 + R() * 0.9); const a = 0.4 + R() * 0.5; ctx.save(); ctx.translate(x, y); ctx.rotate(a); ctx.fillStyle = 'rgba(255,255,255,.95)'; ctx.fillRect(-L / 2, -1.6, L, 3.2); ctx.restore(); ctx.fillStyle = 'rgba(255,255,255,.16)'; ctx.fillRect(x - L * 1.6, y - 0.5, L * 3.2, 1); ctx.fillRect(x - 0.5, y - L * 1.3, 1, L * 2.6); glow(ctx, x, y, L * 0.7, 'rgba(255,255,255,A)', 0.22); }
+  // one moving ship with a wake and Doppler offset
+  ctx.fillStyle = 'rgba(255,255,255,.9)'; ctx.fillRect(w * 0.44, h * 0.18, w / 22, 3); ctx.strokeStyle = 'rgba(255,255,255,.25)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(w * 0.44, h * 0.18 + 1); ctx.lineTo(w * 0.3, h * 0.12); ctx.stroke(); ctx.fillStyle = 'rgba(255,255,255,.35)'; ctx.fillRect(w * 0.47, h * 0.24, w / 22, 2);
+  ctx.restore();
+  label(ctx, 'SAR · C-BAND · VV · 10 M', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+  scaleBar(ctx, { kmPx: 22 / w, w }, 5, w * 0.06, h * PT.botY);
+};
+
+/* =====================================================================================
+   SKY
+   ===================================================================================== */
+// radar reflectivity: a bowing squall line crossing a city's street grid, lightning, warning box
+PT.radar = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 41); const R = rng(o.seed || 41);
+  ctx.fillStyle = '#0a0e14'; ctx.fillRect(0, 0, w, h);
+  const cores = [[w * 0.62, h * 0.5, w * 0.34], [w * 0.22, h * 0.56, w * 0.22]];
+  const urb = (x, y) => Math.max(...cores.map(([cx, cy, r]) => Math.exp(-((x - cx) ** 2 + (y - cy) ** 2) / (r * r))));
+  field(ctx, w, h, 2, (u, v, out) => { const x = u * w, y = v * h; const k = urb(x, y) * (0.6 + 0.5 * N.fbm(u * 9, v * 9, 3)); out[0] = 10 + k * 22; out[1] = 14 + k * 24; out[2] = 20 + k * 30; });
+  // street grid
+  ctx.save(); ctx.lineWidth = 1; const step = Math.max(5, w / 60);
+  for (let x = 0; x < w; x += step) for (let y = 0; y < h; y += step) { const k = urb(x, y); if (R() > k * 1.3) continue; ctx.strokeStyle = `rgba(170,190,220,${0.06 + k * 0.1})`; ctx.beginPath(); ctx.moveTo(x, y); ctx.lineTo(x + step, y); ctx.moveTo(x, y); ctx.lineTo(x, y + step); ctx.stroke(); }
+  // lakes, river, highways
+  ctx.fillStyle = '#0f2236'; for (const [x, y, rx, ry] of [[0.42, 0.22, 0.05, 0.03], [0.86, 0.3, 0.04, 0.06], [0.1, 0.8, 0.05, 0.025]]) { ctx.beginPath(); ctx.ellipse(x * w, y * h, rx * w, ry * h, 0.4, 0, TAU); ctx.fill(); }
+  ctx.strokeStyle = 'rgba(70,120,170,.6)'; ctx.lineWidth = w / 200; ctx.beginPath(); for (let i = 0; i <= 50; i++) { const t = i / 50; const x = t * w, y = h * 0.62 + Math.sin(t * 9) * h * 0.03 + N(t * 5, 2) * h * 0.06; i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke();
+  ctx.strokeStyle = 'rgba(190,205,230,.32)'; ctx.lineWidth = w / 170;
+  for (const [x1, y1, x2, y2] of [[0, 0.5, 1, 0.47], [0.62, 0, 0.6, 1], [0.22, 0, 0.25, 1], [0, 0.15, 1, 0.92], [0, 0.9, 1, 0.12]]) { ctx.beginPath(); ctx.moveTo(x1 * w, y1 * h); ctx.lineTo(x2 * w, y2 * h); ctx.stroke(); }
+  ctx.beginPath(); ctx.ellipse(w * 0.62, h * 0.5, w * 0.16, h * 0.13, 0, 0, TAU); ctx.stroke(); ctx.beginPath(); ctx.ellipse(w * 0.22, h * 0.56, w * 0.1, h * 0.08, 0, 0, TAU); ctx.stroke(); ctx.restore();
+  // reflectivity: bowing line (arc), trailing stratiform, isolated cells ahead
+  const ac = [w * 0.05, h * 0.5], AR = w * 0.58;
+  const col = [0, 0, 0, 0];
+  field(ctx, w, h, 3, (u, v, out) => {
+    const x = u * w, y = v * h; const dx = x - ac[0], dy = y - ac[1]; const r = Math.hypot(dx, dy), a = Math.atan2(dy, dx);
+    const span = smooth(1.25, 0.75, Math.abs(a)); const d = (r - AR - Math.cos(a * 2) * w * 0.05) / w;
+    const n = N.fbm(x / 26, y / 26, 4), n2 = N(x / 9, y / 9);
+    const core = Math.exp(-((d / 0.035) ** 2)) * span * (0.65 + 0.6 * n) * (1 + 0.5 * Math.exp(-((a / 0.22) ** 2)));
+    const strat = Math.exp(-(((d + 0.12) / 0.11) ** 2)) * span * (0.5 + 0.7 * n);
+    let cell = 0; for (const [cx, cy, cr] of [[0.82, 0.25, 0.04], [0.9, 0.62, 0.03], [0.76, 0.82, 0.035]]) cell = Math.max(cell, Math.exp(-((x - cx * w) ** 2 + (y - cy * h) ** 2) / (cr * w) ** 2) * (0.7 + 0.4 * n2));
+    const z = 8 + Math.max(core * 58, strat * 28, cell * 52) + (n2 - 0.5) * 6; dbzColor(z, col); out[0] = col[0]; out[1] = col[1]; out[2] = col[2]; out[3] = col[3];
+  }, false);
+  // tornado-warning polygon at the bow apex (harm → hazard red)
+  const ap = [ac[0] + AR + w * 0.05, ac[1]]; ctx.save(); ctx.strokeStyle = '#FF3B30'; ctx.lineWidth = Math.max(1.5, w / 160); poly(ctx, [[ap[0] - w * 0.06, ap[1] - h * 0.09], [ap[0] + w * 0.13, ap[1] - h * 0.06], [ap[0] + w * 0.12, ap[1] + h * 0.07], [ap[0] - w * 0.05, ap[1] + h * 0.08]], true); ctx.stroke(); ctx.restore();
+  // lightning
+  for (let i = 0; i < 40; i++) { const a = (R() - 0.5) * 1.6, rr = AR + (R() - 0.6) * w * 0.07; const x = ac[0] + Math.cos(a) * rr, y = ac[1] + Math.sin(a) * rr; cross(ctx, x, y, w / 110, i % 5 ? 'rgba(255,255,255,.9)' : 'rgba(255,230,0,1)', 1.2); }
+  // storm motion
+  ctx.save(); ctx.translate(ap[0] + w * 0.16, ap[1] + h * 0.17); ctx.strokeStyle = '#fff'; ctx.lineWidth = 1.6; ctx.beginPath(); ctx.moveTo(-18, 0); ctx.lineTo(16, 0); ctx.lineTo(10, -5); ctx.moveTo(16, 0); ctx.lineTo(10, 5); ctx.stroke(); ctx.restore();
+  label(ctx, '72 KM/H', ap[0] + w * 0.16, ap[1] + h * 0.21, Math.max(8, w / 44), 'rgba(255,255,255,.85)', 'center');
+  for (const [t, x, y] of [['FORT WORTH', 0.22, 0.6], ['DALLAS', 0.62, 0.55], ['ARLINGTON', 0.43, 0.66]]) label(ctx, t, x * w, y * h, Math.max(7, w / 50), 'rgba(220,230,245,.55)', 'center');
+  label(ctx, '0.5° REFLECTIVITY · dBZ', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+  const lx = w * 0.05, ly = h * PT.botY; DBZ.forEach(([d, c], i) => { ctx.fillStyle = `rgb(${c[0]},${c[1]},${c[2]})`; ctx.fillRect(lx + i * (w * 0.035), ly, w * 0.035, Math.max(4, h / 90)); }); label(ctx, '20', lx, ly - 6, Math.max(7, w / 52), 'rgba(255,255,255,.7)'); label(ctx, '75', lx + DBZ.length * w * 0.035, ly - 6, Math.max(7, w / 52), 'rgba(255,255,255,.7)', 'right');
+};
+
+// one aircraft squawking 7700: the track turns red where it declared, diverts and descends
+PT.track = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const T = o.track;
+  const lats = T.pts.map((p) => p[0]).concat(T.div.lat), lons = T.pts.map((p) => p[1]).concat(T.div.lon);
+  const la0 = (Math.min(...lats) + Math.max(...lats)) / 2, lo0 = (Math.min(...lons) + Math.max(...lons)) / 2;
+  const span = Math.max(8, (Math.max(...lons) - Math.min(...lons)) * 1.5, ((Math.max(...lats) - Math.min(...lats)) * 1.6 * w) / h / Math.cos(la0 * D2R));
+  const mv = mapView(la0, lo0, span, w, h);
+  mapBase(ctx, mv, { lights: 0.9, relief: 0.6, land: '#151c26', sea: '#04070b', coast: '#3a4a60' });
+  graticule(ctx, mv, 5);
+  const P = T.pts.map(([la, lo]) => [mv.X(lo), mv.Y(la)]); const k = T.sqAt;
+  ctx.save(); ctx.lineCap = 'round'; ctx.lineJoin = 'round';
+  ctx.lineWidth = Math.max(1.5, w / 200); ctx.strokeStyle = 'rgba(190,215,240,.75)'; poly(ctx, P.slice(0, k + 1)); ctx.stroke();
+  ctx.lineWidth = Math.max(2.2, w / 130); ctx.strokeStyle = '#FF3B30'; ctx.shadowColor = 'rgba(255,59,48,.8)'; ctx.shadowBlur = 10; poly(ctx, P.slice(k)); ctx.stroke(); ctx.shadowBlur = 0;
+  // remaining leg to the diversion field
+  const cur = P[P.length - 1]; const dv = [mv.X(T.div.lon), mv.Y(T.div.lat)]; ctx.setLineDash([5, 5]); ctx.lineWidth = 1.4; ctx.strokeStyle = 'rgba(255,120,110,.8)'; ctx.beginPath(); ctx.moveTo(cur[0], cur[1]); ctx.quadraticCurveTo((cur[0] + dv[0]) / 2 + w * 0.05, (cur[1] + dv[1]) / 2, dv[0], dv[1]); ctx.stroke(); ctx.setLineDash([]);
+  for (const r of [w / 30, w / 18]) { ctx.strokeStyle = 'rgba(255,255,255,.7)'; ctx.lineWidth = 1; ctx.beginPath(); ctx.arc(dv[0], dv[1], r, 0, TAU); ctx.stroke(); }
+  ctx.restore();
+  label(ctx, T.div.iata, dv[0] + w / 16, dv[1], Math.max(9, w / 30), '#fff');
+  const p0 = P[P.length - 2] || P[0]; plane(ctx, cur[0], cur[1], Math.atan2(cur[0] - p0[0], -(cur[1] - p0[1])), Math.max(14, w / 14), '#fff');
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, cur[0], cur[1], w / 6, 'rgba(255,59,48,A)', 0.55); ctx.restore();
+  // squawk tag
+  const tx = clamp(cur[0] + w * 0.04, 4, w - w * 0.36), ty = clamp(cur[1] - h * 0.12, 4, h * 0.7); ctx.fillStyle = '#FF3B30'; ctx.fillRect(tx, ty, w * 0.3, h * 0.065); label(ctx, 'SQ 7700', tx + w * 0.15, ty + h * 0.034, Math.max(9, w / 26), '#fff', 'center');
+  // descent profile inset
+  const ix = w * 0.05, iy = h * 0.6, iw = w * 0.42, ih = h * 0.14; ctx.fillStyle = 'rgba(5,8,12,.72)'; ctx.fillRect(ix, iy, iw, ih); ctx.strokeStyle = 'rgba(255,255,255,.15)'; ctx.strokeRect(ix + 0.5, iy + 0.5, iw - 1, ih - 1);
+  const prof = T.alt; const mx = Math.max(...prof); ctx.beginPath(); prof.forEach((a, i) => { const x = ix + 4 + (i / (prof.length - 1)) * (iw - 8), y = iy + ih - 5 - (a / mx) * (ih - 14); i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); }); ctx.strokeStyle = '#FF6B61'; ctx.lineWidth = 1.6; ctx.stroke();
+  label(ctx, 'ALT ↓ FL370 → FL' + Math.round(prof[prof.length - 1] / 100), ix + 5, iy + 8, Math.max(7, w / 50), 'rgba(255,255,255,.8)');
+};
+
+// lightning density over a basin (number card backdrop)
+PT.strikes = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const mv = mapView(o.lat ?? 26.5, o.lon ?? -89, o.span ?? 22, w, h);
+  mapBase(ctx, mv, { lights: 0.7, land: '#10161e', sea: '#04070b', coast: '#2c3a4c' }); const R = rng(o.seed || 77);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  const cells = [[25.6, -88.2, 1.4], [27.4, -91.5, 1.0], [24.4, -84.9, 0.9], [28.6, -86.4, 0.7], [23.2, -92.8, 1.1]];
+  for (const [la, lo, s] of cells) for (let i = 0; i < 260 * s; i++) { const x = mv.X(lo + R.gauss() * s), y = mv.Y(la + R.gauss() * s * 0.7); const age = R(); ctx.fillStyle = age < 0.15 ? 'rgba(255,255,255,.95)' : age < 0.5 ? 'rgba(255,230,90,.75)' : 'rgba(255,140,40,.45)'; ctx.fillRect(x, y, age < 0.15 ? 2.2 : 1.6, age < 0.15 ? 2.2 : 1.6); }
+  for (const [la, lo] of cells) glow(ctx, mv.X(lo), mv.Y(la), w / 5, 'rgba(255,200,80,A)', 0.18);
+  ctx.restore();
+};
+
+// GNSS interference: hex bins of degraded integrity, tracks with gaps
+PT.gnss = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const mv = mapView(o.lat ?? 56.8, o.lon ?? 21.5, o.span ?? 17, w, h);
+  mapBase(ctx, mv, { lights: 0.8, land: '#121821', sea: '#05080c', coast: '#33425a' }); const R = rng(o.seed || 5);
+  const hot = [[55.0, 20.5, 1.6], [59.3, 24.2, 1.2], [57.2, 19.0, 0.8]]; const hs = w / 16;
+  ctx.save();
+  for (let row = 0; row * hs * 0.87 < h + hs; row++) for (let col = 0; col * hs < w + hs; col++) {
+    const x = col * hs + (row % 2 ? hs / 2 : 0), y = row * hs * 0.87; const la = mv.lat(y), lo = mv.lon(x);
+    let k = 0; for (const [a, b, s] of hot) k = Math.max(k, Math.exp(-(((la - a) / s) ** 2 + ((lo - b) / (s * 1.8)) ** 2)));
+    if (k < 0.12) continue; ctx.beginPath(); for (let i = 0; i < 6; i++) { const an = Math.PI / 6 + (i * Math.PI) / 3; ctx.lineTo(x + Math.cos(an) * hs * 0.5, y + Math.sin(an) * hs * 0.5); } ctx.closePath();
+    ctx.fillStyle = `rgba(255,${Math.round(150 - k * 110)},${Math.round(60 - k * 40)},${0.12 + k * 0.5})`; ctx.fill(); ctx.strokeStyle = `rgba(255,140,90,${k * 0.5})`; ctx.stroke();
+  }
+  // airliner tracks: dashed where position integrity drops
+  ctx.lineWidth = 1.2;
+  for (let i = 0; i < 26; i++) { const y0 = R() * h, y1 = R() * h; let prevBad = null; for (let s = 0; s < 40; s++) { const t0 = s / 40, t1 = (s + 1) / 40; const x0 = t0 * w, x1 = t1 * w, ya = lerp(y0, y1, t0), yb = lerp(y0, y1, t1); const la = mv.lat(ya), lo = mv.lon(x0); let k = 0; for (const [a, b, sd] of hot) k = Math.max(k, Math.exp(-(((la - a) / sd) ** 2 + ((lo - b) / (sd * 1.8)) ** 2))); const bad = k > 0.4; ctx.strokeStyle = bad ? 'rgba(255,120,90,.0)' : 'rgba(150,205,255,.55)'; if (!bad) { ctx.beginPath(); ctx.moveTo(x0, ya); ctx.lineTo(x1, yb); ctx.stroke(); } if (bad && s % 2 === 0) { ctx.fillStyle = 'rgba(255,170,140,.7)'; ctx.fillRect(x0, ya + (R() - 0.5) * 6, 1.5, 1.5); } } }
+  ctx.restore();
+  label(ctx, 'NIC/NACp ≤ 4', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+};
+
+// helicopter school: the circuit flown again and again over the field
+PT.heli = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(11);
+  field(ctx, w, h, 2, (u, v, out) => { const n = N.fbm(u * 7, v * 7, 4), f = N(u * 22, v * 22); const g = f > 0.6 ? 1 : 0; out[0] = lerp(58, 92, n) + g * 18; out[1] = lerp(72, 98, n) + g * 22; out[2] = lerp(42, 60, n); });
+  // tree lines & roads
+  ctx.save(); ctx.fillStyle = 'rgba(25,40,22,.55)'; const R = rng(3); for (let i = 0; i < 40; i++) { ctx.beginPath(); ctx.ellipse(R() * w, R() * h, w * 0.06 * R(), h * 0.012, R() * 3, 0, TAU); ctx.fill(); } ctx.restore();
+  ctx.save(); ctx.translate(w * 0.5, h * 0.5); ctx.rotate(0.06);
+  ctx.fillStyle = '#6d6f70'; ctx.fillRect(-w * 0.36, -h * 0.025, w * 0.72, h * 0.05); ctx.save(); ctx.rotate(1.1); ctx.fillStyle = '#6a6c6d'; ctx.fillRect(-w * 0.3, -h * 0.02, w * 0.6, h * 0.04); ctx.restore();
+  ctx.strokeStyle = 'rgba(255,255,255,.7)'; ctx.setLineDash([6, 6]); ctx.beginPath(); ctx.moveTo(-w * 0.34, 0); ctx.lineTo(w * 0.34, 0); ctx.stroke(); ctx.setLineDash([]);
+  for (let i = 0; i < 12; i++) { ctx.fillStyle = '#7d7f80'; ctx.fillRect(-w * 0.3 + i * w * 0.05, h * 0.08, w * 0.035, w * 0.035); }
+  // circuit laps (oldest faint)
+  const n = o.laps ?? 14; const cw = w * 0.62, ch = h * 0.42;
+  for (let i = 0; i < n; i++) { const j = i / n; const off = (hash01(i + 1) - 0.5) * w * 0.03; ctx.strokeStyle = `rgba(155,240,150,${0.12 + j * 0.65})`; ctx.lineWidth = i === n - 1 ? 2.4 : 1.1; const r = w * 0.06; const x = -cw / 2 + off, y = -ch / 2 - h * 0.02 + off; ctx.beginPath(); ctx.roundRect(x, y, cw, ch, r); ctx.stroke(); }
+  // helicopter
+  const hx = cw / 2 - w * 0.02, hy = -ch * 0.1; ctx.fillStyle = '#E8FFE4'; ctx.beginPath(); ctx.arc(hx, hy, w / 60, 0, TAU); ctx.fill(); ctx.strokeStyle = 'rgba(232,255,228,.8)'; ctx.lineWidth = 1; ctx.beginPath(); ctx.arc(hx, hy, w / 22, 0, TAU); ctx.stroke(); ctx.beginPath(); ctx.moveTo(hx, hy); ctx.lineTo(hx, hy + w / 14); ctx.stroke();
+  ctx.restore();
+  const fs = Math.max(7, w / 44); for (const [t, x, y] of [['UPWIND', 0.5, 0.25], ['DOWNWIND', 0.5, 0.79], ['BASE', 0.12, 0.52], ['CROSSWIND', 0.88, 0.48]]) label(ctx, t, x * w, y * h, fs, 'rgba(225,255,220,.75)', 'center');
+  vignette(ctx, w, h, 0.35);
+};
+
+/* =====================================================================================
+   GROUND
+   ===================================================================================== */
+// shake map: intensity bands over the coast, epicentre, stations
+PT.shake = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const Q = GE.BIGQ; const mv = mapView(Q.lat + 0.6, Q.lon - 1.6, o.span ?? 6.5, w, h);
+  mapBase(ctx, mv, { relief: 1.1, land: '#161d26', sea: '#05080c', coast: '#5a6e88', lights: 0.6 });
+  const fw = Math.round(w / 2); const wm = cropData('water', mv, fw, Math.round(h / 2)); const strike = 0.35;
+  const mmi = (la, lo) => { const dx = (lo - Q.lon) * Math.cos(Q.lat * D2R), dy = la - Q.lat; const a = dx * Math.cos(strike) + dy * Math.sin(strike), b = -dx * Math.sin(strike) + dy * Math.cos(strike); const d = Math.hypot(a / 1.7, b) * 111; return clamp(8.2 - 2.1 * Math.log10(1 + d / 9) * 1.55, 1, 9); };
+  field(ctx, w, h, 2, (u, v, out, x, y) => { const la = mv.lat(v * h), lo = mv.lon(u * w); const I = mmi(la, lo); const band = Math.floor(I); const t = clamp((band - 1) / 7, 0, 1); const j = Math.round(t * 255) * 3; const sea = wm[(y * fw + x) * 4] / 255 > 0.5; out[0] = LUT.mmi[j]; out[1] = LUT.mmi[j + 1]; out[2] = LUT.mmi[j + 2]; out[3] = I < 4 ? 0 : (sea ? 50 : 120) + (I - 4) * 26; }, true);
+  // contour lines
+  ctx.save(); ctx.lineWidth = 1; ctx.strokeStyle = 'rgba(255,255,255,.35)';
+  for (const I of [4, 5, 6, 7]) { const d = 9 * (Math.pow(10, (8.2 - I) / (2.1 * 1.55)) - 1) / 111; ctx.beginPath(); for (let k = 0; k <= 72; k++) { const an = (k / 72) * TAU; const a = Math.cos(an) * d * 1.7, b = Math.sin(an) * d; const dx = a * Math.cos(strike) - b * Math.sin(strike), dy = a * Math.sin(strike) + b * Math.cos(strike); const x = mv.X(Q.lon + dx / Math.cos(Q.lat * D2R)), y = mv.Y(Q.lat + dy); k ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke(); }
+  ctx.restore();
+  // rupture
+  ctx.save(); ctx.strokeStyle = '#fff'; ctx.lineWidth = 2; const e = 0.45; ctx.beginPath(); ctx.moveTo(mv.X(Q.lon - Math.cos(strike) * e), mv.Y(Q.lat - Math.sin(strike) * e)); ctx.lineTo(mv.X(Q.lon + Math.cos(strike) * e), mv.Y(Q.lat + Math.sin(strike) * e)); ctx.stroke(); ctx.restore();
+  // stations
+  const R = rng(14); for (let i = 0; i < 46; i++) { const la = Q.lat + R.gauss() * 1.3 + 0.5, lo = Q.lon - 1.2 + R.gauss() * 1.2; const m = cropData('water', mv, fw, Math.round(h / 2)); const x = mv.X(lo), y = mv.Y(la); if (x < 0 || y < 0 || x >= w || y >= h) continue; if (m[(Math.floor(y / 2) * fw + Math.floor(x / 2)) * 4] > 128) continue; const I = mmi(la, lo) + R.gauss() * 0.4; const j = Math.round(clamp((I - 1) / 7, 0, 1) * 255) * 3; ctx.fillStyle = `rgb(${LUT.mmi[j]},${LUT.mmi[j + 1]},${LUT.mmi[j + 2]})`; ctx.strokeStyle = 'rgba(0,0,0,.7)'; const s = w / 70; ctx.beginPath(); ctx.moveTo(x, y - s); ctx.lineTo(x + s * 0.9, y + s * 0.6); ctx.lineTo(x - s * 0.9, y + s * 0.6); ctx.closePath(); ctx.fill(); ctx.stroke(); }
+  // epicentre star
+  const ex = mv.X(Q.lon), ey = mv.Y(Q.lat); ctx.save(); ctx.translate(ex, ey); ctx.fillStyle = '#FF3B30'; ctx.strokeStyle = '#fff'; ctx.lineWidth = 1.5; ctx.beginPath(); for (let i = 0; i < 10; i++) { const r = i % 2 ? w / 50 : w / 22; const a = -Math.PI / 2 + (i * Math.PI) / 5; ctx.lineTo(Math.cos(a) * r, Math.sin(a) * r); } ctx.closePath(); ctx.fill(); ctx.stroke(); ctx.restore();
+  for (const [t, la, lo] of [['SENDAI', 38.27, 140.87], ['FUKUSHIMA', 37.75, 140.47], ['MITO', 36.37, 140.47], ['TOKYO', 35.68, 139.69]]) { const x = mv.X(lo), y = mv.Y(la); ctx.fillStyle = '#fff'; ctx.fillRect(x - 1.5, y - 1.5, 3, 3); label(ctx, t, x - 5, y, Math.max(7, w / 48), 'rgba(235,240,248,.85)', 'right'); }
+  const lx = w * 0.05, ly = h * PT.botY; for (let i = 2; i <= 8; i++) { const j = Math.round(((i - 1) / 7) * 255) * 3; ctx.fillStyle = `rgb(${LUT.mmi[j]},${LUT.mmi[j + 1]},${LUT.mmi[j + 2]})`; ctx.fillRect(lx + (i - 2) * w * 0.05, ly, w * 0.05, Math.max(4, h / 90)); label(ctx, ['', 'I', 'II', 'III', 'IV', 'V', 'VI', 'VII', 'VIII'][i], lx + (i - 2) * w * 0.05 + w * 0.025, ly - 7, Math.max(6, w / 60), 'rgba(255,255,255,.7)', 'center'); }
+  label(ctx, 'MMI · INSTRUMENTAL INTENSITY', w * 0.05, h * PT.topY, Math.max(8, w / 42), 'rgba(255,255,255,.85)');
+};
+
+// crowd density inside and around a stadium, top-down, with an egress crush point
+PT.stadium = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 66); const N = noiseGen(66);
+  ctx.fillStyle = '#0b0e12'; ctx.fillRect(0, 0, w, h);
+  ctx.save(); ctx.fillStyle = '#12161c'; for (let i = 0; i < 70; i++) { const x = R() * w, y = R() * h; if (Math.hypot((x - w / 2) / w, (y - h / 2) / h) < 0.36) continue; ctx.fillRect(x, y, w * (0.04 + R() * 0.07), h * (0.03 + R() * 0.05)); } ctx.restore();
+  const cx = w / 2, cy = h * 0.48, RX = w * 0.36, RY = h * 0.3;
+  ctx.fillStyle = '#1b2028'; ctx.beginPath(); ctx.ellipse(cx, cy, RX * 1.08, RY * 1.08, 0, 0, TAU); ctx.fill();
+  // intensity buffer of people
+  const k = 2, fw = Math.round(w / k), fh = Math.round(h / k); const I = new Float32Array(fw * fh);
+  const splat = (x, y, s, a) => { const r = Math.ceil(s * 2.5), x0 = Math.round(x / k), y0 = Math.round(y / k); for (let j = -r; j <= r; j++) for (let i = -r; i <= r; i++) { const X = x0 + i, Y = y0 + j; if (X < 0 || Y < 0 || X >= fw || Y >= fh) continue; I[Y * fw + X] += a * Math.exp(-(i * i + j * j) / (s * s)); } };
+  for (let n = 0; n < 2600; n++) { const a = R() * TAU, t = 0.55 + R() * 0.45; splat(cx + Math.cos(a) * RX * t, cy + Math.sin(a) * RY * t, 1.6, 0.35 + 0.5 * N(Math.cos(a) * 3, Math.sin(a) * 3)); }
+  const gates = [[-0.25, 'A'], [1.2, 'B'], [Math.PI * 0.62, 'C'], [Math.PI * 1.25, 'D']];
+  for (const [ga, gl] of gates) { const gx = cx + Math.cos(ga) * RX * 1.08, gy = cy + Math.sin(ga) * RY * 1.08; const crush = gl === 'C'; for (let n = 0; n < (crush ? 900 : 260); n++) { const d = Math.pow(R(), crush ? 1.8 : 1) * w * (crush ? 0.2 : 0.3); const sp = R.gauss() * (crush ? 0.18 : 0.12); splat(gx + Math.cos(ga + sp) * d, gy + Math.sin(ga + sp) * d, 1.8, crush ? 0.6 : 0.3); } }
+  const c2 = mk(fw, fh), cx2 = c2.getContext('2d'); const id = cx2.createImageData(fw, fh);
+  for (let i = 0; i < fw * fh; i++) { const v = clamp(I[i] / 3.2, 0, 1); const j = Math.round(v * 255) * 3; id.data[i * 4] = LUT.inferno[j]; id.data[i * 4 + 1] = LUT.inferno[j + 1]; id.data[i * 4 + 2] = LUT.inferno[j + 2]; id.data[i * 4 + 3] = v < 0.04 ? 0 : clamp(v * 900, 0, 235); }
+  cx2.putImageData(id, 0, 0); ctx.save(); ctx.imageSmoothingQuality = 'high'; ctx.drawImage(c2, 0, 0, w, h); ctx.restore();
+  // pitch
+  ctx.save(); ctx.fillStyle = '#16301e'; ctx.fillRect(cx - RX * 0.42, cy - RY * 0.42, RX * 0.84, RY * 0.84); ctx.strokeStyle = 'rgba(220,255,220,.35)'; ctx.lineWidth = 1; ctx.strokeRect(cx - RX * 0.42, cy - RY * 0.42, RX * 0.84, RY * 0.84); ctx.beginPath(); ctx.moveTo(cx, cy - RY * 0.42); ctx.lineTo(cx, cy + RY * 0.42); ctx.stroke(); ctx.beginPath(); ctx.arc(cx, cy, RY * 0.12, 0, TAU); ctx.stroke(); ctx.restore();
+  for (const [ga, gl] of gates) { const gx = cx + Math.cos(ga) * RX * 1.16, gy = cy + Math.sin(ga) * RY * 1.16; label(ctx, 'GATE ' + gl, gx, gy, Math.max(7, w / 46), gl === 'C' ? '#fff' : 'rgba(230,236,245,.6)', 'center'); }
+  const ga = gates[2][0]; const hx = cx + Math.cos(ga) * RX * 1.3, hy = cy + Math.sin(ga) * RY * 1.3; ctx.save(); ctx.strokeStyle = '#FF3B30'; ctx.lineWidth = 2; ctx.beginPath(); ctx.arc(hx, hy, w / 13, 0, TAU); ctx.stroke(); ctx.restore();
+  label(ctx, '4.6 P/M²', hx, hy + w / 9, Math.max(9, w / 30), '#FF6B61', 'center');
+  label(ctx, 'CROWD DENSITY · P/M²', w * 0.05, h * PT.topY, Math.max(8, w / 42), 'rgba(255,255,255,.85)');
+};
+
+/* ---------- CCTV-style scenes (animated: static base cached, dynamic layer per frame) ---------- */
+const SCN = (PT.scenes = {});
+function cctvOSD(ctx, w, h, t, o) {
+  const fs = Math.max(8, Math.round(w / 34)); const y0 = h * (o.osdY ?? PT.osdY), y1 = h * (o.osdB ?? PT.osdB);
+  osd(ctx, o.cam || 'CAM 0412', w * 0.045, y0, fs); osd(ctx, PT.stamp(o.at ?? Date.now()), w * 0.955, y0, fs, 'right');
+  if (o.place) osd(ctx, o.place, w * 0.045, y1 - fs, fs * 0.9);
+  if (o.rec !== false && Math.floor(t * 1.2) % 2 === 0) { ctx.fillStyle = '#FF3B30'; ctx.beginPath(); ctx.arc(w * 0.955 - fs * 0.3, y1 - fs * 0.5, fs * 0.32, 0, TAU); ctx.fill(); osd(ctx, 'REC', w * 0.955 - fs * 0.9, y1 - fs, fs * 0.9, 'right'); }
+}
+PT.osdY = 0.115; PT.osdB = 0.87; PT.topY = 0.125; PT.botY = 0.86;
+PT.cctvOSD = cctvOSD;
+
+// harbour at night: gantry cranes, a lit ship, fog, reflections, rain before a typhoon
+SCN.harbour = {
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const R = rng(o.seed || 8); const N = noiseGen(8); const hz = h * 0.56;
+    const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#0b0d12'); sky.addColorStop(0.7, '#2a2522'); sky.addColorStop(1, '#5a4430'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz);
+    // far shore: city lights band
+    ctx.fillStyle = '#121010'; ctx.fillRect(0, hz - h * 0.035, w, h * 0.04);
+    for (let i = 0; i < 260; i++) { const x = R() * w, y = hz - R() * h * 0.05; ctx.fillStyle = `rgba(255,${170 + R() * 70},${90 + R() * 80},${0.4 + R() * 0.6})`; ctx.fillRect(x, y, 1.3, 1.3); }
+    for (let i = 0; i < 9; i++) { const x = R() * w, bw = w * (0.02 + R() * 0.03), bh = h * (0.05 + R() * 0.12); ctx.fillStyle = '#0d0c0d'; ctx.fillRect(x, hz - bh, bw, bh); for (let k = 0; k < 18; k++) { if (R() < 0.5) continue; ctx.fillStyle = `rgba(255,220,160,${0.3 + R() * 0.5})`; ctx.fillRect(x + R() * bw, hz - R() * bh, 1.4, 1.4); } }
+    // gantry cranes
+    for (let i = 0; i < 4; i++) {
+      const x = w * (0.08 + i * 0.2) + R() * w * 0.04, s = h * (0.34 - i * 0.03), top = hz - s; ctx.strokeStyle = '#08080a'; ctx.fillStyle = '#08080a'; ctx.lineWidth = Math.max(2, w / 160);
+      ctx.beginPath(); ctx.moveTo(x, hz + h * 0.04); ctx.lineTo(x + w * 0.012, top); ctx.moveTo(x + w * 0.07, hz + h * 0.04); ctx.lineTo(x + w * 0.058, top); ctx.stroke();
+      ctx.fillRect(x - w * 0.09, top - h * 0.012, w * 0.26, h * 0.016); ctx.fillRect(x + w * 0.01, top - h * 0.06, w * 0.05, h * 0.05);
+      ctx.lineWidth = 1; for (let k = 0; k < 8; k++) { ctx.beginPath(); ctx.moveTo(x + w * 0.012 * (k / 8) + 1, hz + h * 0.04 - (k * s) / 8); ctx.lineTo(x + w * 0.07 - w * 0.012 * ((k + 1) / 8), hz + h * 0.04 - ((k + 1) * s) / 8); ctx.stroke(); }
+      for (let k = 0; k < 6; k++) { ctx.fillStyle = 'rgba(255,236,200,.85)'; ctx.fillRect(x - w * 0.08 + k * w * 0.045, top - h * 0.002, 2, 2); }
+    }
+    // container ship
+    const sy = hz + h * 0.02; ctx.fillStyle = '#0d0f12'; ctx.beginPath(); ctx.moveTo(w * 0.12, sy); ctx.lineTo(w * 0.92, sy); ctx.lineTo(w * 0.88, sy + h * 0.07); ctx.lineTo(w * 0.15, sy + h * 0.07); ctx.closePath(); ctx.fill();
+    const cols = ['#3b2420', '#1f2d3b', '#2b3326', '#3a3324', '#2a2a30', '#3a1f2a'];
+    for (let i = 0; i < 46; i++) for (let j = 0; j < 4; j++) { if (R() < 0.12) continue; ctx.fillStyle = cols[R.int(cols.length)]; ctx.fillRect(w * 0.18 + i * w * 0.0145, sy - (j + 1) * h * 0.014, w * 0.013, h * 0.012); }
+    ctx.fillStyle = '#16181c'; ctx.fillRect(w * 0.8, sy - h * 0.1, w * 0.07, h * 0.1); for (let k = 0; k < 14; k++) { ctx.fillStyle = 'rgba(255,230,180,.85)'; ctx.fillRect(w * 0.805 + (k % 7) * w * 0.009, sy - h * 0.09 + Math.floor(k / 7) * h * 0.02, 2, 2); }
+    // water
+    const wg = ctx.createLinearGradient(0, hz, 0, h); wg.addColorStop(0, '#15120f'); wg.addColorStop(1, '#050506'); ctx.fillStyle = wg; ctx.fillRect(0, sy + h * 0.07, w, h);
+    // quay & lamps in the foreground
+    ctx.fillStyle = '#0a0a0b'; ctx.beginPath(); ctx.moveTo(0, h * 0.86); ctx.lineTo(w, h * 0.8); ctx.lineTo(w, h); ctx.lineTo(0, h); ctx.fill();
+    for (let i = 0; i < 4; i++) { const x = w * (0.1 + i * 0.28), y = h * (0.86 - i * 0.015); ctx.fillStyle = '#060606'; ctx.fillRect(x, y - h * 0.16, 2, h * 0.16); }
+    // fog
+    for (let y = 0; y < h; y += 4) { const f = Math.exp(-(((y - hz) / (h * 0.12)) ** 2)) * 0.18; ctx.fillStyle = `rgba(150,130,110,${f})`; ctx.fillRect(0, y, w, 4); }
+    c.lights = []; for (let i = 0; i < 4; i++) c.lights.push([w * (0.1 + i * 0.28) + 1, h * (0.86 - i * 0.015) - h * 0.16]);
+    c.hz = hz; c.sy = sy + h * 0.07; return c;
+  },
+  frame(ctx, w, h, t, o, B) {
+    ctx.drawImage(B, 0, 0); const N = this._n || (this._n = noiseGen(4)); const R = rng(Math.floor(t * 8));
+    ctx.save(); ctx.globalCompositeOperation = 'lighter';
+    // reflections shimmer
+    for (let y = B.sy; y < h * 0.86; y += 2) { const f = (y - B.sy) / (h * 0.86 - B.sy); for (const [lx, a] of [[0.83, 0.35], [0.3, 0.12], [0.55, 0.1], [0.12, 0.08]]) { const j = (N(y * 0.15, t * 2 + lx * 9) - 0.5) * 16 * (0.5 + f); ctx.fillStyle = `rgba(255,170,90,${a * (1 - f * 0.7)})`; ctx.fillRect(lx * w + j - 3 - f * 8, y, 6 + f * 16, 1.3); } }
+    for (const [x, y] of B.lights) glow(ctx, x, y, w * 0.06, 'rgba(255,170,80,A)', 0.55);
+    for (let i = 0; i < 4; i++) { const on = Math.sin(t * 3 + i * 1.7) > 0; if (!on) continue; glow(ctx, w * (0.1 + i * 0.2) + w * 0.035, B.hz - h * (0.34 - i * 0.03) - h * 0.065, w * 0.025, 'rgba(255,40,30,A)', 0.9); }
+    ctx.restore();
+    // light rain
+    ctx.save(); ctx.strokeStyle = 'rgba(200,200,210,.18)'; ctx.lineWidth = 1; ctx.beginPath(); for (let i = 0; i < 90; i++) { const x = (R() * w + t * 60) % w, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - 3, y + h * 0.03); } ctx.stroke(); ctx.restore();
+    scan(ctx, w, h, 0.06); vignette(ctx, w, h, 0.5); grain(ctx, w, h, 0.12);
+    cctvOSD(ctx, w, h, t, o);
+  },
+};
+
+// scramble crossing at night in the rain: umbrellas from a high camera, neon on wet asphalt
+SCN.crossing = {
+  // high camera over a scramble: ground plane in perspective, crowds waiting and crossing in the rain
+  map(w, h) { const top = h * 0.25, zF = 2.3, zN = 1; return (u, v) => { const z = lerp(zF, zN, v); const y = top + (h - top) * ((1 / z - 1 / zF) / (1 / zN - 1 / zF)); return [w / 2 + ((u - 0.5) * w * 1.3) / z, y, 1 / z]; }; },
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const R = rng(o.seed || 31); const M = this.map(w, h); const top = h * 0.25;
+    // facades, video screens and signs (abstract, no marks)
+    const fg = ctx.createLinearGradient(0, 0, 0, top); fg.addColorStop(0, '#060609'); fg.addColorStop(1, '#141218'); ctx.fillStyle = fg; ctx.fillRect(0, 0, w, top + 2);
+    for (let i = 0; i < 7; i++) { const x = (i / 7) * w + R() * 10, bw = w / 7 - 4; ctx.fillStyle = `rgb(${12 + R() * 10},${12 + R() * 8},${16 + R() * 10})`; ctx.fillRect(x, R() * top * 0.2, bw, top); for (let k = 0; k < 40; k++) { if (R() < 0.5) continue; ctx.fillStyle = `rgba(255,${210 + R() * 40},${160 + R() * 70},${0.25 + R() * 0.4})`; ctx.fillRect(x + R() * bw, R() * top, 2, 1.5); } }
+    const neon = ['255,70,130', '70,200,255', '255,190,70', '170,110,255', '90,255,190'];
+    const screens = []; for (let i = 0; i < 4; i++) { const x = w * (0.05 + i * 0.25) + R() * 10, y = top * (0.14 + R() * 0.3), sw = w * (0.09 + R() * 0.05), sh = top * (0.22 + R() * 0.16); screens.push([x, y, sw, sh, neon[R.int(5)], neon[R.int(5)]]); }
+    for (const [x, y, sw, sh, a, b] of screens) { ctx.fillStyle = '#050507'; ctx.fillRect(x - 3, y - 3, sw + 6, sh + 6); const g = ctx.createLinearGradient(x, y, x + sw, y + sh); g.addColorStop(0, `rgba(${a},.75)`); g.addColorStop(0.6, `rgba(${b},.55)`); g.addColorStop(1, `rgba(${a},.35)`); ctx.fillStyle = g; ctx.fillRect(x, y, sw, sh); ctx.fillStyle = 'rgba(255,255,255,.35)'; for (let k = 0; k < 3; k++) ctx.fillRect(x + sw * 0.1, y + sh * (0.55 + k * 0.12), sw * (0.3 + R() * 0.5), Math.max(1, sh * 0.05)); ctx.fillStyle = 'rgba(0,0,0,.25)'; for (let yy = y; yy < y + sh; yy += 2) ctx.fillRect(x, yy, sw, 1); ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, x + sw / 2, y + sh / 2, sw * 0.8, `rgba(${a},A)`, 0.18); ctx.restore(); }
+    for (let i = 0; i < 9; i++) { const x = R() * w, y = R() * top * 0.7; ctx.fillStyle = `rgba(${neon[R.int(5)]},.6)`; ctx.fillRect(x, y, w * 0.008, top * (0.15 + R() * 0.25)); }
+    // asphalt
+    ctx.fillStyle = '#121117'; ctx.beginPath(); const q = [M(0, 0), M(1, 0), M(1, 1), M(0, 1)]; ctx.moveTo(-w, top); ctx.lineTo(w * 2, top); ctx.lineTo(w * 2, h); ctx.lineTo(-w, h); ctx.fill();
+    ctx.save(); ctx.globalCompositeOperation = 'lighter';
+    for (const [x, y, sw, sh, a] of screens) { const g = ctx.createLinearGradient(0, top, 0, h); g.addColorStop(0, `rgba(${a},.30)`); g.addColorStop(0.6, `rgba(${a},.05)`); g.addColorStop(1, `rgba(${a},0)`); ctx.fillStyle = g; for (let k = 0; k < 6; k++) ctx.fillRect(x + sw * (0.1 + k * 0.15) + R.gauss() * 3, top, sw * 0.08, h - top); }
+    ctx.restore();
+    // crosswalk stripes as quads on the ground plane
+    const zebra = (u1, v1, u2, v2, n, wd) => { const du = u2 - u1, dv = v2 - v1, L = Math.hypot(du, dv); const nu = -dv / L * wd, nv = du / L * wd; ctx.fillStyle = 'rgba(205,208,218,.26)'; for (let i = 0; i < n; i++) { const t0 = (i + 0.15) / n, t1 = (i + 0.62) / n; const a = M(u1 + du * t0 + nu, v1 + dv * t0 + nv), b = M(u1 + du * t1 + nu, v1 + dv * t1 + nv), cc = M(u1 + du * t1 - nu, v1 + dv * t1 - nv), d = M(u1 + du * t0 - nu, v1 + dv * t0 - nv); poly(ctx, [a, b, cc, d], true); ctx.fill(); } };
+    zebra(0.1, 0.14, 0.9, 0.14, 26, 0.06); zebra(0.08, 0.9, 0.92, 0.9, 26, 0.07); zebra(0.08, 0.2, 0.08, 0.84, 20, 0.055); zebra(0.92, 0.2, 0.92, 0.84, 20, 0.055); zebra(0.17, 0.22, 0.83, 0.82, 30, 0.028); zebra(0.83, 0.22, 0.17, 0.82, 30, 0.028);
+    // kerbs/corner pavements
+    ctx.fillStyle = '#1d1c22'; for (const [u0, v0] of [[-0.3, -0.2], [1.0, -0.2], [-0.3, 1.0], [1.0, 1.0]]) { poly(ctx, [M(u0, v0), M(u0 + 0.3, v0), M(u0 + 0.3, v0 + 0.2), M(u0, v0 + 0.2)], true); ctx.fill(); }
+    // vehicles waiting, lights on
+    for (const [u, v, d] of [[-0.05, 0.4, 1], [-0.05, 0.55, 1], [-0.05, 0.7, 1], [1.05, 0.35, -1], [1.05, 0.5, -1], [0.35, -0.05, 0], [0.55, 1.08, 0]]) { const [x, y, s] = M(u, v); ctx.fillStyle = '#18181d'; ctx.fillRect(x - 22 * s, y - 9 * s, 44 * s, 18 * s); ctx.save(); ctx.globalCompositeOperation = 'lighter'; if (d >= 0) { glow(ctx, x + 22 * s, y - 5 * s, 26 * s, 'rgba(255,248,225,A)', 0.8); glow(ctx, x + 22 * s, y + 5 * s, 26 * s, 'rgba(255,248,225,A)', 0.8); } else { glow(ctx, x + 22 * s, y, 18 * s, 'rgba(255,40,40,A)', 0.7); } ctx.restore(); }
+    // people
+    const P = []; const corners = [[0.06, 0.08], [0.94, 0.08], [0.06, 0.94], [0.94, 0.94]]; const cols = ['226,60,72', '34,44,64', '236,236,242', '56,134,228', '248,188,44', '26,26,32', '118,196,124', '240,120,170', '40,40,46', '190,190,200'];
+    for (let i = 0; i < 520; i++) { const wait = i < 170; const ci = i % 4; const a = corners[ci], b = wait ? a : corners[[3, 2, 1, 0, 1, 0, 3, 2][(i >> 2) % 8] ?? 3 - ci]; const umb = R() < 0.72; P.push({ a, b, wait, off: R(), sp: 0.035 + R() * 0.03, jx: R.gauss() * (wait ? 0.035 : 0.03), jy: R.gauss() * (wait ? 0.03 : 0.022), umb, col: cols[R.int(cols.length)], s: 0.8 + R() * 0.45 }); }
+    c.P = P; c.M = M; return c;
+  },
+  frame(ctx, w, h, t, o, B) {
+    ctx.drawImage(B, 0, 0); const M = B.M; const list = [];
+    for (const p of B.P) { const u = p.wait ? 0 : (p.off + t * p.sp) % 1; const [x, y, s] = M(lerp(p.a[0], p.b[0], u) + p.jx, lerp(p.a[1], p.b[1], u) + p.jy); list.push([y, x, s * (w / 46) * p.s, p]); }
+    list.sort((a, b) => a[0] - b[0]);
+    for (const [y, x, s, p] of list) { if (p.umb) { ctx.fillStyle = `rgba(${p.col},.95)`; ctx.beginPath(); ctx.ellipse(x, y, s * 1.1, s * 0.82, 0, 0, TAU); ctx.fill(); ctx.fillStyle = 'rgba(255,255,255,.16)'; ctx.beginPath(); ctx.ellipse(x - s * 0.25, y - s * 0.22, s * 0.5, s * 0.32, 0, 0, TAU); ctx.fill(); } else { ctx.fillStyle = '#17161b'; ctx.beginPath(); ctx.ellipse(x, y + s * 0.2, s * 0.55, s * 0.4, 0, 0, TAU); ctx.fill(); ctx.fillStyle = '#2b2622'; ctx.beginPath(); ctx.arc(x, y - s * 0.1, s * 0.33, 0, TAU); ctx.fill(); } }
+    ctx.save(); ctx.strokeStyle = 'rgba(210,215,230,.15)'; ctx.lineWidth = 1; const R = rng(Math.floor(t * 10)); ctx.beginPath(); for (let i = 0; i < 160; i++) { const x = R() * w, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - 2, y + h * 0.025); } ctx.stroke(); ctx.restore();
+    vignette(ctx, w, h, 0.45); scan(ctx, w, h, 0.05); grain(ctx, w, h, 0.1);
+    if (!o.noOSD) cctvOSD(ctx, w, h, t, o);
+  },
+};
+
+// waterfront in a storm at night: looking along the wall, swells breaking over it, sodium lamps on a
+// flooded road, a town behind; handheld when a person films it
+SCN.seawall = {
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const R = rng(o.seed || 51); const N = noiseGen(o.seed || 51); const hz = h * 0.4;
+    const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#06070a'); sky.addColorStop(1, o.skyline ? '#2a2129' : '#191a20'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz + 2);
+    field(ctx, w, hz, 3, (u, v, out) => { const n = N.fbm(u * 2.5 + v, v * 4, 5); out[0] = 34 + n * 40; out[1] = 32 + n * 38; out[2] = 38 + n * 40; out[3] = 150 * smooth(0.35, 0.8, n); });
+    // town / skyline on the right half, beyond the road
+    const town = (x0, x1, tall) => { for (let i = 0; i < (tall ? 26 : 34); i++) { const x = lerp(x0, x1, R()), bw = w * (tall ? 0.02 + R() * 0.035 : 0.025 + R() * 0.04), bh = h * (tall ? 0.04 + Math.pow(R(), 2) * 0.24 : 0.02 + R() * 0.05); ctx.fillStyle = '#0b0a0d'; ctx.fillRect(x, hz - bh, bw, bh + 2); const n = Math.floor(bw * bh * 0.012); for (let k = 0; k < n; k++) { if (R() < 0.5) continue; ctx.fillStyle = `rgba(255,${190 + R() * 60},${120 + R() * 90},${0.3 + R() * 0.6})`; ctx.fillRect(x + R() * bw, hz - R() * bh, 1.4, 1.4); } } };
+    town(w * 0.5, w * 1.0, !!o.skyline);
+    ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, w * 0.8, hz, w * 0.5, 'rgba(255,140,60,A)', o.skyline ? 0.22 : 0.12); ctx.restore();
+    // sea on the left: dark swells with streaked foam, perspective-compressed toward the horizon
+    field(ctx, w, h, 2, (u, v, out) => { const y = v * h; if (y < hz) { out[3] = 0; return; } const d = (y - hz) / (h - hz); const z = 1 / (0.05 + d); const n = N.fbm(u * 3 * z * 0.25 + 3, d * 9 + z * 0.15, 5); const sw = Math.sin(z * 1.6 + n * 4); const crest = smooth(0.7, 0.98, sw) * smooth(0.45, 0.7, n); const foam = smooth(0.68, 0.82, N(u * 30 * z * 0.1, d * 60)) * 0.35 * smooth(0.5, 0.75, n);
+      out[0] = 10 + n * 22 + (crest + foam) * 170; out[1] = 13 + n * 25 + (crest + foam) * 172; out[2] = 18 + n * 28 + (crest + foam) * 178; out[3] = 255; });
+    // the wall: a parapet running from bottom-left toward the horizon; road + puddles on its right
+    const vp = [w * 0.56, hz + h * 0.005]; const L0 = [w * -0.02, h * 1.0], L1 = [w * 0.22, h * 1.0];
+    ctx.fillStyle = '#1e1d1f'; poly(ctx, [L0, vp, [vp[0] + 2, vp[1]], L1], true); ctx.fill(); // wall top
+    const road = [[w * 0.22, h], [vp[0] + 2, vp[1]], [w * 0.9, vp[1] + h * 0.02], [w * 1.2, h]]; const rg = ctx.createLinearGradient(0, hz, 0, h); rg.addColorStop(0, '#141316'); rg.addColorStop(1, '#0a0a0b'); ctx.fillStyle = rg; poly(ctx, road, true); ctx.fill();
+    ctx.strokeStyle = 'rgba(200,190,170,.18)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(L1[0], L1[1]); ctx.lineTo(vp[0] + 2, vp[1]); ctx.stroke();
+    // lamps along the road edge
+    const lamps = []; for (let i = 0; i < 7; i++) { const f = Math.pow(i / 7, 0.8); const bx = lerp(w * 0.5, vp[0] + w * 0.02, f), by = lerp(h * 1.0, vp[1] + h * 0.004, f); const lh = lerp(h * 0.5, h * 0.02, f); ctx.fillStyle = '#050506'; ctx.fillRect(bx, by - lh, Math.max(1.2, 6 * (1 - f)), lh); ctx.fillRect(bx - lh * 0.12, by - lh, lh * 0.14, Math.max(1, 4 * (1 - f))); lamps.push([bx - lh * 0.1, by - lh + 3, 1 - f, by]); }
+    if (o.palm) { ctx.save(); ctx.translate(w * 0.9, h * 0.98); ctx.strokeStyle = '#040404'; ctx.lineWidth = w / 45; ctx.beginPath(); ctx.moveTo(0, 0); ctx.quadraticCurveTo(-w * 0.02, -h * 0.3, -w * 0.12, -h * 0.5); ctx.stroke(); ctx.lineWidth = w / 160; for (let k = 0; k < 9; k++) { const a = -2.6 + k * 0.28; ctx.beginPath(); ctx.moveTo(-w * 0.12, -h * 0.5); ctx.quadraticCurveTo(-w * 0.12 + Math.cos(a) * w * 0.08, -h * 0.5 + Math.sin(a) * h * 0.04, -w * 0.12 + Math.cos(a) * w * 0.17 - w * 0.05, -h * 0.5 + Math.sin(a) * h * 0.06 + h * 0.06); ctx.stroke(); } ctx.restore(); }
+    c.lamps = lamps; c.hz = hz; c.vp = vp; return c;
+  },
+  frame(ctx, w, h, t, o, B) {
+    const shake = o.handheld ? [Math.sin(t * 7.1) * w * 0.004 + Math.sin(t * 2.3) * w * 0.006, Math.cos(t * 6.3) * h * 0.003] : [0, 0];
+    ctx.save(); ctx.translate(shake[0], shake[1]); ctx.drawImage(B, -4, -4, w + 8, h + 8);
+    ctx.save(); ctx.globalCompositeOperation = 'lighter';
+    for (const [x, y, f, gy] of B.lamps) { glow(ctx, x, y, w * 0.14 * (0.3 + f), 'rgba(255,150,50,A)', 0.55 + 0.1 * Math.sin(t * 13 + x)); const g = ctx.createLinearGradient(0, gy - h * 0.01, 0, gy + h * 0.16 * f); g.addColorStop(0, 'rgba(255,150,60,.0)'); g.addColorStop(0.2, 'rgba(255,150,60,.3)'); g.addColorStop(1, 'rgba(255,150,60,0)'); ctx.fillStyle = g; ctx.fillRect(x - w * 0.012 * (0.5 + f), gy - h * 0.01, w * 0.024 * (0.5 + f) + 1.5, h * 0.17 * f); }
+    // breaking swells: spray sheets rise off the wall and blow right with the wind
+    const R0 = rng(7); for (let b = 0; b < 3; b++) { const per = 3.6 + b * 1.3; const tt = t + b * 1.7; const ph = (tt % per) / per; if (ph > 0.6) continue; const k = Math.sin((ph / 0.6) * Math.PI); const f = [0.18, 0.42, 0.68][b]; const bx = lerp(w * 0.08, B.vp[0], f), by = lerp(h * 0.98, B.vp[1], f); const sz = (1 - f * 0.85) * h * 0.55; const R = rng(b * 97 + Math.floor(tt / per));
+      for (let i = 0; i < 90; i++) { const up = Math.pow(R(), 0.7) * sz * k, side = (R() - 0.35) * sz * 0.35 + up * 0.6 * ph; const x = bx + side, y = by - up; const r = (0.002 + R() * 0.007) * w * (1 - f * 0.6) * (0.6 + k); ctx.fillStyle = `rgba(210,218,230,${(0.04 + R() * 0.1) * k})`; ctx.beginPath(); ctx.arc(x, y, r, 0, TAU); ctx.fill(); }
+      ctx.strokeStyle = `rgba(220,226,236,${0.08 * k})`; ctx.lineWidth = Math.max(1, w / 400); ctx.beginPath(); for (let i = 0; i < 40; i++) { const up = R() * sz * k; const x = bx + (R() - 0.3) * sz * 0.3, y = by - up * 0.3; ctx.moveTo(x, y); ctx.lineTo(x + sz * 0.12 * ph + R() * 6, y - up * 0.7); } ctx.stroke();
+      const g = ctx.createRadialGradient(bx + sz * 0.25 * ph, by - sz * 0.35 * k, 0, bx + sz * 0.25 * ph, by - sz * 0.35 * k, sz * 0.55); g.addColorStop(0, `rgba(190,198,212,${0.13 * k})`); g.addColorStop(1, 'rgba(190,198,212,0)'); ctx.fillStyle = g; ctx.fillRect(bx - sz, by - sz * 1.2, sz * 2.2, sz * 1.4); }
+    ctx.restore();
+    // rain, wind-driven, brighter near the lamps
+    const R = rng(Math.floor(t * 24)); ctx.lineWidth = 1; ctx.strokeStyle = 'rgba(205,212,228,.26)'; ctx.beginPath(); for (let i = 0; i < 320; i++) { const x = R() * w * 1.25, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - w * 0.035, y + h * 0.05); } ctx.stroke();
+    ctx.strokeStyle = 'rgba(255,190,120,.35)'; ctx.beginPath(); for (const [x, y, f] of B.lamps) for (let i = 0; i < 10 * f; i++) { const xx = x + (R() - 0.5) * w * 0.2 * f, yy = y + (R() - 0.3) * h * 0.2 * f; ctx.moveTo(xx, yy); ctx.lineTo(xx - w * 0.02, yy + h * 0.03); } ctx.stroke();
+    ctx.restore();
+    vignette(ctx, w, h, 0.55); grain(ctx, w, h, 0.12);
+    if (!o.noOSD) cctvOSD(ctx, w, h, t, o);
+  },
+};
+
+// a quiet volcano webcam by day: ash column over the bay
+SCN.volcano = {
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const N = noiseGen(12); const R = rng(12); const hz = h * 0.66;
+    const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#6f8fb0'); sky.addColorStop(1, '#c9cfd2'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz);
+    // ash plume
+    const vx = w * 0.46, vy = hz - h * 0.3;
+    field(ctx, w, h, 2, (u, v, out) => { const x = u * w - vx, y = v * h - vy; if (y > 4) { out[3] = 0; return; } const up = -y; const drift = up * 0.55; const wd = 10 + up * 0.32; const n = N.fbm((x - drift) / 40, up / 40, 5); const d = Math.exp(-(((x - drift) / wd) ** 2) * (1.2 - n)) * smooth(0, 20, up) * (0.4 + 0.9 * n) * Math.exp(-up / (h * 1.2)); const a = clamp(d * 1.3, 0, 0.95); const sh = 0.6 + (x - drift) / wd * 0.15; out[0] = (120 + n * 70) * sh; out[1] = (108 + n * 62) * sh; out[2] = (98 + n * 58) * sh; out[3] = a * 255; });
+    // cone
+    const prof = (x) => { const d = Math.abs(x - vx) / w; return vy + (d < 0.035 ? (0.035 - d) * h * 0.25 : 0) + Math.pow(d, 1.35) * h * 0.95 + N(x / 22, 0) * 5; };
+    field(ctx, w, h, 1.5, (u, v, out) => { const x = u * w, y = v * h; const top = prof(x); if (y < top || y > hz + 2) { out[3] = 0; return; } const d = (x - vx) / w; const n = N.fbm(u * 14, v * 6, 4); const gul = Math.pow(Math.abs(Math.sin(d * 60 + n * 3)), 6); const shade = 0.75 + d * 1.1 - gul * 0.25; const veg = smooth(0.08, 0.22, (y - top) / h) * smooth(0.4, 0.7, n); out[0] = (78 + n * 30) * shade - veg * 20; out[1] = (72 + n * 26) * shade + veg * 6; out[2] = (66 + n * 22) * shade - veg * 10; out[3] = 255; });
+    // bay
+    const wg = ctx.createLinearGradient(0, hz, 0, h); wg.addColorStop(0, '#7f9aa8'); wg.addColorStop(1, '#3d5664'); ctx.fillStyle = wg; ctx.fillRect(0, hz, w, h - hz);
+    for (let y = hz; y < h; y += 2) { ctx.fillStyle = `rgba(255,255,255,${0.04 + R() * 0.05})`; ctx.fillRect(R() * w, y, w * 0.2 * R(), 1); }
+    // town on the near shore
+    ctx.fillStyle = '#2f3438'; ctx.fillRect(0, h * 0.86, w, h * 0.14); for (let i = 0; i < 60; i++) { const x = R() * w, bw = w * (0.02 + R() * 0.04), bh = h * (0.02 + R() * 0.06); ctx.fillStyle = ['#d8d4cc', '#b9b4aa', '#8e8a84', '#6c6a68'][R.int(4)]; ctx.fillRect(x, h * 0.88 - bh, bw, bh); }
+    return c;
+  },
+  frame(ctx, w, h, t, o, B) { ctx.drawImage(B, 0, 0); vignette(ctx, w, h, 0.25); grain(ctx, w, h, 0.07); if (!o.noOSD) cctvOSD(ctx, w, h, t, o); },
+};
+
+/* =====================================================================================
+   INSIDE — what a person saw
+   ===================================================================================== */
+PT.aurora = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 61); const N = noiseGen(61); const hz = h * 0.66;
+  const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#02030a'); sky.addColorStop(1, '#0b1a22'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, h);
+  for (let i = 0; i < 500; i++) { ctx.fillStyle = `rgba(255,255,255,${R() * 0.8})`; ctx.fillRect(R() * w, R() * hz, 1, 1); }
+  // curtains (per-pixel: base line, height and ray striation per column)
+  const curtains = [[0.42, 0.06, 1.3, [170, 80, 255]], [0.55, 0.04, 4.2, [200, 90, 255]]];
+  field(ctx, w, h, 3, (u, v, out) => { let r = 0, g = 0, b = 0; const y = v * h; for (const [yb, amp, sd, top] of curtains) { const base = h * yb + Math.sin(u * 5 + sd) * amp * h + N(u * 6, sd) * amp * h * 1.4; const ht = h * (0.18 + 0.28 * N.fbm(u * 9 + sd, sd, 3)); const f = (base - y) / ht; if (f < -0.03 || f > 1) continue; const ray = 0.35 + 0.65 * Math.pow(N(u * 70, sd * 3), 2); const low = f < 0 ? smooth(-0.03, 0, f) : 1; const gk = Math.exp(-f * 3.2) * low * ray, pk = smooth(0.25, 0.9, f) * (1 - f) * ray * 0.6; r += gk * 60 + pk * top[0]; g += gk * 255 + pk * top[1] * 0.3; b += gk * 140 + pk * top[2]; } out[0] = r * 0.7; out[1] = g * 0.7; out[2] = b * 0.7; out[3] = 255; }, true, 'lighter');
+  // mountains + fjord reflection
+  ctx.fillStyle = '#05070a'; ctx.beginPath(); ctx.moveTo(0, hz); for (let x = 0; x <= w; x += 3) ctx.lineTo(x, hz - h * 0.05 - N.ridge(x / w * 3, 2, 4) * h * 0.16); ctx.lineTo(w, hz); ctx.fill();
+  const img = ctx.getImageData(0, 0, w, Math.floor(hz)); const ref = mk(w, Math.floor(hz)); ref.getContext('2d').putImageData(img, 0, 0);
+  ctx.save(); ctx.translate(0, hz * 2); ctx.scale(1, -1); ctx.globalAlpha = 0.45; for (let y = 0; y < hz; y += 3) { const j = Math.sin(y * 0.4) * 2; ctx.drawImage(ref, 0, y, w, 3, j, y, w, 3); } ctx.restore();
+  ctx.fillStyle = 'rgba(2,4,8,.35)'; ctx.fillRect(0, hz, w, h - hz);
+  ctx.fillStyle = '#020305'; ctx.fillRect(0, h * 0.9, w, h * 0.1); for (let i = 0; i < 26; i++) { const x = R() * w, th = h * (0.06 + R() * 0.1); ctx.beginPath(); ctx.moveTo(x, h * 0.9 - th); ctx.lineTo(x - th * 0.22, h * 0.91); ctx.lineTo(x + th * 0.22, h * 0.91); ctx.fill(); }
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, w * 0.7, h * 0.885, w * 0.05, 'rgba(255,190,110,A)', 0.8); ctx.restore();
+  vignette(ctx, w, h, 0.45); grain(ctx, w, h, 0.12);
+};
+
+// a hillside on fire, from the road
+PT.firewit = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 71); const N = noiseGen(71);
+  const sky = ctx.createLinearGradient(0, 0, 0, h * 0.7); sky.addColorStop(0, '#07060a'); sky.addColorStop(0.7, '#3a1a10'); sky.addColorStop(1, '#8a3a12'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, h);
+  // smoke lit from below
+  field(ctx, w, h * 0.7, 3, (u, v, out) => { const n = N.fbm(u * 3 + 0.5 * v, v * 4, 5); const lit = smooth(0.2, 0.95, v); out[0] = 40 + n * 90 * lit + 60 * lit; out[1] = 25 + n * 45 * lit; out[2] = 20 + n * 25 * lit; out[3] = 255 * smooth(0.35, 0.75, n) * 0.85; });
+  const ridge = (x) => h * 0.52 - N.fbm(x / w * 2.4, 3, 4) * h * 0.22 + (x / w) * h * 0.06;
+  ctx.fillStyle = '#060404'; ctx.beginPath(); ctx.moveTo(0, h); for (let x = 0; x <= w; x += 3) ctx.lineTo(x, ridge(x)); ctx.lineTo(w, h); ctx.fill();
+  // flames along the ridge
+  ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let x = 0; x < w; x += 2) { const y = ridge(x); const k = smooth(0.25, 0.6, N(x / 40, 7)); if (k < 0.05) continue; const fh = h * (0.02 + 0.07 * N(x / 9, 2)) * k; const g = ctx.createLinearGradient(0, y, 0, y - fh); g.addColorStop(0, `rgba(255,220,120,${0.9 * k})`); g.addColorStop(0.4, `rgba(255,120,30,${0.7 * k})`); g.addColorStop(1, 'rgba(200,40,10,0)'); ctx.fillStyle = g; ctx.fillRect(x, y - fh, 2.4, fh + 2); }
+  for (let x = 0; x < w; x += w / 14) { const y = ridge(x); glow(ctx, x, y, w * 0.12, 'rgba(255,100,20,A)', 0.25 * smooth(0.25, 0.6, N(x / 40, 7))); }
+  for (let i = 0; i < 120; i++) { const x = R() * w, y = R() * h * 0.55; ctx.fillStyle = `rgba(255,${150 + R() * 80},60,${R() * 0.8})`; ctx.fillRect(x, y, 1.6, 1.6); }
+  ctx.restore();
+  // road & tail lights
+  ctx.fillStyle = '#0b0b0c'; ctx.beginPath(); ctx.moveTo(0, h); ctx.lineTo(w * 0.42, h * 0.74); ctx.lineTo(w * 0.52, h * 0.74); ctx.lineTo(w, h); ctx.fill();
+  ctx.strokeStyle = 'rgba(255,220,120,.4)'; ctx.setLineDash([8, 10]); ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(w * 0.62, h); ctx.lineTo(w * 0.475, h * 0.745); ctx.stroke(); ctx.setLineDash([]);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; for (const [x, y, s] of [[0.36, 0.86, 1], [0.44, 0.8, 0.6], [0.47, 0.77, 0.4]]) { glow(ctx, x * w, y * h, w * 0.04 * s, 'rgba(255,30,30,A)', 0.8); glow(ctx, x * w + w * 0.06 * s, y * h, w * 0.04 * s, 'rgba(255,30,30,A)', 0.8); } ctx.restore();
+  vignette(ctx, w, h, 0.5); grain(ctx, w, h, 0.13);
+};
+
+// inside the cabin of a diverting airliner: masks down, emergency floor lighting, a calm crew
+PT.cabin = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 81); const vx = w * 0.52, vy = h * 0.42;
+  const bg = ctx.createRadialGradient(vx, vy, 0, vx, vy, h); bg.addColorStop(0, '#5a5040'); bg.addColorStop(0.35, '#2a2620'); bg.addColorStop(1, '#0c0b0a'); ctx.fillStyle = bg; ctx.fillRect(0, 0, w, h);
+  const P = (x, y, z) => [vx + (x - vx) * z, vy + (y - vy) * z];
+  // ceiling & bins
+  ctx.fillStyle = '#1e1c1a'; poly(ctx, [[0, 0], [w, 0], P(w, 0, 0.12), P(0, 0, 0.12)], true); ctx.fill();
+  for (const side of [0, 1]) { const x0 = side ? w : 0; ctx.fillStyle = '#2c2a27'; poly(ctx, [[x0, h * 0.05], P(x0, h * 0.05, 0.12), P(x0, h * 0.3, 0.12), [x0, h * 0.3]], true); ctx.fill();
+    ctx.strokeStyle = 'rgba(255,236,200,.5)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(x0, h * 0.3); const e = P(x0, h * 0.3, 0.12); ctx.lineTo(e[0], e[1]); ctx.stroke(); }
+  // windows (dark night outside, faint blue)
+  for (let i = 0; i < 9; i++) { const z = 1 / (1 + i * 0.55); for (const side of [0, 1]) { const x0 = side ? w : 0; const [x, y] = P(x0, h * 0.36, z); const ww = w * 0.05 * z, wh = h * 0.08 * z; ctx.fillStyle = '#0b1424'; ctx.beginPath(); ctx.ellipse(x + (side ? -ww : ww), y, ww * 0.5, wh * 0.5, 0, 0, TAU); ctx.fill(); } }
+  // seat rows receding
+  for (let i = 9; i >= 0; i--) { const z = 1 / (1 + i * 0.55); for (const side of [0, 1]) { for (let k = 0; k < 3; k++) { const sx = side ? lerp(w * 0.62, w * 1.05, k / 2.4) : lerp(w * 0.42, -w * 0.05, k / 2.4); const [x, y] = P(sx, h * 0.6, z); const sw = w * 0.13 * z, sh = h * 0.3 * z; ctx.fillStyle = `rgb(${18 + i * 2},${24 + i * 2},${44 + i * 2})`; ctx.beginPath(); ctx.roundRect(x - sw / 2, y - sh * 0.55, sw * 0.92, sh, sw * 0.18); ctx.fill(); ctx.fillStyle = `rgba(210,205,190,${0.5 - i * 0.03})`; ctx.fillRect(x - sw * 0.38, y - sh * 0.52, sw * 0.7, sh * 0.12); if (R() < 0.75) { ctx.fillStyle = `rgba(${40 + R() * 40},${30 + R() * 30},${25 + R() * 20},.95)`; ctx.beginPath(); ctx.arc(x - sw * 0.05, y - sh * 0.62, sw * 0.2, 0, TAU); ctx.fill(); } } } }
+  // oxygen masks hanging on their tubes
+  for (let i = 0; i < 26; i++) { const z = 1 / (1 + R() * 5); const side = R() < 0.5; const sx = side ? lerp(w * 0.62, w * 1.0, R()) : lerp(w * 0.42, 0, R()); const [x, y0] = P(sx, h * 0.3, z); const L = h * (0.12 + R() * 0.16) * z; const sway = (R() - 0.5) * 10 * z; ctx.strokeStyle = 'rgba(240,240,230,.7)'; ctx.lineWidth = Math.max(0.6, 1.4 * z); ctx.beginPath(); ctx.moveTo(x, y0); ctx.quadraticCurveTo(x + sway, y0 + L * 0.6, x + sway * 0.6, y0 + L); ctx.stroke(); ctx.fillStyle = '#F4C21A'; ctx.beginPath(); ctx.ellipse(x + sway * 0.6, y0 + L + 5 * z, 7 * z * (w / 400), 9 * z * (w / 400), 0, 0, TAU); ctx.fill(); }
+  // aisle with emergency floor path lighting
+  ctx.fillStyle = '#161412'; poly(ctx, [[w * 0.36, h], [w * 0.68, h], P(w * 0.56, h, 0.1), P(w * 0.48, h, 0.1)], true); ctx.fill();
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; for (let i = 0; i < 18; i++) { const z = 1 / (1 + i * 0.4); for (const xx of [w * 0.38, w * 0.66]) { const [x, y] = P(xx, h * 0.99, z); glow(ctx, x, y, 10 * z * (w / 300), 'rgba(255,170,70,A)', 0.9); } } glow(ctx, vx, vy - h * 0.05, w * 0.3, 'rgba(255,220,170,A)', 0.25); ctx.restore();
+  // a crew member down the aisle
+  const [cx, cy] = P(w * 0.52, h * 0.66, 0.42); ctx.fillStyle = '#0d0c10'; ctx.beginPath(); ctx.roundRect(cx - w * 0.03, cy - h * 0.16, w * 0.06, h * 0.17, 6); ctx.fill(); ctx.beginPath(); ctx.arc(cx, cy - h * 0.18, w * 0.022, 0, TAU); ctx.fill();
+  // motion blur feel + grain
+  ctx.save(); ctx.globalAlpha = 0.18; ctx.drawImage(cv, 3, 1); ctx.restore();
+  vignette(ctx, w, h, 0.6); grain(ctx, w, h, 0.16);
+};
+
+// a city block after the power went out: one building on generator light
+PT.blackout = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 91);
+  const sky = ctx.createLinearGradient(0, 0, 0, h); sky.addColorStop(0, '#05060a'); sky.addColorStop(1, '#10121a'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, h);
+  for (let i = 0; i < 7; i++) { const x = i * w / 6 - 10, bw = w / 6 + 10, bh = h * (0.25 + R() * 0.3); ctx.fillStyle = '#08090c'; ctx.fillRect(x, h * 0.72 - bh, bw, bh); }
+  const hx = w * 0.56, hy = h * 0.38; ctx.fillStyle = '#121418'; ctx.fillRect(hx - w * 0.16, hy, w * 0.32, h * 0.34);
+  for (let r = 0; r < 7; r++) for (let c = 0; c < 10; c++) { if (R() < 0.45) continue; ctx.fillStyle = `rgba(255,${225 + R() * 30},${180 + R() * 50},${0.45 + R() * 0.5})`; ctx.fillRect(hx - w * 0.145 + c * w * 0.03, hy + h * 0.025 + r * h * 0.042, w * 0.016, h * 0.022); }
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, hx, hy + h * 0.15, w * 0.4, 'rgba(255,230,190,A)', 0.18); glow(ctx, w * 0.2, h * 0.86, w * 0.1, 'rgba(255,40,40,A)', 0.6); ctx.restore();
+  const rg = ctx.createLinearGradient(0, h * 0.72, 0, h); rg.addColorStop(0, '#0b0c10'); rg.addColorStop(1, '#030304'); ctx.fillStyle = rg; ctx.fillRect(0, h * 0.72, w, h * 0.28);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; ctx.globalAlpha = 0.25; for (let y = h * 0.74; y < h; y += 2) { ctx.fillStyle = 'rgba(255,220,170,.5)'; ctx.fillRect(hx - w * 0.08 + Math.sin(y) * 4, y, w * 0.16, 1); } ctx.restore();
+  ctx.strokeStyle = 'rgba(200,210,230,.2)'; ctx.lineWidth = 1; ctx.beginPath(); for (let i = 0; i < 160; i++) { const x = R() * w, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - 4, y + 14); } ctx.stroke();
+  vignette(ctx, w, h, 0.55); grain(ctx, w, h, 0.15);
+};
+
+/* ---------- registry: id → draw(canvas, opts); scenes are drawn at t ---------- */
+PT.draw = function (id, cv, o = {}) {
+  if (SCN[id]) { const sc = SCN[id]; const key = id + '|' + cv.width + 'x' + cv.height + '|' + (o.seed || 0) + '|' + (o.skyline ? 1 : 0) + (o.palm ? 1 : 0); PT._bases = PT._bases || new Map(); let B = PT._bases.get(key); if (!B) { B = sc.base(cv.width, cv.height, o); PT._bases.set(key, B); } sc.frame(cv.getContext('2d'), cv.width, cv.height, o.t ?? performance.now() / 1000, o, B); return true; }
+  const f = PT[id]; if (typeof f !== 'function') return false; f(cv, o); return true;
+};
+PT.animated = (id) => !!SCN[id];
+
 // ---- 40-camera.js
 /* Camera: orbit (target lat/lon, range, heading, tilt, lens shift) with touch/pinch/wheel and
    inertia; fly-to along eased great-circle arcs with a log-space altitude hump (van Wijk-style);
@@ -3207,7 +4346,8 @@ function dayReplay(lat, lon, localHour = 15.5) {
   while (t > NOW) t -= 86400000; return { at: t, start: t - 3 * 3600000, end: t + 3 * 3600000, replay: true };
 }
 SIT.dayReplay = dayReplay;
-const LAUNCH_T0 = NOW + (2 * 3600 + 14 * 60 + 33) * 1000;
+const LAUNCH_T0 = NOW - (34 * 60 + 12) * 1000;
+GE.LAUNCH_T0 = LAUNCH_T0;
 const KOSHI_T = GE.scenes.FLOOD.startMs;
 const AURORA_T = (() => { const d = new Date(NOW); d.setUTCHours(21, 30, 0, 0); if (d.getTime() < NOW) d.setUTCDate(d.getUTCDate() + 1); return d.getTime(); })();
 
@@ -3293,11 +4433,11 @@ add({
 });
 add({
   id: 'launch', short: 'Launch · SLC-40', fam: 'orbit', kind: 'launch', section: 'now', live: true, aspect: 1.5, ageS: 300, watchers: 33800,
-  title: 'Rideshare launch from SLC-40 — countdown', place: 'Cape Canaveral, Florida', lat: 28.5618, lon: -80.5772,
+  title: 'Twilight launch from SLC-40 — plume seen along 600 km of coast', place: 'Cape Canaveral, Florida', lat: 28.5618, lon: -80.5772,
   camera: { lat: 28.5585, lon: -80.5825, range: 0.00045, heading: 0.85, tilt: 1.28 }, labels3d: [[28.5618, -80.5772, 'SLC-40 · vehicle on pad', 0.11]], thumbCam: { lat: 28.25, lon: -80.95, range: 0.028, heading: 0.75, tilt: 1.0 }, layers: ['launches', 'flights', 'ais', 'tracks'], source: 'Range schedule (illustrative)',
-  metric: () => [`<span class="num">T−${fmt.dur((LAUNCH_T0 - Date.now()) / 1000)}</span>`, 'Rideshare to SSO · trajectory NE'],
-  metrics: () => [{ v: fmt.dur((LAUNCH_T0 - Date.now()) / 1000), u: '', l: 'Countdown', s: 'Range · 5 min' }, { v: 92, u: '%', l: 'Weather go', s: 'Forecast · 1 h' }, { v: 14, u: '', l: 'Vessels in hazard area', s: 'AIS · 40 s' }],
-  brief: { lede: 'Vehicle is vertical on the pad. The hazard area offshore is still being cleared — 14 vessels remain inside. Trajectory heads northeast along the coast.', series: [{ label: 'Vessels in hazard area', unit: '', data: [41, 39, 36, 33, 31, 28, 24, 21, 19, 17, 15, 14], src: 'AIS · 15 min · 40 s', fmt: (v) => v }], sources: [['Range schedule (illustrative)', '5 min', 'live'], ['AIS', '40 s', 'live']] },
+  metric: () => [`<span class="num">T+${fmt.dur((Date.now() - LAUNCH_T0) / 1000)}</span>`, 'Rideshare to SSO · 2nd stage coasting'],
+  metrics: () => [{ v: fmt.dur((Date.now() - LAUNCH_T0) / 1000), u: '', l: 'Since liftoff', s: 'Range · live' }, { v: 212, u: 'km', l: '2nd stage altitude', s: 'Tracking · 10 s' }, { v: 418, u: '', l: 'Sky captures', s: 'Signed · 4 min' }],
+  brief: { lede: 'The vehicle lifted off just after sunset. Its exhaust climbed into sunlight above the dark ground and spread into a glowing "jellyfish" seen from Georgia to the Keys. The second stage is coasting to its burn; the pad is being safed.', series: [{ label: 'Sky captures per minute', unit: '', data: [0, 2, 14, 61, 120, 96, 70, 44, 30, 22, 15, 11], src: 'Signed bundles · 1 min', fmt: (v) => v }], sources: [['Range schedule (illustrative)', '5 min', 'live'], ['Tracking camera (illustrative)', '10 s', 'live'], ['Signed sky captures', '4 min', 'live']] },
 });
 add({
   id: 'koshi', short: 'Bhote Koshi · 4D', fam: 'haz', kind: 'recon', section: 'recon', live: false, aspect: 1.33, ageS: 53 * 86400, watchers: 12800, thread: 'koshi', d4: true,
@@ -3381,6 +4521,21 @@ add({
   brief: { lede: 'Two traffic separation lanes, one of the densest anchorages anywhere.', series: [{ label: 'Transits per hour', unit: '', data: walk(24, 80, 4, 0, 61).map(Math.round), src: 'AIS · hourly', fmt: (v) => v }], sources: [['AIS', '40 s', 'live']] },
 });
 
+/* round two: situations behind the new feed cards (lite: camera, layers, brief) */
+const lite = (o) => add({ live: true, aspect: 1.25, section: 'now', watchers: 3000, metric: () => [o.m0 || '', o.m1 || ''], metrics: () => o.ms.map(([v, u, l, sx]) => ({ v, u, l, s: sx })), brief: { lede: o.lede, series: o.series || [], sources: o.sources || [] }, ...o });
+lite({ id: 'dfw', short: 'Squall line · DFW', fam: 'wx', kind: 'storm', title: 'Bowing squall line crossing Dallas–Fort Worth', place: 'Dallas–Fort Worth, Texas', lat: 32.82, lon: -97.0, camera: { lat: 32.62, lon: -97.12, range: 0.05, heading: 0.3, tilt: 0.9 }, layers: ['radar', 'lightning', 'flights', 'traffic'], source: 'Radar mosaic', watchers: 26100, ageS: 90,
+  ms: [[62, 'dBZ', 'Peak reflectivity', 'Radar · 2 min'], [72, 'km/h', 'Line motion', 'Derived'], [1, '', 'Tornado warning', 'Warning feed · 4 min']], lede: 'A bowing line is racing east at 72 km/h. The apex is producing 100 km/h gusts and a brief tornado warning covers Arlington. Departures at DFW are on a ground stop.', series: [{ label: 'Peak dBZ', unit: '', data: [38, 41, 47, 52, 55, 58, 61, 62], src: 'Radar mosaic · 5 min', fmt: (v) => v }], sources: [['Radar mosaic (illustrative)', '2 min', 'live'], ['Lightning network', '30 s', 'live']] });
+lite({ id: 'gulf', short: 'Lightning · Gulf', fam: 'wx', kind: 'lightning', title: '4,812 lightning strikes in the last hour over the Gulf', place: 'Gulf of Mexico', lat: 26.5, lon: -89, camera: { lat: 24.5, lon: -89.5, range: 0.3, heading: 0, tilt: 0.5 }, layers: ['lightning', 'clouds', 'flights', 'ais'], source: 'Lightning network', watchers: 4100, ageS: 60,
+  ms: [['4,812', '', 'Strikes / h', 'Network · 1 min'], [5, '', 'Active cells', 'Derived'], [31, '', 'Flights deviating', 'ADS-B · 2 min']], lede: 'Five clusters of deep convection are firing over warm Gulf water. Airliners are deviating around the two strongest cells.', sources: [['Lightning network (illustrative)', '1 min', 'live']] });
+lite({ id: 'shibuya', short: 'Shibuya crossing', fam: 'eyes', kind: 'eye', title: 'Shibuya crossing in the rain — public camera', place: 'Shibuya, Tokyo', lat: 35.6595, lon: 139.7005, camera: { lat: 35.6575, lon: 139.6985, range: 0.0009, heading: 0.6, tilt: 1.1 }, layers: ['cctv', 'transit', 'traffic', 'venues'], source: 'Public camera', watchers: 9400, ageS: 3,
+  ms: [['~2,400', '', 'People per cycle', 'Camera count · 1 min'], [12, 'mm/h', 'Rain', 'Gauge · 10 min'], [46, 's', 'Signal cycle', 'Observed']], lede: 'A public street camera over the scramble. Counts are estimated on-device; no faces are kept.', sources: [['Public street camera (illustrative)', 'live', 'live']] });
+lite({ id: 'derby', short: 'Derby egress', fam: 'ground', kind: 'crowd', title: 'Derby egress: crowd density building at Gate C', place: 'Avellaneda, Buenos Aires', lat: -34.6705, lon: -58.3685, camera: { lat: -34.6735, lon: -58.3715, range: 0.0012, heading: 0.4, tilt: 1.0 }, layers: ['venues', 'transit', 'traffic', 'cctv'], source: 'Crowd sensing (illustrative)', watchers: 11800, ageS: 40,
+  ms: [[4.6, 'p/m²', 'Peak density', 'Derived · 30 s'], ['41k', '', 'Leaving', 'Estimate'], [3, '', 'Gates open', 'Venue feed']], lede: 'Fans are leaving after the final whistle. Density outside Gate C has passed 4 people per square metre while Gates A and D are flowing freely. Stewards are being redirected.', series: [{ label: 'Density at Gate C', unit: 'p/m²', data: [1.1, 1.4, 2.0, 2.8, 3.5, 4.1, 4.6], src: 'Derived · 1 min', fmt: (v) => v.toFixed(1) }], sources: [['Crowd sensing (illustrative)', '30 s', 'live'], ['Signed captures', '3 min', 'live']] });
+lite({ id: 'sakurajima', short: 'Sakurajima cam', fam: 'haz', kind: 'volcano', title: 'Sakurajima ash column to 3.2 km — webcam', place: 'Kagoshima Bay, Japan', lat: 31.58, lon: 130.66, camera: { lat: 31.52, lon: 130.6, range: 0.012, heading: 0.5, tilt: 1.15 }, layers: ['volcanoes', 'flights', 'wind', 'cctv'], source: 'Volcano webcam', watchers: 5300, ageS: 120,
+  ms: [[3.2, 'km', 'Ash column', 'Webcam · 2 min'], ['ESE', '', 'Drift', 'Wind model'], [0, '', 'Flights affected', 'ADS-B']], lede: 'A routine but tall explosion. Ash is drifting away from the city; the airport is open.', sources: [['Volcano webcam (illustrative)', '2 min', 'live'], ['Wind model', '1 h', 'live']] });
+lite({ id: 'lakefront', short: 'Lake Michigan gale', fam: 'wx', kind: 'gale', title: 'Gale on Lake Michigan — waves over the lakefront trail', place: 'Chicago lakefront', lat: 41.866, lon: -87.607, camera: { lat: 41.62, lon: -87.42, range: 0.035, heading: -0.35, tilt: 1.0 }, layers: ['cctv', 'signed', 'traffic'], source: 'Buoy + signed captures', watchers: 1900, ageS: 300, section: 'near',
+  ms: [[3.4, 'm', 'Wave height', 'Buoy · 10 min'], [74, 'km/h', 'Gusts', 'Station · 5 min'], [2, '', 'Trail closures', 'City feed']], lede: 'North-northeast gales are piling waves onto the lakefront. The trail is closed between two harbours.', sources: [['Lake buoy (illustrative)', '10 min', 'live'], ['Signed captures', 'live', 'live']] });
+
 for (const s of S) if (s.time && s.time.replay) { s.live = false; s.replayLabel = 'Today ' + new Date(s.time.at).toLocaleTimeString('en-US', { hour: 'numeric', minute: '2-digit', timeZone: 'UTC' }) + ' UTC'; }
 SIT.list = S;
 SIT.byId = Object.fromEntries(S.map((s) => [s.id, s]));
@@ -3390,12 +4545,272 @@ SIT.sections = [
 // dynamic cameras
 SIT.cameraFor = function (s) {
   if (s.id === 'starlink') { const g = GE.world.sun.gmst; const p = GE.satAt(GE.SATS.find((x) => x.kind === 5), GE.world.t, g); const [la, lo] = geo.ll(p); return { lat: la - 6, lon: lo - 8, range: 0.32, heading: 0.6, tilt: 0.85 }; }
+  if (s.id === 'squawk' && GE.feed && GE.feed._sq) return s.camera;
   if (s.id === 'squawk') { const f = GE.FLIGHTS[GE.world.squawks[0]]; const p = GE.flightAt(f, GE.world.t) || { lat: 50, lon: -30 }; return { lat: p.lat - 4, lon: p.lon - 3, range: 0.3, heading: 0.3, tilt: 0.75 }; }
   if (s.id === 'iss') { const p = GE.satAt(GE.ISS, GE.world.t, GE.world.sun.gmst); const [la, lo] = geo.ll(p); return { lat: la - 9, lon: lo - 4, range: 0.48, heading: 0.35, tilt: 0.78 }; }
   return s.camera;
 };
 SIT.pin = (s) => { if (s.id === 'starlink' || s.id === 'squawk' || s.id === 'iss') { const c = SIT.cameraFor(s); return null; } return { id: s.id, lat: s.lat, lon: s.lon, title: s.title, col: [...hex2rgb(fam(s.fam)), 1], seed: hash01(s.id.length) }; };
 
+// ---- 54-rooms.js
+/* Rooms — every situation has one. Structured posts (Witness / Context / Question / Correction /
+   Prediction) anchored in place and time, badges earned from evidence, community notes shown only when
+   raters who usually disagree both find them helpful, and a Known / Disputed / Unknown synthesis whose
+   every line cites a post or an observation. All people, posts and claims are fictional. */
+const RM = (GE.rooms = { byId: {} });
+const MIN_ = 60000, HR2 = 3600000;
+RM.KINDS = {
+  witness: { name: 'Witness', icon: 'eye', tone: 'gold', hint: 'I saw or recorded this' },
+  context: { name: 'Context', icon: 'layers', tone: 'sky', hint: 'Background, a map, a source' },
+  question: { name: 'Question', icon: 'bubble', tone: 'white', hint: 'Floats to the top until answered' },
+  correction: { name: 'Correction', icon: 'flag', tone: 'amber', hint: 'Something here is wrong' },
+  prediction: { name: 'Prediction', icon: 'clock', tone: 'orbit', hint: 'What happens next — scored later' },
+};
+const P0 = GE.PEOPLE;
+const kmBetween = (a, b, c, d) => geo.dist(a, b, c, d) * EARTH_KM;
+RM.kmBetween = kmBetween;
+
+/* ---------- room content ---------- */
+const CY = GE.CYCLONE.at(0);
+const ROOMS = {
+  cyclone: {
+    watching: 3204, rate: 4,
+    src: { O1: 'Geostationary IR mosaic · 01:40Z', O2: 'Advisory + 14 ensemble tracks · 3 h', O3: 'AIS vessel positions · 40 s', S1: 'Sealed live stream, 6 segments · @nadia_basco' },
+    posts: [
+      { id: 'cy1', kind: 'witness', by: 'nadia', ago: 4, live: true, text: 'Waves are coming over the seawall by the port every 30–40 seconds. The road behind it is ankle-deep. The wall itself is intact from what I can see — I\'m 200 m up the slope.', place: { lat: 20.4485, lon: 121.9705, label: 'Basco seawall' }, att: { paint: 'seawall', o: { palm: true, handheld: true, noOSD: true, seed: 52 }, tier: 'sealed-live', segs: 6, distKm: 0.2 }, reacts: { eye: 1240, heart: 212, alert: 48 }, replies: 31 },
+      { id: 'cy2', kind: 'question', by: 'rafa', ago: 6, text: 'Is the Magapit bridge into Aparri still open? Nobody here knows and the power is out.', place: { lat: 18.12, lon: 121.65, label: 'Magapit bridge' }, reacts: { eye: 96 }, replies: 2 },
+      { id: 'cy3', kind: 'context', by: 'lin', ago: 11, text: 'An eyewall replacement looks likely in the next 12 h. Expect the peak wind number to drop while the wind field gets wider. For Batanes that is not good news, so don\'t read a lower number as "weakening".', cites: ['O1', 'O2'], reacts: { heart: 340, eye: 520 }, replies: 18 },
+      { id: 'cy4', kind: 'witness', by: 'repost', ago: 9, text: 'VIDEO: Basco port pier has COLLAPSED!! Share before it\'s deleted', att: { paint: 'harbour', o: { seed: 19, cam: 'CAM 03', place: 'PORT' }, tier: 'unverified', distKm: null }, reacts: { alert: 860 }, replies: 77,
+        note: { text: 'This clip is from a 2019 storm at a different port. Reverse-image search finds 3 earlier copies. The pier is visible and intact in tonight\'s sealed live stream from Basco [P1].', helpfulA: 0.81, helpfulB: 0.74, ratersA: 118, ratersB: 94, cites: ['P1'] } },
+      { id: 'cy5', kind: 'prediction', by: 'joon', ago: 14, text: 'Kaohsiung will close the port to outbound traffic by 06:00 local. 11 ships have already left the anchorage and are heading south of the track.', place: { lat: 22.61, lon: 120.27, label: 'Kaohsiung pier 70' }, att: { paint: 'harbour', o: { seed: 8, cam: 'HBR-07', place: 'KAOHSIUNG PIER 70' }, tier: 'eye', distKm: null }, cites: ['O3'], reacts: { eye: 210, heart: 41 }, replies: 6, resolves: '06:00 local' },
+      { id: 'cy6', kind: 'witness', by: 'rafa', ago: 22, text: 'Power out across Aparri centro since 01:10. The hospital is on generators. Rain is sideways.', place: { lat: 18.357, lon: 121.637, label: 'Aparri centro' }, att: { paint: 'blackout', o: { seed: 91 }, tier: 'sealed', distKm: 0.4 }, reacts: { heart: 190, eye: 300 }, replies: 9 },
+      { id: 'cy7', kind: 'correction', by: 'ais', ago: 18, text: 'Correction to an earlier post: there are 2 ships holding off Batanes, not 6. The other 4 are at anchor in the lee of Sabtang and are fine.', cites: ['O3'], place: { lat: 20.34, lon: 121.85, label: 'Sabtang lee' }, reacts: { heart: 88 }, replies: 3 },
+    ],
+    synth: {
+      known: [['Waves are overtopping the Basco seawall near the port; the wall itself is intact as of a few minutes ago.', ['P1', 'S1']], ['Eyewall cloud tops are colder than −80 °C with frequent lightning.', ['O1']], ['Aparri centro has lost power; the hospital is on generators.', ['P6']]],
+      disputed: [['A viral "collapsed pier" video — a community note shows it predates this storm.', ['P4', 'N1']], ['Whether Halcyon is weakening: peak wind estimates dip while the wind field broadens.', ['P3', 'O2']]],
+      unknown: [['Whether the Magapit bridge into Aparri is open — asked 6 min ago, no evidence yet.', ['P2']], ['Landfall point: guidance still spreads ±150 km at 36 h.', ['O2']]],
+    },
+  },
+  quake: {
+    watching: 1880, rate: 2,
+    src: { O1: 'Seismic catalog · revised 12 min ago', O2: 'Tide gauges · 3 min', O3: 'Rail status boards · 9 min' },
+    posts: [
+      { id: 'qk1', kind: 'question', by: 'aiko', ago: 48, text: 'Are trains running north of Sendai yet? Stuck at the station with my kids.', place: { lat: 38.26, lon: 140.88, label: 'Sendai station' }, answered: 'qk2', reacts: { eye: 140 }, replies: 5 },
+      { id: 'qk2', kind: 'context', by: 'tetsu', ago: 41, text: 'Northbound service resumed at 02:41 after track inspection. Expect 20–30 min delays through Fukushima.', cites: ['O3'], reacts: { heart: 220 }, replies: 4 },
+      { id: 'qk3', kind: 'witness', by: 'aiko', ago: 300, text: 'Long rolling shake, maybe 40 seconds. Shelves came down in the store and everyone came out onto the street. Nobody hurt here.', place: { lat: 38.262, lon: 140.871, label: 'Aoba-ku' }, att: { paint: 'crossing', o: { seed: 33, cam: 'PHONE', rec: false }, tier: 'sealed', distKm: 162 }, reacts: { heart: 410, eye: 700 }, replies: 22 },
+      { id: 'qk4', kind: 'correction', by: 'geo', ago: 280, text: 'The depth is 32 km in the revised solution, not the 10 km in early reposts. That matters for how far the shaking reached.', cites: ['O1'], reacts: { heart: 160 }, replies: 7 },
+      { id: 'qk5', kind: 'witness', by: 'repost', ago: 310, text: 'TSUNAMI 3 METERS hitting the coast right now!!!', reacts: { alert: 1900 }, replies: 140,
+        note: { text: 'Tide gauges along the coast recorded at most 20 cm [O2]. No tsunami warning was issued. The video attached to the original claim is from 2011.', helpfulA: 0.88, helpfulB: 0.79, ratersA: 302, ratersB: 241, cites: ['O2'] } },
+      { id: 'qk6', kind: 'prediction', by: 'geo', ago: 200, text: 'Chance of an M5+ aftershock in the next 72 h is about 1 in 4 for a sequence like this. Not a reason to panic, a reason to secure shelves.', cites: ['O1'], reacts: { heart: 98 }, replies: 11, resolves: 'in 72 h' },
+    ],
+    synth: {
+      known: [['An M 6.4 thrust event at 32 km depth off the Honshu coast.', ['O1', 'P4']], ['Tide gauges recorded at most 20 cm; no tsunami.', ['O2', 'N1']], ['Northbound trains resumed at 02:41 with delays.', ['P2', 'O3']]],
+      disputed: [['Early reposts claimed a 3 m tsunami — rated false by raters across perspectives.', ['P5', 'N1']]],
+      unknown: [['Damage inland of Fukushima — the only sealed capture so far is from Sendai.', ['P3']], ['Whether a larger aftershock follows (≈ 1 in 4 within 72 h).', ['P6']]],
+    },
+  },
+  squawk: {
+    watching: 2410, rate: 3,
+    src: { O1: 'ADS-B · 1 Hz', O2: 'Diversion airport board · 2 min' },
+    posts: [
+      { id: 'sq1', kind: 'witness', by: 'seat', ago: 7, text: 'On board. Masks dropped about 20 minutes ago. Crew are calm, we\'re descending and they said we\'re landing soon. Everyone is OK.', att: { paint: 'cabin', o: { seed: 81 }, tier: 'sealed', distKm: 0 }, reacts: { heart: 1820, eye: 2100 }, replies: 64 },
+      { id: 'sq2', kind: 'context', by: 'tomas', ago: 12, text: 'Squawk 7700, a turn toward the nearest long runway and a steady ~2,400 ft/min descent to FL100 is what a pressurisation problem looks like. It is a well-practised procedure.', cites: ['O1'], reacts: { heart: 960 }, replies: 21 },
+      { id: 'sq3', kind: 'question', by: 'sky', ago: 5, text: 'Does anyone know which runway they\'ll use? Wind there is strong from the east.', reacts: { eye: 44 }, replies: 1 },
+      { id: 'sq4', kind: 'prediction', by: 'tomas', ago: 9, text: 'They\'ll be on the ground in about 34 minutes.', cites: ['O1', 'O2'], reacts: { heart: 120 }, replies: 2, resolves: 'at landing' },
+    ],
+    synth: {
+      known: [['The aircraft squawked 7700, turned toward the diversion airport and is descending.', ['O1']], ['A passenger on board reports masks deployed and the crew calm.', ['P1']]],
+      disputed: [],
+      unknown: [['The cause — the descent profile fits a pressurisation problem, unconfirmed.', ['P2']], ['Landing runway and time (est. ~34 min).', ['P3', 'P4']]],
+    },
+  },
+  fires: {
+    watching: 1460, rate: 2,
+    src: { O1: 'VIIRS 375 m hotspots · 38 min', O2: 'Wind model · 1 h' },
+    posts: [
+      { id: 'fi1', kind: 'witness', by: 'ines', ago: 26, text: 'The ridge above the N2 is burning along about two kilometres. Ash is falling on the road. Traffic is still moving south.', place: { lat: 40.13, lon: -8.05, label: 'N2 at the ridge' }, att: { paint: 'firewit', o: { seed: 71 }, tier: 'sealed', distKm: 1.8 }, reacts: { heart: 260, eye: 900 }, replies: 18 },
+      { id: 'fi2', kind: 'context', by: 'bomb', ago: 20, text: 'Front is moving west at about 1.2 km/h. The N2 will close between the two junctions within the hour. Please don\'t stop on the road to film.', cites: ['O1', 'O2'], reacts: { heart: 700 }, replies: 12 },
+      { id: 'fi3', kind: 'question', by: 'ines', ago: 8, text: 'Is the IC8 open toward Coimbra?', reacts: { eye: 60 }, replies: 0 },
+    ],
+    synth: { known: [['A fire front about 2 km long is burning above the N2, moving west ~1.2 km/h.', ['P1', 'P2', 'O1']]], disputed: [], unknown: [['Whether the IC8 toward Coimbra is open.', ['P3']]] },
+  },
+};
+// light rooms for the rest: a context post from the brief + an open question
+function liteRoom(s) {
+  const by = ['kora', 'sky', 'geo', 'ais', 'hydro'][s.id.length % 5];
+  return { watching: Math.round((s.watchers || 2000) * 0.06) + 40, rate: 1, src: Object.fromEntries((s.brief?.sources || []).slice(0, 3).map(([n, a], i) => ['O' + (i + 1), `${n} · ${a}`])),
+    posts: [{ id: s.id + '-1', kind: 'context', by, ago: 12, text: s.brief?.lede || s.title, cites: ['O1'], reacts: { heart: 40, eye: 120 }, replies: 3 }, { id: s.id + '-2', kind: 'question', by: 'kora', ago: 5, text: 'Anyone close enough to send a sealed capture?', reacts: { eye: 20 }, replies: 0 }],
+    synth: { known: [[s.brief?.lede?.split('. ')[0] + '.', ['O1', 'P1']]], disputed: [], unknown: [['No witness captures yet.', ['P2']]] } };
+}
+
+/* ---------- derived: badges, evidence score, ordering ---------- */
+RM.badges = function (room, p) {
+  const s = GE.SIT.byId[room.sit]; const who = P0[p.by] || {}; const out = [];
+  const sealed = p.att && /^sealed/.test(p.att.tier);
+  if (sealed && p.att.distKm != null && p.att.distKm <= 5) out.push(['there', `Was there · ${p.att.distKm < 1 ? Math.round(p.att.distKm * 1000) + ' m' : p.att.distKm.toFixed(1) + ' km'}`]);
+  if (sealed) out.push(['sealed', p.att.tier === 'sealed-live' ? 'Sealed live' : 'Sealed']);
+  if (who.home && s && kmBetween(who.home[0], who.home[1], p.place?.lat ?? s.lat, p.place?.lon ?? s.lon) < 120) out.push(['local', 'Local']);
+  if (who.domain) out.push(['domain', who.domain]);
+  if (p.att && p.att.tier === 'unverified') out.push(['unv', 'Unverified upload']);
+  if (p.by === 'you' && GE.ME && s && kmBetween(GE.ME.lat, GE.ME.lon, s.lat, s.lon) < 120 && !out.some((b) => b[0] === 'local')) out.push(['local', 'Local']);
+  return out;
+};
+RM.score = function (room, p) { let sc = 0; for (const [k] of RM.badges(room, p)) sc += { there: 4, sealed: 3, domain: 2, local: 1, unv: -2 }[k] || 0; if (p.att?.tier === 'eye') sc += 1; if (p.note) sc -= 3; return sc; };
+RM.ordered = function (room, mode = 'evidence') {
+  const ps = room.posts.slice();
+  const openQ = (p) => p.kind === 'question' && !p.answered;
+  if (mode === 'latest') return ps.sort((a, b) => b.at - a.at);
+  if (mode === 'questions') return ps.filter((p) => p.kind === 'question').sort((a, b) => (openQ(b) - openQ(a)) || b.at - a.at);
+  return ps.sort((a, b) => (openQ(b) - openQ(a)) || RM.score(room, b) - RM.score(room, a) || b.at - a.at);
+};
+RM.pid = (room, p) => 'P' + (room.posts.indexOf(p) + 1);
+RM.byPid = (room, pid) => room.posts[+pid.slice(1) - 1];
+
+/* ---------- ledger per room (real SHA-256 chain) ---------- */
+RM.append = async function (room, type, actor, payload) {
+  const L = room.ledger; const prev = L.length ? L[L.length - 1].hash : '0'.repeat(64);
+  const e = { i: L.length, ts: Date.now(), type, actor, payload }; e.digest = await sha256(canon(payload)); e.prev = prev; e.hash = await sha256(canon({ i: e.i, ts: e.ts, type: e.type, actor: e.actor, digest: e.digest, prev })); L.push(e); return e;
+};
+
+/* ---------- build ---------- */
+RM.get = function (sitId) {
+  if (RM.byId[sitId]) return RM.byId[sitId];
+  const s = GE.SIT.byId[sitId]; if (!s) return null;
+  const R0 = ROOMS[sitId] || liteRoom(s);
+  const room = { sit: sitId, ...R0, ledger: [], posts: R0.posts.map((p) => ({ ...p, at: NOW - (p.ago || 1) * MIN_ })) };
+  for (const p of room.posts) if (p.att && p.att.paint === 'seawall' && p.live) p.att.o.cam = '@' + P0[p.by].h;
+  RM.byId[sitId] = room;
+  (async () => { for (const p of room.posts) await RM.append(room, 'post.' + p.kind, P0[p.by]?.h || p.by, { id: p.id, text: p.text, att: p.att ? { tier: p.att.tier } : null, place: p.place || null }); })();
+  return room;
+};
+RM.count = (sitId) => { const r = ROOMS[sitId]; return r ? r.posts.length : 2; };
+RM.watching = (sitId) => (RM.byId[sitId]?.watching) ?? ROOMS[sitId]?.watching ?? Math.round((GE.SIT.byId[sitId]?.watchers || 2000) * 0.06) + 40;
+RM.sealedCount = (sitId) => { const r = RM.byId[sitId] || ROOMS[sitId]; return r ? r.posts.filter((p) => p.att && /^sealed/.test(p.att.tier)).length : 0; };
+RM.topClaim = function (sitId) {
+  const r = ROOMS[sitId]; if (!r) return null;
+  const open = r.posts.find((p) => p.kind === 'question' && !p.answered);
+  const k = r.synth.known[0], d = r.synth.disputed[0];
+  return { q: open?.text, known: k?.[0], disputed: d?.[0], sealed: r.posts.filter((p) => p.att && /^sealed/.test(p.att.tier)).length };
+};
+
+// ---- 55-feed.js
+/* Feed model — mixed archetypes across the four altitude bands, ordered for diversity.
+   Bands answer "where is the sensor": Orbit, Sky, Ground, and Inside (a person). */
+const FD = (GE.feed = {});
+GE.BANDS = {
+  orbit: { name: 'Orbit', c: '#B79CFF', alt: '400–36,000 km', sensor: 'satellites · ISS · launches' },
+  sky: { name: 'Sky', c: '#8CD4FF', alt: '0–15 km', sensor: 'aircraft · radar · lightning' },
+  ground: { name: 'Ground', c: '#FFA53D', alt: '0 m', sensor: 'cameras · seismometers · crowds' },
+  inside: { name: 'Inside', c: '#F2CF7A', alt: 'you', sensor: 'witnesses · broadcasts · rooms' },
+};
+GE.ARCH = { sensor: 'Sensor', eye: 'Eye', track: 'Track', number: 'Number', witness: 'Witness', room: 'Room' };
+const MIN3 = 60000;
+FD.fmtDist = (km) => (km < 1 ? Math.round(km * 1000) + ' m' : km < 100 ? km.toFixed(km < 10 ? 1 : 0) + ' km' : fmt.n(Math.round(km)) + ' km');
+FD.distFromMe = (lat, lon) => geo.dist(GE.ME.lat, GE.ME.lon, lat, lon) * EARTH_KM;
+const llz = (lat, lon) => `${Math.abs(lat).toFixed(2)}${lat >= 0 ? 'N' : 'S'} ${Math.abs(lon).toFixed(2)}${lon >= 0 ? 'E' : 'W'}`;
+const hmsZ = () => { const d = new Date(); return `${String(d.getUTCHours()).padStart(2, '0')}:${String(d.getUTCMinutes()).padStart(2, '0')}:${String(d.getUTCSeconds()).padStart(2, '0')}Z`; };
+FD.hmsZ = hmsZ; FD.llz = llz;
+
+/* the diverting flight, computed from the synthetic traffic so card, room and globe agree */
+FD.squawkTrack = function () {
+  if (FD._sq) return FD._sq;
+  const f = GE.FLIGHTS[GE.world.squawks[0]]; const pts = [];
+  for (let k = -90; k <= 0; k += 3) { const p = GE.flightAt(f, GE.world.t + k * 60); if (p) pts.push([p.lat, p.lon]); }
+  let ok = pts.length > 12;
+  if (!ok) { pts.length = 0; for (let k = 0; k <= 30; k++) pts.push(k < 18 ? [55 + k * 0.12, -10 - k * 0.9] : [57.1 + (k - 18) * 0.25, -26.2 - (k - 18) * 0.35]); }
+  const cur = pts[pts.length - 1]; let div = null, bd = 1e9;
+  for (const a of GE.AP) { if (a.w < 8) continue; const d = geo.dist(cur[0], cur[1], a.lat, a.lon); if (d < bd && d > 0.02) { bd = d; div = a; } }
+  if (!ok) div = GE.apByIata.RKV || div;
+  // bend the last third toward the diversion field
+  const k0 = Math.floor(pts.length * 0.62); const bend = pts.slice(0, k0 + 1); const a = pts[k0];
+  for (let i = 1; i <= pts.length - 1 - k0; i++) { const t = (i / (pts.length - 1 - k0)) * 0.45; bend.push([lerp(a[0], div.lat, t), lerp(a[1], div.lon, t)]); }
+  const alt = [37000, 37000, 36000, 31000, 27000, 24000];
+  FD._sq = { pts: bend, sqAt: k0, div: { lat: div.lat, lon: div.lon, iata: div.iata, city: div.city }, alt, cur: bend[bend.length - 1] };
+  // put the same track on the globe: white before the declaration, red after, the aircraft at its head
+  const W = GE.world; const C2 = FD._sq.cur; const alt3 = (i) => 10.5 - Math.max(0, i - k0) * 0.25;
+  W.extraLines.push({ pts: bend.slice(0, k0 + 1).map(([la, lo], i) => geo.vec(la, lo, alt3(i))), col: [0.85, 0.9, 1, 0.55] }, { pts: bend.slice(k0).map(([la, lo], i) => geo.vec(la, lo, alt3(i + k0))), col: [1, 0.25, 0.2, 0.95] }, { pts: [geo.vec(C2[0], C2[1], 7), geo.vec(div.lat, div.lon, 0)], col: [1, 0.45, 0.4, 0.5], dashed: 1 });
+  (W.extraSprites = W.extraSprites || []).push({ v: geo.vec(C2[0], C2[1], 7), col: [1, 0.23, 0.19, 1], size: 30 });
+  const s = GE.SIT.byId.squawk; if (s) { s.lat = C2[0]; s.lon = C2[1]; s.camera = { lat: C2[0] - 4, lon: C2[1] - 3, range: 0.14, heading: 0.35, tilt: 0.85 }; }
+  return FD._sq;
+};
+
+/* ---------- items ---------- */
+FD.items = function () {
+  if (FD._items) return FD._items;
+  const C = GE.CYCLONE.at(0); const sq = FD.squawkTrack(); const iss = GE.SIT.issPass(Date.now());
+  const it = [
+    { id: 'basco', arch: 'witness', band: 'inside', sit: 'cyclone', post: 'cy1', wide: true, prio: 100, live: true, by: 'nadia', paint: 'seawall', po: { palm: true, handheld: true, noOSD: true, seed: 52 }, aspect: 0.62,
+      title: 'Waves over the Basco seawall — live from the port', place: 'Basco, Batanes', lat: 20.4485, lon: 121.9705, ago: 14, cam: { lat: 18.6, lon: 123.4, range: 0.18, heading: -0.55, tilt: 0.62 },
+      tele: () => `WITNESS · SEALED LIVE · ±4 M · ${fmt.n(Math.round(RM.kmBetween(20.4485, 121.9705, C.lat, C.lon)))} KM FROM EYE` },
+    { id: 'ir', arch: 'sensor', band: 'orbit', sit: 'cyclone', prio: 95, paint: 'ir', aspect: 1.25, title: 'Typhoon Halcyon: −83 °C cloud tops and lightning in the eyewall', place: 'Philippine Sea', lat: C.lat, lon: C.lon, ago: 2,
+      tele: () => `ORBIT · GEO IR · 35,786 KM · ${llz(C.lat, C.lon)}` },
+    { id: 'cabin', arch: 'witness', band: 'inside', sit: 'squawk', post: 'sq1', prio: 92, by: 'seat', paint: 'cabin', aspect: 1.3, title: '“Masks dropped. Crew calm. We’re descending.” — on board the 7700', place: 'Over the North Atlantic', lat: sq.cur[0], lon: sq.cur[1], ago: 7,
+      tele: () => 'WITNESS · SEALED · ON BOARD · FL240' },
+    { id: 'harbour', arch: 'eye', band: 'ground', sit: 'cyclone', post: 'cy5', prio: 90, live: true, paint: 'harbour', po: { seed: 8, cam: 'HBR-07', place: 'KAOHSIUNG · PIER 70' }, aspect: 1.0, title: 'Kaohsiung harbour cam: ships leave ahead of Halcyon', place: 'Kaohsiung, Taiwan', lat: 22.61, lon: 120.27, ago: 0, cam: { lat: 21.2, lon: 121.6, range: 0.2, heading: -0.7, tilt: 0.6 },
+      tele: () => `GROUND · CAM HBR-07 · ${llz(22.61, 120.27)} · ${hmsZ()}` },
+    { id: 'squawk', arch: 'track', band: 'sky', sit: 'squawk', prio: 89, live: true, paint: 'track', po: { track: sq }, aspect: 1.15, title: `Squawk 7700 — diverting to ${sq.div.iata} ${sq.div.city ? '(' + sq.div.city + ')' : ''}`, place: 'Over the North Atlantic', lat: sq.cur[0], lon: sq.cur[1], ago: 3,
+      readout: 'SQ 7700 · FL240 ↓', tele: () => 'SKY · ADS-B · 2,400 FPM ↓ · 412 KT', cta: ['airplane', 'Follow the track'] },
+    { id: 'room-cy', arch: 'room', band: 'inside', sit: 'cyclone', prio: 88, wide: true, title: 'Typhoon Halcyon', place: 'Batanes · Babuyan · Luzon Strait', lat: 20.45, lon: 121.97, ago: 1, ev: [['seawall', { palm: true, noOSD: true, seed: 52 }], ['harbour', { seed: 8, cam: 'HBR-07' }], ['blackout', { seed: 91 }], ['ir', {}]] },
+    { id: 'radar', arch: 'sensor', band: 'sky', sit: 'dfw', prio: 86, paint: 'radar', aspect: 1.2, title: 'Bowing squall line crossing Dallas–Fort Worth — tornado warning', place: 'Dallas–Fort Worth', lat: 32.82, lon: -97.0, ago: 2,
+      tele: () => 'SKY · RADAR 0.5° · 62 DBZ · 72 KM/H E' },
+    { id: 'crossing', arch: 'eye', band: 'ground', sit: 'shibuya', prio: 84, live: true, paint: 'crossing', po: { seed: 31, cam: 'CAM 0412', place: 'SHIBUYA SCRAMBLE' }, aspect: 1.25, title: 'Shibuya crossing in the rain: ~2,400 people every cycle', place: 'Shibuya, Tokyo', lat: 35.6595, lon: 139.7005, ago: 0,
+      tele: () => `GROUND · CAM 0412 · ${llz(35.6595, 139.7005)} · ${hmsZ()}` },
+    { id: 'shake', arch: 'sensor', band: 'ground', sit: 'quake', prio: 83, paint: 'shake', aspect: 1.15, title: 'M 6.4 off Honshu: strongest shaking on the Fukushima coast', place: 'Off eastern Honshu', lat: GE.BIGQ.lat, lon: GE.BIGQ.lon, ago: 324,
+      tele: () => 'GROUND · 46 STATIONS · MMI VI · 32 KM DEEP' },
+    { id: 'firesat', arch: 'sensor', band: 'orbit', sit: 'fires', prio: 80, paint: 'firesat', aspect: 1.1, title: 'Central Portugal: a 60 km smoke plume drifts toward the coast', place: 'Pampilhosa da Serra', lat: 40.05, lon: -7.95, ago: 38,
+      tele: () => 'ORBIT · 375 M · FRP 840 MW · WIND ESE 31' },
+    { id: 'isscam', arch: 'eye', band: 'orbit', sit: 'iss', prio: 79, live: true, paint: 'isscam', aspect: 1.3, title: 'From the station’s external camera: the Nile at night', place: '418 km over Egypt', lat: 27.1, lon: 31.2, ago: 0,
+      tele: () => 'ORBIT · ISS · 418 KM · 7.66 KM/S · 27.1N 31.2E' },
+    { id: 'firewit', arch: 'witness', band: 'inside', sit: 'fires', post: 'fi1', prio: 78, by: 'ines', paint: 'firewit', aspect: 1.25, title: 'The ridge above the N2 is burning — 1.8 km from the front', place: 'N2, central Portugal', lat: 40.13, lon: -8.05, ago: 26,
+      tele: () => 'WITNESS · SEALED · ±6 M · 1.8 KM FROM FRONT' },
+    { id: 'lightning', arch: 'number', band: 'sky', sit: 'gulf', prio: 76, paint: 'strikes', aspect: 1.05, title: 'Lightning over the Gulf of Mexico', place: 'Gulf of Mexico', lat: 26.5, lon: -89, ago: 1,
+      big: '4,812', unit: 'strikes', label: 'in the last hour over the Gulf', spark: [1200, 1500, 1900, 2600, 3100, 3800, 4300, 4812], tele: () => 'SKY · LIGHTNING NETWORK · 5 CELLS' },
+    { id: 'stadium', arch: 'sensor', band: 'ground', sit: 'derby', prio: 75, live: true, paint: 'stadium', aspect: 1.1, title: 'Derby egress: 4.6 people/m² building at Gate C', place: 'Avellaneda, Buenos Aires', lat: -34.6705, lon: -58.3685, ago: 1,
+      tele: () => 'GROUND · CROWD SENSING · GATE C · 4.6 P/M²' },
+    { id: 'aurora', arch: 'witness', band: 'inside', sit: 'aurora', prio: 74, by: 'ola', paint: 'aurora', aspect: 1.2, title: 'Corona overhead in Tromsø, sealed 18 minutes ago', place: 'Tromsø, Norway', lat: 69.65, lon: 18.96, ago: 18,
+      tele: () => 'WITNESS · SEALED · ±5 M · KP 6' },
+    { id: 'skychart', arch: 'track', band: 'orbit', sit: 'iss', prio: 72, paint: 'skychart', po: { at: iss.start, max: Math.round(iss.max) }, aspect: 1.0, title: `The ISS crosses your sky at ${fmt.hm(iss.maxAt)} UTC`, place: `Over ${GE.ME.name}`, lat: GE.ME.lat, lon: GE.ME.lon, ago: 0,
+      readout: `MAX ${Math.round(iss.max)}° · ${Math.round((iss.end - iss.start) / 60000)} MIN`, tele: () => 'ORBIT · ISS PASS · TLE · COMPUTED', cta: ['bell', 'Remind me'] },
+    { id: 'plume', arch: 'track', band: 'orbit', sit: 'launch', prio: 71, paint: 'plume', aspect: 1.3, title: 'Twilight launch: the plume was seen along 600 km of coast', place: 'Cape Canaveral', lat: 28.5618, lon: -80.5772, ago: 34,
+      readout: () => `T+${fmt.dur((Date.now() - GE.LAUNCH_T0) / 1000)}`, tele: () => 'ORBIT · TRACKING CAM · 2ND STAGE 212 KM' },
+    { id: 'room-qk', arch: 'room', band: 'inside', sit: 'quake', prio: 70, title: 'M 6.4 off Honshu', place: 'Fukushima · Miyagi · Ibaraki', lat: GE.BIGQ.lat, lon: GE.BIGQ.lon, ago: 3, ev: [['shake', {}], ['crossing', { seed: 33, cam: 'PHONE', rec: false }]] },
+    { id: 'gnss', arch: 'number', band: 'sky', sit: 'gnss', prio: 68, paint: 'gnss', aspect: 1.05, title: 'GPS interference over the Baltic', place: 'Baltic Sea', lat: 56.8, lon: 21.5, ago: 10,
+      big: '340', unit: 'aircraft', label: 'lost GPS integrity in the last hour', spark: [120, 160, 150, 210, 260, 240, 300, 340], tele: () => 'SKY · ADS-B NIC/NACp · 10 MIN' },
+    { id: 'heli', arch: 'track', band: 'sky', sit: 'novosel', prio: 66, live: true, paint: 'heli', po: { laps: 14 }, aspect: 1.1, title: 'HAWK 21 is flying its 14th circuit at Fort Novosel', place: 'Cairns Army Airfield, Alabama', lat: 31.276, lon: -85.713, ago: 0, ride: true,
+      readout: 'CIRCUIT 14 · 500 FT', tele: () => 'SKY · ADS-B/MLAT · 72 KT · 500 FT AGL', cta: ['helicopter', 'Ride along'] },
+    { id: 'koshi', arch: 'room', band: 'inside', sit: 'koshi', recon: 'koshi', prio: 64, wide: true, paint: 'globe', aspect: 0.56, title: 'Bhote Koshi outburst flood — 4D reconstruction', place: 'Rasuwa, Nepal · 26 Aug 2026', lat: 28.215, lon: 85.36, ago: 120 },
+    { id: 'sar', arch: 'sensor', band: 'orbit', sit: 'suez', prio: 62, paint: 'sar', aspect: 1.15, title: 'Radar satellite pass: 48 ships waiting off Suez', place: 'Gulf of Suez', lat: 29.86, lon: 32.55, ago: 47,
+      tele: () => 'ORBIT · SAR C-BAND · 10 M · DESC PASS' },
+    { id: 'volcano', arch: 'eye', band: 'ground', sit: 'sakurajima', prio: 60, live: true, paint: 'volcano', po: { cam: 'VOLCANO CAM 2', place: 'KAGOSHIMA BAY' }, aspect: 1.05, title: 'Sakurajima: ash column to 3.2 km, drifting away from the city', place: 'Kagoshima, Japan', lat: 31.58, lon: 130.66, ago: 2,
+      tele: () => `GROUND · VOLCANO CAM 2 · ${llz(31.58, 130.66)}` },
+    { id: 'blackout', arch: 'witness', band: 'inside', sit: 'cyclone', post: 'cy6', prio: 58, by: 'rafa', paint: 'blackout', aspect: 1.15, title: 'Aparri is dark — the hospital is running on generators', place: 'Aparri, Cagayan', lat: 18.357, lon: 121.637, ago: 22,
+      tele: () => 'WITNESS · SEALED · ±8 M · LOCAL' },
+  ];
+  for (const x of it) { x.at = NOW - x.ago * MIN3; x.dist = FD.distFromMe(x.lat, x.lon); }
+  return (FD._items = it);
+};
+FD.user = []; // your own posts land here (newest first)
+
+/* diversity-aware ordering: never two of the same archetype or band side by side when avoidable */
+FD.order = function (items) {
+  const rest = items.slice().sort((a, b) => b.prio - a.prio); const out = [];
+  while (rest.length) {
+    const prev = out[out.length - 1], prev2 = out[out.length - 2];
+    const fits = (x, strict) => !prev || ((x.arch !== prev.arch || !strict) && x.band !== prev.band && (!strict || !prev2 || x.arch !== prev2.arch));
+    let i = rest.findIndex((x) => fits(x, true)); if (i < 0) i = rest.findIndex((x) => fits(x, false)); if (i < 0) i = 0;
+    out.push(rest.splice(i, 1)[0]);
+  }
+  return out;
+};
+FD.list = function (band = 'all') {
+  const all = [...FD.user, ...FD.items()];
+  const f = band === 'all' ? all : band === 'near' ? all.filter((x) => x.dist < 2500) : all.filter((x) => x.band === band);
+  const user = f.filter((x) => x.mine); const ordered = FD.order(f.filter((x) => !x.mine));
+  return [...user, ...ordered];
+};
+FD.counts = function () { const c = { all: 0, orbit: 0, sky: 0, ground: 0, inside: 0 }; for (const x of [...FD.user, ...FD.items()]) { c.all++; c[x.band]++; } return c; };
+
 // ---- 60-shell.js
 /* Shell: tabs, Liquid-Glass tab bar with sliding lens, tab-bar accessory (followed situation),
    minimize-on-scroll, layout (phone / two-pane / hinge), overlay labels, toasts. */
@@ -3466,11 +4881,17 @@ APP.updateChrome = function () {
 
 /* ---------- accessory ---------- */
 APP.renderAccessory = function () {
-  const s = GE.SIT.byId[APP.following]; if (!s) return;
-  const html = `<span class="dot pulse"></span><span class="txt"><div class="ttl">${esc(GE.CYCLONE.name)}</div><div class="sub num">${esc(s.accessory ? s.accessory() : '')}</div></span><svg class="spk" width="54" height="22" viewBox="0 0 54 22">${sparkPath(GE.CYCLONE.track.slice(0, 7).map((x) => x[3]), 54, 22, '#FF6A3D')}</svg><span class="ab"><svg class="ic sm"><use href="#i-chevu"/></svg></span>`;
-  $('#acc').innerHTML = html;
-  $('#accMini').innerHTML = `<span class="dot pulse"></span><span class="txt"><div class="ttl">${esc(GE.CYCLONE.name)}</div><div class="sub num">${esc(s.accessory ? s.accessory() : '')}</div></span>`;
+  // the tab-bar accessory follows a person, not a number: the live witness you follow (or you, when live)
+  const me = GE.capture?.live; let ttl, sub, open;
+  if (me && me.on) { ttl = `You’re live · ${fmt.dur((Date.now() - me.t0) / 1000).slice(3)}`; sub = `Sealed live · ${me.segs.length} segments · ${fmt.n(me.viewers)} watching`; open = () => APP.setTab('capture'); }
+  else { const r = GE.rooms.byId.cyclone; const n = r ? r.watching : 3204; ttl = '@nadia_basco · Basco seawall'; sub = `Sealed live · Typhoon Halcyon room · ${fmt.n(n)} watching`; open = () => { const it = GE.feed.items().find((x) => x.id === 'basco'); GE.now._item = it; GE.sheet.open('cyclone', { post: 'cy1' }); }; }
+  APP._accOpen = open;
+  const html = `<span class="accdot"><span class="dot pulse"></span></span><span class="txt"><div class="ttl">${esc(ttl)}</div><div class="sub num">${esc(sub)}</div></span><canvas class="accv" width="120" height="68"></canvas><span class="ab"><svg class="ic sm"><use href="#i-chevu"/></svg></span>`;
+  const a = $('#acc'); if (a._k !== ttl + sub) { a.innerHTML = html; a._k = ttl + sub; }
+  const m = $('#accMini'); if (m._k !== ttl + sub) { m.innerHTML = `<span class="dot pulse"></span><span class="txt"><div class="ttl">${esc(ttl)}</div><div class="sub num">${esc(sub)}</div></span>`; m._k = ttl + sub; }
 };
+APP.accFrame = function () { const cv = $('#acc .accv'); if (!cv || $('#accHost').classList.contains('hidden')) return; const me = GE.capture?.live; if (me && me.on) GE.paint.draw('seawall', cv, { skyline: true, noOSD: true, seed: 53, t: performance.now() / 1000 }); else GE.paint.draw('seawall', cv, { palm: true, noOSD: true, seed: 52, t: performance.now() / 1000 }); };
+setInterval(() => { try { APP.accFrame(); } catch {} }, 200);
 function sparkPath(data, w, h, col, sw = 1.6) {
   const mn = Math.min(...data), mx = Math.max(...data), n = data.length;
   const pts = data.map((v, i) => [(i / (n - 1)) * (w - 4) + 2, h - 3 - ((v - mn) / (mx - mn || 1)) * (h - 6)]);
@@ -3491,6 +4912,8 @@ APP.updateLabels = function (view) {
     const short = s.short || s.title.split(/ [—–-] /)[0].slice(0, 28);
     want.push({ k: 's:' + s.id, lat: s.lat, lon: s.lon, alt: 0.2, pr: s.watchers, html: `<i style="--c:${GE.FAM[s.fam].color}"></i>${esc(short)}`, w: short.length * 6.6 + 32, cls: 'glass', onclick: () => GE.sheet.open(s.id, { fromGlobe: true }) });
   }
+  const showEyes = (APP.tab === 'globe' || APP.isWide()) && !APP.intro && APP.mode !== 'ride' && APP.mode !== 'workspace';
+  if (showEyes) for (const e of GE.EYES || []) { if (view.range > 0.9 && e.kind !== 'you') continue; const t = e.label + (e.live ? ' · LIVE' : ''); want.push({ k: 'e:' + e.id + (e.live ? 'L' : ''), lat: e.lat, lon: e.lon, alt: 0.05, pr: e.kind === 'you' ? 2e9 : 6e4, html: `<i class="ei k-${e.kind}"><svg class="ic xs"><use href="#i-${e.kind === 'cctv' ? 'video' : 'eye'}"/></svg></i>${esc(t)}`, w: t.length * 6.4 + 40, cls: 'glass eyelbl k-' + e.kind, onclick: () => { if (e.id === 'you' && GE.live.on) { APP.setTab('capture'); return; } if (e.sit) { const it = GE.feed.items().find((x) => x.post && x.post === e.post); GE.now._item = it || null; GE.sheet.open(e.sit, { post: e.post }); } } }); }
   if (GE.world.sel && GE.world.sel.v && APP.mode !== 'ride') want.push({ k: 'sel', v: GE.world.sel.v, pr: 1e9, html: `<b>${esc(GE.world.sel.title)}</b>`, w: 90, cls: 'plain tag' });
   for (const [k, l] of GE.extraLabels || []) want.push({ k, pr: 1e8, w: 120, ...l });
   want.sort((a, b) => b.pr - a.pr);
@@ -3525,7 +4948,7 @@ GE.extraLabels = new Map();
 /* ---------- wiring ---------- */
 APP.initShell = function () {
   $$('.tab').forEach((b) => b.addEventListener('click', () => APP.setTab(b.dataset.tab)));
-  const openFollowed = () => GE.sheet.open(APP.following);
+  const openFollowed = () => (APP._accOpen ? APP._accOpen() : GE.sheet.open(APP.following));
   $('#acc').addEventListener('click', openFollowed); $('#accMini').addEventListener('click', openFollowed);
   $('#btnSearch').addEventListener('click', () => GE.gui.openSearch());
   // minimize tab bar on scroll (feed-like views)
@@ -3605,74 +5028,140 @@ TH.fallback = function (s, canvas) {
 };
 
 /* ---------- feed ---------- */
+const BAND_ORDER = ['all', 'orbit', 'sky', 'ground', 'inside'];
+NOWV.band = store.get('band', 'all');
 const famIcon = (f) => GE.FAM[f].icon;
-function cardHTML(s) {
-  const c = GE.FAM[s.fam].color;
-  const [m, ml] = s.metric();
-  const badge = s.d4 ? `<span class="badge d4">4D</span><span class="badge replay">Thread</span>` : s.live ? `<span class="badge live"><span class="dot pulse"></span>Live</span>` : `<span class="badge replay">${s.replayLabel ? 'Replay · ' + s.replayLabel.replace('Today ', '') : 'Replay'}</span>`;
-  const right = s.thread ? `<span class="stack">${['tamang', 'hydro', 'kora', 'geo'].map((k) => `<span class="avatar sm" style="--h:${GE.PEOPLE[k].hue}">${GE.PEOPLE[k].h[0].toUpperCase()}</span>`).join('')}</span>` : `<span class="r">${ic('eye', 'xs')}<span class="num">${fmt.k(s.watchers)}</span></span>`;
-  return `<div class="thumb" style="aspect-ratio:${1}/${s.aspect}"><canvas width="360" height="${Math.round(360 * s.aspect)}"></canvas>
-    <div class="tl">${badge}</div><div class="tr" style="--c:${c}">${ic(famIcon(s.fam), 'sm')}</div>
-    <div class="bl"><div class="metric num" data-m>${m}</div><div class="mlabel num" data-ml>${ml}</div></div></div>
-    <div class="meta"><div class="ttl">${esc(s.title)}</div><div class="src"><span class="l"><span style="width:6px;height:6px;border-radius:50%;background:${c};flex:none"></span><span data-age>${esc(s.source)} · ${fmt.ago(Date.now() - s.updatedAt)}</span></span>${right}</div>
-    ${s.ride ? `<button class="cta" data-ride>${ic('helicopter', 'sm')}Jump into the chopper</button>` : ''}</div>`;
+const avatarHTML = (k, cls = 'sm') => { const p = GE.PEOPLE[k] || { h: k, hue: 205 }; return `<span class="avatar ${cls}" style="--h:${p.hue}">${esc((p.h || '?')[0].toUpperCase())}</span>`; };
+GE.avatarHTML = avatarHTML;
+const bandTag = (b) => `<span class="bt">${GE.BANDS[b].name.toUpperCase()}</span>`;
+function cvSize(x) { const W0 = x.wide ? 800 : 400; return [W0, Math.round(W0 * x.aspect)]; }
+function whereHTML(x) { const ago = x.live && x.ago < 1 ? 'LIVE NOW' : x.live ? `LIVE · ${fmt.ago(Date.now() - x.at).replace(' ago', '').toUpperCase()}` : fmt.ago(Date.now() - x.at).toUpperCase(); return `<div class="where"><div class="pl">${esc(x.place)}</div><div class="d mono">${x.dist < 60 ? 'NEAR YOU · ' : ''}${GE.feed.fmtDist(x.dist).toUpperCase()} AWAY · ${ago}</div></div>`; }
+function socHTML(x) {
+  const r = GE.rooms; const n = r.watching(x.sit); const posts = r.count(x.sit); const sealed = r.sealedCount(x.sit);
+  const ppl = (GE.rooms.byId[x.sit]?.posts || []).slice(0, 3).map((p) => p.by);
+  const stack = (ppl.length ? ppl : ['kora', 'sky', 'geo']).map((k) => avatarHTML(k)).join('');
+  return `<div class="soc">${x.wide ? `<span class="stack">${stack}</span>` : ''}<span>${ic('threads', 'xs')}<b class="num">${fmt.k(n)}</b> in room</span>${sealed ? `<span class="sl">${ic('seal', 'xs')}<b class="num">${sealed}</b> sealed</span>` : `<span><b class="num">${posts}</b> posts</span>`}</div>`;
+}
+function frameHTML(x, inner = '') {
+  const [w, h] = cvSize(x);
+  return `<div class="fr" style="aspect-ratio:${1}/${x.aspect}"><canvas width="${w}" height="${h}"></canvas><i class="bk a"></i><i class="bk b"></i><i class="bk c"></i><i class="bk d"></i>
+    <div class="ftop">${bandTag(x.band)}<span class="at">${GE.ARCH[x.arch].toUpperCase()}</span>${x.live ? '<span class="lv"><i></i>LIVE</span>' : ''}${x.mine ? '<span class="mine">YOU</span>' : ''}</div>
+    ${inner}${x.tele ? `<div class="tele" data-tele>${esc(x.tele())}</div>` : ''}</div>`;
+}
+function cardHTML(x) {
+  const B = GE.BANDS[x.band];
+  if (x.arch === 'room' && !x.recon) return roomCardHTML(x);
+  let inner = '';
+  if (x.arch === 'number') inner = `<div class="numov"><div class="big num">${x.big}<small>${esc(x.unit)}</small></div><div class="nl">${esc(x.label)}</div><svg class="nsp" viewBox="0 0 160 34" preserveAspectRatio="none">${GE.sparkPath(x.spark, 160, 34, B.c, 2)}</svg></div>`;
+  if (x.readout) inner += `<div class="readout num" data-ro>${esc(typeof x.readout === 'function' ? x.readout() : x.readout)}</div>`;
+  if (x.arch === 'witness') inner += `<svg class="fseal"><use href="#i-seal"/></svg>`;
+  if (x.recon) inner += `<div class="r4d"><span class="badge d4">4D</span><span class="badge">Reconstruction</span></div>`;
+  const who = x.by ? (() => { const p = GE.PEOPLE[x.by]; const room = GE.rooms.get(x.sit); const post = room?.posts.find((q) => q.id === x.post); const bd = post ? GE.rooms.badges(room, post).slice(0, 2) : []; return `<div class="who">${avatarHTML(x.by)}<b>@${esc(p.h)}</b>${bd.map(([k, l]) => `<span class="bdg ${k}">${esc(l)}</span>`).join('')}</div>`; })() : '';
+  const cta = x.cta ? `<button class="cta" data-cta>${ic(x.cta[0], 'sm')}${esc(x.cta[1])}</button>` : '';
+  const recon = x.recon ? `<div class="soc"><span><b class="num">23</b> observations</span><span><b class="num">9</b> hypotheses</span><span class="sl">${ic('link', 'xs')}ledger verified</span></div>` : socHTML(x);
+  return `${frameHTML(x, inner)}<div class="fm">${who}<div class="ttl">${esc(x.title)}</div>${whereHTML(x)}${recon}${cta}</div>`;
+}
+function roomCardHTML(x) {
+  const room = GE.rooms.get(x.sit); const syn = room.synth; const open = room.posts.find((p) => p.kind === 'question' && !p.answered);
+  const ppl = [...new Set(room.posts.map((p) => p.by))].slice(0, 5);
+  const line = (cls, lab, t, c) => t ? `<div class="cl ${cls}"><b>${lab}</b><span>${esc(t)}</span>${c ? `<span class="cites">${c.map((z) => `<i>${z}</i>`).join('')}</span>` : ''}</div>` : '';
+  const ev = (x.ev || []).map((e, i) => `<canvas class="evc" data-ev="${i}" width="200" height="150"></canvas>`).join('');
+  const sealed = room.posts.filter((p) => p.att && /^sealed/.test(p.att.tier)).length; const notes = room.posts.filter((p) => p.note).length;
+  return `<div class="rhead"><span class="rtag">${ic('threads', 'xs')}ROOM</span>${bandTag('inside')}<span class="lvw"><span class="dot pulse"></span><b class="num" data-watch>${fmt.n(room.watching)}</b> watching</span><span class="stack">${ppl.map((k) => avatarHTML(k)).join('')}</span></div>
+    <h3>${esc(x.title)}</h3>${whereHTML(x)}
+    <div class="claims">${line('known', 'KNOWN', syn.known[0]?.[0], syn.known[0]?.[1])}${line('disputed', 'DISPUTED', syn.disputed[0]?.[0], syn.disputed[0]?.[1])}${open ? line('open', 'ASKED', '“' + open.text + '”', null) : line('unknown', 'UNKNOWN', syn.unknown[0]?.[0], syn.unknown[0]?.[1])}</div>
+    ${ev ? `<div class="evs">${ev}</div>` : ''}
+    <div class="rfoot"><span><b class="num">${room.posts.length}</b> posts · <b class="num">${sealed}</b> sealed${notes ? ` · <b class="num">${notes}</b> note` : ''}</span><span class="join">Join the room ${ic('chevr', 'xs')}</span></div>`;
 }
 NOWV.render = function () {
-  const v = $('#v-now');
-  const now = new Date();
-  const kick = now.toLocaleDateString('en-GB', { weekday: 'long', day: 'numeric', month: 'long', timeZone: 'UTC' });
-  v.innerHTML = `<div class="navbar">Now</div>
+  const v = $('#v-now'); const now = new Date();
+  const kick = now.toLocaleDateString('en-GB', { weekday: 'short', day: 'numeric', month: 'short', timeZone: 'UTC' }).toUpperCase();
+  v.innerHTML = `<div class="navbar"><span class="wm">GOD’S EYE</span></div>
   <div class="now-hero">
-    <div class="lt"><div class="kicker"><span class="dot pulse"></span><span>${kick}</span>·<span class="num" id="nowClock">${fmt.hm(Date.now())} UTC</span></div>
-      <div class="row"><h1>Now</h1><button class="avatar md" style="--h:205" aria-label="You" id="nowMe">Y</button></div></div>
-    <div class="livebar"><span><b class="num" id="cSit">${GE.SIT.list.length}</b> situations</span><span><b class="num" id="cAir">–</b> aircraft</span><span><b class="num" id="cShip">–</b> vessels</span><span><b class="num" id="cSat">${fmt.n(GE.SATS.length)}</b> satellites</span></div>
+    <div class="hud"><span class="wm">GOD’S&nbsp;EYE</span><i class="hb a"></i><i class="hb b"></i><i class="hb c"></i><i class="hb d"></i><i class="xh"></i><div class="hud-t mono" id="heroTele"></div></div>
+    <div class="lt"><div class="kicker mono"><span class="dot pulse"></span><span>LIVE · ${kick} · <span class="num" id="nowClock">${GE.feed.hmsZ()}</span></span></div>
+      <div class="row"><h1>Right now, at every altitude.</h1><button class="avatar md" style="--h:205" aria-label="You" id="nowMe">Y</button></div>
+      <div class="counts mono"><span><b class="num" id="cAir">–</b> aircraft</span><span><b class="num" id="cShip">–</b> vessels</span><span><b class="num">${fmt.n(GE.SATS.length)}</b> satellites</span><span><b class="num">408</b> cameras</span><span class="w"><b class="num" id="cWit">14</b> witnesses live</span></div></div>
   </div>
-  <div class="now-body"><div class="chips" id="nowChips">
-    ${[['all', 'For you'], ['now', 'Happening now'], ['near', 'Near you'], ['recon', 'Reconstructions'], ['always', 'Always on']].map(([k, l]) => `<button class="chip ${NOWV.filter === k ? 'on' : ''}" data-f="${k}">${l}</button>`).join('')}
-  </div><div id="nowSecs"></div></div>`;
+  <div class="now-body"><div class="bandrail" id="bandRail" role="tablist" aria-label="Altitude"></div><div id="feed"></div><div class="feed-end mono">${ic('sparkles', 'xs')} CONCEPT · ILLUSTRATIVE DATA · PEOPLE AND POSTS ARE FICTIONAL</div></div>`;
   $('#nowMe').addEventListener('click', () => APP.setTab('you'));
-  $$('#nowChips .chip').forEach((b) => b.addEventListener('click', () => { NOWV.filter = b.dataset.f; $$('#nowChips .chip').forEach((x) => x.classList.toggle('on', x === b)); NOWV.renderSections(); haptic(4); }));
-  NOWV.renderSections();
+  NOWV.renderRail(); NOWV.renderFeed();
 };
-NOWV.renderSections = function () {
-  const host = $('#nowSecs'); host.innerHTML = '';
-  for (const sec of GE.SIT.sections) {
-    if (NOWV.filter !== 'all' && NOWV.filter !== sec.id) continue;
-    const items = GE.SIT.list.filter((s) => s.section === sec.id);
-    const hd = h('div', { class: 'sec-h' }, h('h2', null, sec.title), h('span', null, sec.sub));
-    const grid = h('div', { class: 'masonry' }); const cols = [h('div', { class: 'col' }), h('div', { class: 'col' })]; grid.append(...cols);
-    const hs = [0, 0];
-    for (const s of items) {
-      const el = h('article', { class: 'card', 'data-id': s.id, tabindex: 0, role: 'button', 'aria-label': s.title }); el.innerHTML = cardHTML(s);
-      const ci = hs[0] <= hs[1] ? 0 : 1; cols[ci].append(el); hs[ci] += s.aspect + 0.62;
-      el.addEventListener('click', (e) => { if (e.target.closest('[data-ride]')) { e.stopPropagation(); NOWV.open(s, el, { ride: true }); return; } NOWV.open(s, el); });
-      el.addEventListener('keydown', (e) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); NOWV.open(s, el); } });
-      const cv = el.querySelector('canvas');
-      const cached = TH.done.get(s.id);
-      if (cached) cv.getContext('2d').drawImage(cached, 0, 0);
-      else { TH.fallback(s, cv); TH.enqueue(() => { const c2 = document.createElement('canvas'); c2.width = cv.width; c2.height = cv.height; TH.renderSituation(s, c2); TH.done.set(s.id, c2); $$(`.card[data-id="${s.id}"] canvas, .tcard[data-id="${s.id}"] canvas`).forEach((x) => { const xc = x.getContext('2d'); xc.drawImage(c2, 0, 0, x.width, x.height); }); }); }
-    }
-    host.append(hd, grid);
+NOWV.renderRail = function () {
+  const c = GE.feed.counts();
+  $('#bandRail').innerHTML = BAND_ORDER.map((b) => { const B = GE.BANDS[b]; return `<button class="bcell ${NOWV.band === b ? 'on' : ''}" data-b="${b}" role="tab" aria-selected="${NOWV.band === b}" style="--c:${B ? B.c : '#E8EEF8'}"><i></i><b>${b === 'all' ? 'ALL' : B.name.toUpperCase()}</b><span class="num">${c[b]}</span><em>${b === 'all' ? 'orbit → you' : esc(B.alt)}</em></button>`; }).join('<span class="rarr"></span>');
+  $$('#bandRail .bcell').forEach((el) => el.addEventListener('click', () => { NOWV.band = el.dataset.b; store.set('band', NOWV.band); NOWV.renderRail(); NOWV.renderFeed(); haptic(5); const v = $('#v-now'); const r = $('#bandRail'); if (v.scrollTop > r.offsetTop) v.scrollTo({ top: r.offsetTop - 4, behavior: 'smooth' }); }));
+};
+NOWV.cardEl = function (x) {
+  const el = h('article', { class: `card fc a-${x.arch} b-${x.band}${x.wide ? ' wide' : ''}${x.arch === 'room' && !x.recon ? ' room' : ''}${x.mine ? ' mine' : ''}`, 'data-fid': x.id, 'data-id': x.sit, tabindex: 0, role: 'button', 'aria-label': x.title, style: `--c:${GE.BANDS[x.band].c}` });
+  el.innerHTML = cardHTML(x);
+  const go = (e) => { if (e && e.target.closest('[data-cta]')) { e.stopPropagation(); if (x.ride) { NOWV.open(GE.SIT.byId[x.sit], el, { ride: true }); return; } if (x.cta[0] === 'bell') { APP.toast(`${ic('bell', 'sm')} Reminder set · 5 min before the pass`); return; } } NOWV.openItem(x, el); };
+  el.addEventListener('click', go); el.addEventListener('keydown', (e) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); go(); } });
+  // paint
+  const cv = el.querySelector('.fr canvas');
+  if (cv) NOWV.paint(x, cv);
+  el.querySelectorAll('canvas.evc').forEach((c) => { const [id, o] = x.ev[+c.dataset.ev]; TH.enqueue(() => GE.paint.draw(id, c, { ...o, t: 2 + +c.dataset.ev })); });
+  return el;
+};
+NOWV.paint = function (x, cv) {
+  if (x.img) { const im = new Image(); im.onload = () => { const cx = cv.getContext('2d'); const s = Math.max(cv.width / im.width, cv.height / im.height); cx.drawImage(im, (cv.width - im.width * s) / 2, (cv.height - im.height * s) / 2, im.width * s, im.height * s); }; im.src = x.img; return; }
+  if (x.paint === 'globe') { const s = GE.SIT.byId[x.sit]; const cached = TH.done.get(s.id); if (cached) cv.getContext('2d').drawImage(cached, 0, 0, cv.width, cv.height); else { TH.fallback(s, cv); TH.enqueue(() => { const c2 = document.createElement('canvas'); c2.width = cv.width; c2.height = cv.height; TH.renderSituation(s, c2); TH.done.set(s.id, c2); $$(`[data-id="${s.id}"] .fr canvas`).forEach((z) => z.getContext('2d').drawImage(c2, 0, 0, z.width, z.height)); }); } return; }
+  const key = x.id + '|' + cv.width; const done = NOWV.painted.get(key);
+  const cx = cv.getContext('2d'); cx.fillStyle = '#06080c'; cx.fillRect(0, 0, cv.width, cv.height);
+  if (GE.paint.animated(x.paint)) { NOWV.anim.set(cv, x); TH.enqueue(() => GE.paint.draw(x.paint, cv, { ...x.po, t: performance.now() / 1000 })); return; }
+  if (done) { cx.drawImage(done, 0, 0); return; }
+  TH.enqueue(() => { if (!GE.paint.draw(x.paint, cv, { ...x.po })) return; const c2 = GE.paint.mk(cv.width, cv.height); c2.getContext('2d').drawImage(cv, 0, 0); NOWV.painted.set(key, c2); });
+};
+NOWV.painted = new Map(); NOWV.anim = new Map(); NOWV.vis = new Set();
+NOWV.renderFeed = function () {
+  const host = $('#feed'); if (!host) return; host.innerHTML = ''; NOWV.anim.clear();
+  const list = GE.feed.list(NOWV.band);
+  if (NOWV.band !== 'all') { const B = GE.BANDS[NOWV.band]; host.append(h('div', { class: 'band-h', style: `--c:${B.c}`, html: `<b>${B.name}</b><span>${esc(B.alt)} · ${esc(B.sensor)}</span>` })); }
+  let grid = null, cols = null, hs = [0, 0];
+  const flush = () => { grid = null; };
+  for (const x of list) {
+    const el = NOWV.cardEl(x);
+    if (x.wide) { flush(); host.append(el); continue; }
+    if (!grid) { grid = h('div', { class: 'masonry' }); cols = [h('div', { class: 'col' }), h('div', { class: 'col' })]; grid.append(...cols); host.append(grid); hs = [0, 0]; }
+    const ci = hs[0] <= hs[1] ? 0 : 1; cols[ci].append(el); hs[ci] += (x.aspect || 0.9) + (x.arch === 'number' ? 0.5 : 0.62) + (x.by ? 0.16 : 0) + (x.cta ? 0.2 : 0);
   }
+  NOWV.observe();
+};
+NOWV.observe = function () {
+  if (!('IntersectionObserver' in window)) { NOWV.anim.forEach((x, cv) => NOWV.vis.add(cv)); return; }
+  NOWV.io && NOWV.io.disconnect(); NOWV.vis.clear();
+  NOWV.io = new IntersectionObserver((es) => { for (const e of es) { const cv = e.target; if (e.isIntersecting) NOWV.vis.add(cv); else NOWV.vis.delete(cv); } }, { root: $('#v-now'), rootMargin: '80px' });
+  NOWV.anim.forEach((x, cv) => NOWV.io.observe(cv));
+};
+// animated eyes: CCTV and live scenes redraw at ~8 fps while visible
+NOWV.animate = function () {
+  if (APP.tab !== 'now' || APP.mode || APP.intro) return; const t = performance.now() / 1000;
+  for (const cv of NOWV.vis) { const x = NOWV.anim.get(cv); if (!x) continue; GE.paint.draw(x.paint, cv, { ...x.po, t }); }
+};
+setInterval(() => { try { NOWV.animate(); } catch (e) { console.warn(e); } }, 125);
+NOWV.openItem = function (x, el) {
+  if (x.recon) { APP.setTab('threads'); GE.threads.openWs(x.recon); return; }
+  const s = GE.SIT.byId[x.sit]; NOWV._item = x;
+  if (x.arch === 'room') { GE.sheet.open(x.sit, { post: x.post }); return; }
+  NOWV.open(s, el, { cam: x.cam, post: x.post, seg: x.arch === 'number' || (x.arch === 'sensor' && !x.post) ? 'room' : 'room' });
 };
 NOWV.tick = function () {
   const W = GE.world;
   const c = W.counts; const air = (c.flights || 0) + (c.military || 0) + (c.ga || 0) + GE.HELI_CIRCUITS.length;
   const a = $('#cAir'); if (a) a.textContent = fmt.n(air);
   const sh = $('#cShip'); if (sh) sh.textContent = fmt.n(GE.SHIPS.length);
-  const ck = $('#nowClock'); if (ck) ck.textContent = fmt.hm(Date.now()) + ' UTC';
-  for (const el of $$('.card[data-id]')) {
-    const s = GE.SIT.byId[el.dataset.id]; if (!s) continue;
-    const [m, ml] = s.metric(); const me = el.querySelector('[data-m]'), mle = el.querySelector('[data-ml]');
-    if (me && me.innerHTML !== m) { me.innerHTML = m; } if (mle && mle.innerHTML !== ml) mle.innerHTML = ml;
-    const ag = el.querySelector('[data-age]'); if (ag) ag.textContent = `${s.source} · ${fmt.ago(Date.now() - s.updatedAt)}`;
-  }
+  const ck = $('#nowClock'); if (ck) ck.textContent = GE.feed.hmsZ();
+  const ht = $('#heroTele'); if (ht && GE.mainView) { const v = GE.mainView; const [la, lo, alt] = geo.ll(v.eye); ht.textContent = `ORBIT · ALT ${fmt.n(Math.round(alt))} KM · NADIR ${GE.feed.llz(la, lo)} · TERMINATOR ${W.sun.lat >= 0 ? 'N' : 'S'} · ${GE.feed.hmsZ()}`; }
+  if (APP.tab !== 'now') return;
+  const items = new Map([...GE.feed.user, ...GE.feed.items()].map((x) => [x.id, x]));
+  for (const el of $$('#feed .fc[data-fid]')) { const x = items.get(el.dataset.fid); if (!x) continue; const t = el.querySelector('[data-tele]'); if (t && x.tele) { const s2 = x.tele(); if (t.textContent !== s2) t.textContent = s2; } const ro = el.querySelector('[data-ro]'); if (ro && typeof x.readout === 'function') ro.textContent = x.readout(); const w = el.querySelector('[data-watch]'); if (w) { const r = GE.rooms.byId[x.sit]; if (r) w.textContent = fmt.n(r.watching); } }
 };
+GE.rooms.drift = setInterval(() => { for (const r of Object.values(GE.rooms.byId)) r.watching += Math.round((Math.random() - 0.42) * r.rate * 3); }, 2000);
 
 /* ---------- hero morph: card → live globe ---------- */
 NOWV.open = function (s, cardEl, o = {}) {
   const wide = APP.isWide();
-  const thumb = cardEl?.querySelector('.thumb canvas');
+  const thumb = cardEl?.querySelector('.fr canvas') || cardEl?.querySelector('.evc');
   if (wide || !thumb || prefersReduced()) { GE.sheet.open(s.id, { ...o, fade: !wide }); return; }
   const r = thumb.getBoundingClientRect(); const app = $('#app').getBoundingClientRect();
   const M = $('#morph'); M.innerHTML = ''; const cv = document.createElement('canvas'); cv.width = thumb.width; cv.height = thumb.height; cv.getContext('2d').drawImage(thumb, 0, 0); M.append(cv);
@@ -3692,9 +5181,9 @@ NOWV.open = function (s, cardEl, o = {}) {
   }));
 };
 NOWV.foldBack = function (id) {
-  const cardEl = $(`#v-now .card[data-id="${id}"]`); const M = $('#morph');
+  const cardEl = (NOWV._morphCard && document.body.contains(NOWV._morphCard) && NOWV._morphCard.dataset.id === id) ? NOWV._morphCard : $(`#v-now .card[data-id="${id}"]`); const M = $('#morph');
   if (!cardEl || prefersReduced() || APP.isWide()) return false;
-  const thumb = cardEl.querySelector('.thumb canvas'); const app = $('#app').getBoundingClientRect();
+  const thumb = cardEl.querySelector('.fr canvas') || cardEl.querySelector('.evc'); if (!thumb) return false; const app = $('#app').getBoundingClientRect();
   M.innerHTML = ''; const cv = document.createElement('canvas'); cv.width = thumb.width; cv.height = thumb.height; cv.getContext('2d').drawImage(thumb, 0, 0); M.append(cv);
   const tw = app.width, th = app.height * 0.57;
   Object.assign(M.style, { left: '0px', top: '0px', width: tw + 'px', height: th + 'px', transformOrigin: '0 0', transition: 'none', transform: 'none', borderRadius: '0px', opacity: '0' });
@@ -3713,7 +5202,7 @@ NOWV.foldBack = function (id) {
 /* Situation sheet: detents (peek / medium / large), drag with velocity snapping, the world always
    wins (touching the globe collapses to peek). Tufte-grade brief: direct-labelled sparklines with
    uncertainty, small multiples rendered from the globe, evidence strip, every number sourced + aged. */
-const SH = (GE.sheet = { id: null, detent: 'medium' });
+const SH = (GE.sheet = { id: null, detent: 'medium', seg: 'room' });
 const sheetEl = () => $('#sheet');
 SH.heights = function () {
   const H = $('#app').clientHeight; const sab = parseFloat(getComputedStyle(document.documentElement).getPropertyValue('--sab')) || 0;
@@ -3731,7 +5220,7 @@ SH.setDetent = function (d, animate = true) {
 SH.open = function (id, o = {}) {
   const s = GE.SIT.byId[id]; if (!s) return;
   const W = GE.world;
-  SH.id = id; SH.sit = s;
+  SH.fromTab = APP.mode === 'situation' ? SH.fromTab : APP.tab; SH.id = id; SH.sit = s; SH.opts = o; SH.seg = o.seg || 'room';
   if (APP.tab !== 'globe' && !APP.isWide()) { APP.tab = 'globe'; $('#app').dataset.tab = 'globe'; $$('.tab').forEach((b) => b.classList.toggle('on', b.dataset.tab === 'globe')); $$('.pane .view').forEach((v) => v.classList.remove('on')); APP.moveLens(); }
   APP.setMode('situation');
   // layers & time window
@@ -3740,9 +5229,9 @@ SH.open = function (id, o = {}) {
   bus.emit('layers', W.layers);
   if (s.time) { W.setWindow({ start: s.time.start ?? s.time.at - 6 * 3600000, end: s.time.end ?? s.time.at + 6 * 3600000 }); W.setTime(s.time.at); }
   W.auroraK = s.auroraK ?? 0.85;
-  GE.setExtras && GE.setExtras(s.id); GE.setLabels3d(s.thread ? GE.threads.data[s.thread].labels : s.labels3d);
+  GE.setExtras && GE.setExtras(s.id); GE.setLabels3d(s.thread ? GE.threads.data[s.thread].labels : s.labels3d); GE.roomUI.labels(s, o.post);
   // camera
-  const cam = GE.SIT.cameraFor(s);
+  const cam = o.cam || GE.SIT.cameraFor(s);
   const hs = SH.heights();
   const shiftY = APP.isWide() ? 0 : hs.medium / hs.H;
   SH.targetShift = shiftY;
@@ -3760,13 +5249,14 @@ SH.open = function (id, o = {}) {
 SH.close = function (silent, keepTime) {
   if (!SH.id) return; const id = SH.id; const W = GE.world;
   const el = sheetEl(); el.classList.remove('drag', 'wopen'); el.style.transform = APP.isWide() ? '' : 'translateY(100%)';
-  SH.id = null; W.focus = null; GE.setExtras && GE.setExtras(null); GE.setLabels3d(null);
+  SH.id = null; W.focus = null; GE.setExtras && GE.setExtras(null); GE.setLabels3d(null); GE.roomUI.composer(false);
   if (SH._savedLayers) { W.layers.forEach((l, i) => (l.on = SH._savedLayers[i])); SH._savedLayers = null; bus.emit('layers', W.layers); }
   if (!keepTime) { W.setWindow(null); W.setTime(null); } W.auroraK = 0.85;
   APP.setMode('');
   if (silent) return;
   const fromNow = !APP.isWide() && GE.now && $(`#v-now .card[data-id="${id}"]`);
-  if (fromNow) { APP.setTab('now', { force: true }); requestAnimationFrame(() => GE.now.foldBack(id)); }
+  if (SH.fromTab === 'threads' || SH.fromTab === 'you') APP.setTab(SH.fromTab, { force: true });
+  else if (fromNow) { APP.setTab('now', { force: true }); requestAnimationFrame(() => GE.now.foldBack(id)); }
   else { Cam.flyTo({ range: Math.max(Cam.range * 3, 0.6), shiftY: APP.isWide() ? 0 : 0.06, tilt: 0 }); }
 };
 
@@ -3839,8 +5329,26 @@ function barsSVG(items, w) {
   items.forEach(([k, v], i) => { const y = i * 22; s += `<text x="0" y="${y + 14}" font-size="12" fill="rgba(232,238,248,.75)" font-family="var(--font)">${k}</text><rect x="92" y="${y + 6}" width="${(w - 132) * v}" height="10" rx="3" fill="rgba(124,196,255,.55)"/><text x="${92 + (w - 132) * v + 6}" y="${y + 15}" font-size="11" fill="rgba(232,238,248,.55)" font-family="var(--font)">${Math.round(v * 100)}</text>`; });
   return `<svg viewBox="0 0 ${w} ${hgt}" width="${w}" height="${hgt}">${s}</svg>`;
 }
+const bandOfSit = (s) => (GE.now?._item?.sit === s.id ? GE.now._item.band : { orbit: 'orbit', sky: 'sky', wx: 'sky', eyes: 'ground' }[s.fam] || 'ground');
 SH.render = function (s) {
-  const c = GE.FAM[s.fam].color; const el = $('#sheetC');
+  const el = $('#sheetC'); const b = bandOfSit(s); const B = GE.BANDS[b]; const room = GE.rooms.get(s.id);
+  const live = s.live ? `<span class="badge live"><span class="dot pulse"></span>Live</span>` : s.d4 ? `<span class="badge d4">4D</span>` : `<span class="badge replay">Replay</span>`;
+  const ppl = [...new Set(room.posts.map((p) => p.by))].slice(0, 5);
+  el.innerHTML = `<div class="sh-hd"><div class="t"><div class="tags" style="--c:${B.c}"><span class="bt">${B.name.toUpperCase()}</span>${live}<span class="age num" data-sage>${fmt.ago(Date.now() - s.updatedAt)}</span></div>
+    <h2>${esc(s.title)}</h2><div class="pl">${esc(s.place)} · <span class="mono">${fmt.ll(s.lat, s.lon, 2)}</span> · <b>${GE.feed.fmtDist(GE.feed.distFromMe(s.lat, s.lon))}</b> from you</div></div></div>
+    <div class="presence-row"><span class="stack">${ppl.map((k) => GE.avatarHTML(k)).join('')}</span><span><b class="num" data-watch>${fmt.n(room.watching)}</b> watching</span><span class="rate">${room.rate} posts/min</span></div>
+    <div class="seg2" id="shSegs"><button data-seg="room" class="${SH.seg === 'room' ? 'on' : ''}">${ic('threads', 'xs')}Room <span class="num">${room.posts.length}</span></button><button data-seg="brief" class="${SH.seg === 'brief' ? 'on' : ''}">${ic('signal', 'xs')}Brief &amp; sources</button></div>
+    <div id="shSeg"></div>`;
+  el.querySelectorAll('[data-seg]').forEach((bt) => bt.addEventListener('click', () => { SH.seg = bt.dataset.seg; el.querySelectorAll('[data-seg]').forEach((x) => x.classList.toggle('on', x === bt)); SH.renderSeg(s); haptic(4); }));
+  SH.renderSeg(s);
+};
+SH.renderSeg = function (s) {
+  const host = $('#shSeg'); GE.roomUI.composer(SH.seg === 'room');
+  if (SH.seg === 'room') { GE.roomUI.render(host, s, { post: SH.opts?.post }); return; }
+  SH.renderBrief(s, host);
+};
+SH.renderBrief = function (s, el) {
+  const c = GE.FAM[s.fam].color;
   const ms = s.metrics();
   const live = s.live ? `<span class="badge live"><span class="dot pulse"></span>Live</span>` : s.d4 ? `<span class="badge d4">4D</span>` : `<span class="badge replay">Replay</span>`;
   const acts = [
@@ -3851,8 +5359,6 @@ SH.render = function (s) {
   ].join('');
   const b = s.brief || {};
   el.innerHTML = `
-  <div class="sh-hd"><div class="t"><div style="display:flex;gap:6px;align-items:center"><span class="badge fam" style="--c:${c}"><i></i>${GE.FAM[s.fam].name}</span>${live}<span style="font-size:12px;color:var(--text3)" class="num" data-sage>${fmt.ago(Date.now() - s.updatedAt)}</span></div>
-    <h2>${esc(s.title)}</h2><div class="pl">${esc(s.place)} · <span class="mono">${fmt.ll(s.lat, s.lon, 2)}</span></div></div></div>
   <div class="metrics" id="shMetrics">${ms.map((m) => `<div class="metric"><div class="v">${m.v}<small>${m.u}</small></div><div class="l">${m.l}</div><div class="s">${m.s}</div></div>`).join('')}</div>
   <div class="acts sh-acts">${acts}</div>
   <div class="brief">
@@ -4046,7 +5552,10 @@ GUI.drawRibbon = function () {
   el.classList.toggle('future', cur > 0.02 && !W.window);
   el.classList.toggle('breath', W.live && !prefersReduced());
   const nb = $('#rbNow'); nb.classList.toggle('live', W.live); nb.innerHTML = W.window ? `${ic('clock', 'xs')}EVENT` : W.live ? '<span class="dot pulse"></span>LIVE' : 'NOW';
-  const stt = $('#statusTxt'); if (stt) { stt.textContent = W.window ? 'Replay' : W.live ? 'Live' : cur > 0 ? 'Forecast' : 'Replay'; $('#statusTime').textContent = fmt.utc(simMs, false) + ' UTC'; $('#status .dot').style.background = W.live ? '' : cur > 0 ? 'var(--wx)' : 'var(--gold)'; }
+  const stt = $('#statusTxt'); if (stt) {
+    const alt = (GE.mainView ? geo.ll(GE.mainView.eye)[2] : Cam.range * EARTH_KM); const band = alt > 120 ? 'ORBIT' : alt > 0.8 ? 'SKY' : 'GROUND'; const bc = { ORBIT: 'var(--b-orbit)', SKY: 'var(--b-sky)', GROUND: 'var(--b-ground)' }[band];
+    if (GE.live && GE.live.on) { stt.innerHTML = `You’re live · <b class="num">${fmt.dur((Date.now() - GE.live.t0) / 1000).slice(3)}</b>`; $('#statusTime').textContent = 'return'; $('#status .dot').style.background = ''; }
+    else { stt.innerHTML = `${W.window ? 'Replay' : W.live ? 'Live' : cur > 0 ? 'Forecast' : 'Replay'} <span class="alt mono" style="color:${bc}">${band} · ${alt >= 10 ? fmt.n(Math.round(alt)) + ' KM' : alt >= 1 ? alt.toFixed(1) + ' KM' : fmt.n(Math.round(alt * 1000)) + ' M'}</span>`; $('#statusTime').textContent = fmt.utc(simMs, false) + ' UTC'; $('#status .dot').style.background = W.live ? '' : cur > 0 ? 'var(--wx)' : 'var(--gold)'; } }
 };
 GUI.pips = function () {
   const nowMs = Date.now(); const W = GE.world;
@@ -4127,7 +5636,7 @@ GUI.init = function () {
   $('#btnLens').addEventListener('click', () => { const ids = LENSES.map((l) => l[0]); const i = (ids.indexOf(GE.world.lens) + 1) % ids.length; GE.world.setLens(ids[i]); APP.toast(`${ic('sparkles', 'sm')} ${LENSES[i][1]} lens`); $('#btnLens').classList.toggle('on', ids[i] !== 'cinematic'); });
   $('#btnHome').addEventListener('click', () => { GUI.showPick(null); Cam.flyTo({ range: 2.6, tilt: 0, heading: 0, shiftY: APP.isWide() ? 0 : 0.06 }); });
   $('#btnCompass').addEventListener('click', () => Cam.flyTo({ heading: 0, tilt: 0 }, { duration: 0.8 }));
-  $('#status').addEventListener('click', () => GUI.snapNow());
+  $('#status').addEventListener('click', () => { if (GE.live && GE.live.on) { APP.setTab('capture'); return; } GUI.snapNow(); });
 };
 
 // ---- 64-ride.js
@@ -4279,32 +5788,42 @@ CAP.enter = function () {
   CAP.render();
   KEY.get();
 };
-CAP.exit = function () { if (!CAP.on) return; CAP.on = false; GE.renderOverride = null; Cam.setRig(null); Cam.rigBlend = 1; $('#sealOv').classList.remove('on'); };
+CAP.exit = function () { if (!CAP.on) return; CAP.on = false; CAP.cover = false; GE.renderOverride = null; Cam.setRig(null); Cam.rigBlend = 1; $('#sealOv').classList.remove('on'); };
+CAP.MODES = [['look', 'Look'], ['witness', 'Witness'], ['live', 'Live'], ['upload', 'Upload']];
+CAP.setMode = function (m) { if (CAP.mode === 'live' && m !== 'live' && CAP.live?.on) { APP.toast(`${ic('live', 'sm')} End the broadcast first`); return; } CAP.mode = m; if (CAP.on) CAP.render(); };
 CAP.render = function () {
-  const el = $('#v-capture'); const last = GE.captures[GE.captures.length - 1];
-  el.innerHTML = `<div class="cap-ui">
+  const el = $('#v-capture'); const last = GE.captures[GE.captures.length - 1]; const m = CAP.mode;
+  const rt = CAP.replyTo && GE.SIT.byId[CAP.replyTo.sit];
+  CAP.cover = m === 'live';
+  el.innerHTML = `<canvas class="livecv ${m === 'live' ? 'on' : ''}" id="liveCv"></canvas><div class="cap-ui m-${m}">
     <svg class="compass-tape" id="ctape"></svg>
     <div class="callouts" id="callouts"></div>
-    <div class="cap-top"><span class="st glass">${ic('location', 'xs')}<span>Simulated camera · ${SPOT.name}</span></span><span class="st glass" id="capMode">${CAP.mode === 'look' ? `${ic('eye', 'xs')}Look · AR` : `${ic('key', 'xs')}Witness · signing`}</span></div>
-    <div class="sensors glass ${CAP.mode === 'witness' ? 'on' : ''}" id="sensors"></div>
+    <div class="cap-top"><span class="st glass">${ic('location', 'xs')}<span>Simulated camera · ${SPOT.name}</span></span><span class="st glass" id="capMode">${{ look: `${ic('eye', 'xs')}Look · AR`, witness: `${ic('key', 'xs')}Witness · signing`, live: `${ic('live', 'xs')}Live · sealed every 10 s`, upload: `${ic('gallery', 'xs')}Upload · unverified` }[m]}</span></div>
+    ${rt ? `<div class="replyto glass">${ic('threads', 'xs')}<span>Replying in <b>${esc(rt.short || rt.title.split(' — ')[0])}</b></span><button id="rtX" aria-label="Cancel reply">${ic('x', 'xs')}</button></div>` : ''}
+    <div class="sensors glass ${m === 'witness' ? 'on' : ''}" id="sensors"></div>
+    <div id="modeHost"></div>
     <div class="cap-bottom">
-      <div class="zooms glass">${[0.5, 1, 3].map((z) => `<button data-z="${z}" class="${CAP.zoom === z ? 'on' : ''}">${z === 0.5 ? '.5' : z}×</button>`).join('')}</div>
-      <div class="dial" id="dial"><button data-m="look" class="${CAP.mode === 'look' ? 'on' : ''}">Look</button><button data-m="witness" class="${CAP.mode === 'witness' ? 'on' : ''}">Witness</button></div>
+      ${m === 'look' || m === 'witness' ? `<div class="zooms glass">${[0.5, 1, 3].map((z) => `<button data-z="${z}" class="${CAP.zoom === z ? 'on' : ''}">${z === 0.5 ? '.5' : z}×</button>`).join('')}</div>` : ''}
+      <div class="dial" id="dial">${CAP.MODES.map(([k, l]) => `<button data-m="${k}" class="${m === k ? 'on' : ''}">${l}</button>`).join('')}</div>
       <div class="shutrow"><button class="lastcap" id="lastcap" aria-label="Last capture" style="${last ? `background-image:url(${last.thumb})` : ''}">${last ? '<svg class="seal"><use href="#i-seal"/></svg>' : ''}</button>
-        <button class="shutter ${CAP.mode === 'look' ? 'look' : ''}" id="shutter" aria-label="${CAP.mode === 'look' ? 'Switch to Witness' : 'Capture and sign'}"><i></i></button>
-        <button class="circ glass" id="capFlip" aria-label="Layers in view">${ic('layers')}</button></div>
+        <button class="shutter s-${m} ${CAP.live?.on ? 'rec' : ''}" id="shutter" aria-label="${{ look: 'Switch to Witness', witness: 'Capture and sign', live: CAP.live?.on ? 'End broadcast' : 'Go live', upload: 'Choose a file' }[m]}"><i></i></button>
+        <button class="circ glass" id="capFlip" aria-label="${m === 'live' ? 'See yourself on the globe' : 'Layers in view'}">${ic(m === 'live' ? 'globe' : 'layers')}</button></div>
     </div></div>`;
   el.querySelectorAll('[data-z]').forEach((b) => b.addEventListener('click', () => { CAP.zoom = +b.dataset.z; CAP.syncZoom(); haptic(4); }));
-  el.querySelectorAll('[data-m]').forEach((b) => b.addEventListener('click', () => { CAP.mode = b.dataset.m; CAP.render(); haptic(6); }));
-  $('#shutter').addEventListener('click', () => { if (CAP.mode === 'look') { CAP.mode = 'witness'; CAP.render(); return; } CAP.shoot(); });
+  el.querySelectorAll('[data-m]').forEach((b) => b.addEventListener('click', () => { CAP.setMode(b.dataset.m); haptic(6); }));
+  $('#rtX')?.addEventListener('click', () => { CAP.replyTo = null; CAP.render(); });
+  $('#shutter').addEventListener('click', () => { if (m === 'look') { CAP.setMode('witness'); return; } if (m === 'witness') CAP.shoot(); if (m === 'live') (CAP.live?.on ? GE.live.stop() : GE.live.start()); if (m === 'upload') $('#upFile')?.click(); });
   $('#lastcap').addEventListener('click', () => { if (GE.captures.length) GE.you.inspect(GE.captures.length - 1); });
-  $('#capFlip').addEventListener('click', () => APP.toast(`${ic('layers', 'sm')} Showing Sky + Orbit in view`));
+  $('#capFlip').addEventListener('click', () => { if (m === 'live') GE.live.showOnGlobe(); else APP.toast(`${ic('layers', 'sm')} Showing Sky + Orbit in view`); });
+  if (m === 'live') GE.live.renderUI($('#modeHost'));
+  if (m === 'upload') GE.upload.renderUI($('#modeHost'));
 };
 CAP.syncZoom = () => $$('#v-capture [data-z]').forEach((x) => x.classList.toggle('on', +x.dataset.z === CAP.zoom));
 
 /* ---------- per-frame AR overlay ---------- */
 CAP.frame = function (view) {
   if (!CAP.on) return;
+  if (CAP.mode === 'live' || CAP.mode === 'upload') { GE.live.frame(); return; }
   const W = GE.world; const t = CAP.t + (performance.now() / 1000 - (CAP._t0 || (CAP._t0 = performance.now() / 1000)));
   const host = $('#callouts'); if (!host) return;
   // compass tape
@@ -4386,8 +5905,8 @@ CAP.ceremony = function (b, cv) {
     <div class="step" data-s="3"><span class="ck">${ic('check', 'xs')}</span><div><b>Bundle hash</b><div class="h" id="sh3">…</div></div></div>
     <div class="step" data-s="4"><span class="ck">${ic('check', 'xs')}</span><div><b>Signed</b> · ECDSA P-256, key generated on device, non-extractable<div class="h" id="sh4">…</div></div></div>
   </div>
-  <div class="btnrow" id="bbtns" style="opacity:.35;pointer-events:none"><button class="btn gold" id="bdrop">${ic('cube', 'sm')}Drop as hologram here</button></div>
-  <div class="btnrow" id="bbtns2" style="opacity:.35;pointer-events:none"><button class="btn" id="bver">${ic('check', 'sm')}Verify</button><button class="btn" id="bdone">Done</button></div>
+  <div class="btnrow" id="bbtns" style="opacity:.35;pointer-events:none"><button class="btn gold" id="bdrop">${ic('threads', 'sm')}Attach &amp; post</button></div>
+  <div class="btnrow" id="bbtns2" style="opacity:.35;pointer-events:none"><button class="btn" id="bver">${ic('check', 'sm')}Verify</button><button class="btn" id="bdone">Keep private</button></div>
   <p style="margin:0;font-size:11px;color:var(--text3);text-align:center">None of this proves truth. It raises the cost of lying.</p></div>`;
   const ph = $('#bph'); const c2 = document.createElement('canvas'); c2.width = 600; c2.height = 450; c2.getContext('2d').drawImage(cv, 0, 0, 600, 450); ph.prepend(c2);
   ov.classList.add('on');
@@ -4401,7 +5920,7 @@ CAP.ceremonyFill = async function (b) {
   $(`.step[data-s="4"]`).classList.add('on'); await stream('sh4', b.sig ? b.sig : 'WebCrypto unavailable here — bundle hashed but unsigned'); await step(4);
   $('#bigseal').classList.add('on'); haptic([10, 40, 20]);
   for (const id of ['bbtns', 'bbtns2']) { const e = $('#' + id); e.style.opacity = 1; e.style.pointerEvents = 'auto'; }
-  $('#bdrop').addEventListener('click', () => { GE.world.userHolos.push({ lat: b.lat, lon: b.lon, title: 'Your capture · ' + b.place, by: 'you', at: b.at }); b.dropped = true; $('#sealOv').classList.remove('on'); APP.toast(`${ic('cube', 'sm')} Hologram dropped · visible to people here`); CAP.render(); GE.you.render(); });
+  $('#bdrop').addEventListener('click', () => { $('#sealOv').classList.remove('on'); GE.attach.open({ kind: 'witness', tier: 'sealed', img: b.thumb, lat: b.lat, lon: b.lon, at: b.at, place: b.place, hash: b.hash, cap: b }); });
   $('#bver').addEventListener('click', () => { $('#sealOv').classList.remove('on'); GE.you.inspect(GE.captures.indexOf(b)); });
   $('#bdone').addEventListener('click', () => { $('#sealOv').classList.remove('on'); CAP.render(); GE.you.render(); });
 };
@@ -4565,12 +6084,20 @@ THR.init = async function () {
 /* ---------- list ---------- */
 THR.render = function () {
   const v = $('#v-threads');
-  v.innerHTML = `<div class="tlist" id="tlist" style="background:var(--bg);min-height:100%"><div class="navbar">Threads</div><div class="lt"><div class="kicker">${ic('seal', 'xs')} Signed evidence · open ledgers</div><div class="row"><h1>Threads</h1><span class="concept" style="margin-bottom:8px">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
-  <div class="livebar" style="padding-bottom:14px"><span class="presence"><span class="stack">${['kora', 'hydro', 'tamang', 'geo', 'sky'].map((k) => `<span class="avatar sm on" style="--h:${P[k].hue}">${P[k].h[0].toUpperCase()}</span>`).join('')}</span></span><span><b class="num">37</b> people reconstructing now</span></div>
+  v.innerHTML = `<div class="tlist" id="tlist" style="background:var(--bg);min-height:100%"><div class="navbar">Rooms</div><div class="lt"><div class="kicker mono">${ic('threads', 'xs')} CONVERSATIONS ON THE EVIDENCE</div><div class="row"><h1>Rooms</h1><span class="concept" style="margin-bottom:8px">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
+  <div class="livebar" style="padding-bottom:6px"><span class="presence"><span class="stack">${['nadia', 'lin', 'aiko', 'tomas', 'ines'].map((k) => GE.avatarHTML(k)).join('')}</span></span><span><b class="num">${fmt.n(Object.values(GE.rooms.byId).reduce((a, r) => a + r.watching, 0) || 9400)}</b> people in rooms now</span></div>
+  <div class="rooms-why">Every situation has a room. Posts are <b>Witness</b>, <b>Context</b>, <b>Question</b>, <b>Correction</b> or <b>Prediction</b>, ordered by evidence — never by followers.</div>
+  <div class="sec-h"><h2>Live rooms</h2><span>heating up</span></div><div id="roomsLive" class="rooms-live"></div>
+  <div class="sec-h"><h2>Reconstructions</h2><span>4D · signed · open ledgers</span></div>
   ${Object.values(THREADS).map((T) => { const s = GE.SIT.byId[T.sit]; return `<article class="tcard" data-t="${T.id}" data-id="${T.sit}"><div class="thumb"><canvas width="640" height="360"></canvas><div class="bl"><div><h3>${esc(T.title)}</h3><p>${esc(T.place)} · ${esc(T.date)}</p></div><span class="badge d4">4D</span></div></div><div class="stats"><div><b>${T.obs.length}</b>observations</div><div><b>${T.hyps.length}</b>hypotheses</div><div><b>${THR.ledgers[T.id]?.length || '–'}</b>ledger</div><span class="stack">${T.people.slice(0, 4).map((k) => `<span class="avatar sm" style="--h:${P[k].hue}">${P[k].h[0].toUpperCase()}</span>`).join('')}</span></div></article>`; }).join('')}
   <div style="padding:6px 14px 150px"><button class="btn" style="width:100%" id="newThread">${ic('plus', 'sm')}Start a reconstruction</button><p style="font-size:11.5px;color:var(--text3);text-align:center;margin-top:12px">Concept · illustrative data. Witness posts, handles and claims are fictional.</p></div></div>
   <div class="ws" id="ws"></div>`;
   $('#newThread').addEventListener('click', () => APP.toast(`${ic('threads', 'sm')} New thread · add your first observation`));
+  const host = $('#roomsLive'); const sq = GE.feed.squawkTrack();
+  const extra = [{ id: 'room-sq', arch: 'room', band: 'inside', sit: 'squawk', title: 'Squawk 7700 over the North Atlantic', place: 'Diverting to ' + sq.div.iata, lat: sq.cur[0], lon: sq.cur[1], ago: 3, ev: [['cabin', { seed: 81 }], ['track', { track: sq }]] }, { id: 'room-fi', arch: 'room', band: 'inside', sit: 'fires', title: 'Central Portugal fires', place: 'N2 · Pampilhosa da Serra', lat: 40.13, lon: -8.05, ago: 8, ev: [['firewit', { seed: 71 }], ['firesat', {}]] }];
+  const mine = GE.feed.user.filter((x) => x.sit && !['cyclone', 'quake', 'squawk', 'fires'].includes(x.sit)).map((x) => ({ id: 'room-' + x.sit, arch: 'room', band: 'inside', sit: x.sit, title: GE.SIT.byId[x.sit].title, place: GE.SIT.byId[x.sit].place, lat: x.lat, lon: x.lon, ago: 0 }));
+  const items = [...mine, ...GE.feed.items().filter((x) => x.arch === 'room' && !x.recon), ...extra];
+  for (const x of items) { x.at = x.at || NOW - (x.ago || 1) * 60000; x.dist = GE.feed.distFromMe(x.lat, x.lon); x.wide = true; host.append(GE.now.cardEl(x)); }
   $$('.tcard').forEach((c) => {
     c.addEventListener('click', () => THR.openWs(c.dataset.t));
     const cv = c.querySelector('canvas'); const s = GE.SIT.byId[c.dataset.id]; const done = GE.thumbs.done.get(s.id);
@@ -4709,10 +6236,12 @@ YOU.render = function () {
   const caps = GE.captures; const holos = [...W.userHolos, ...GE.HOLOS.filter((x) => x.by === 'you')];
   v.innerHTML = `<div style="background:var(--bg);min-height:100%;padding-bottom:150px"><div class="navbar">You</div>
   <div class="lt"><div class="kicker">${ic('key', 'xs')} Device key · P-256 · ${GE.crypto.KEY.pair ? 'ready' : 'generating…'}</div><h1>You</h1></div>
-  <div class="you-h"><span class="avatar xl" style="--h:205">Y</span><div><h2>Your window</h2><div style="color:var(--text2);font-size:13px;margin:2px 0 8px">Watching from ${esc(GE.ME.name)} · ${esc(GE.ME.tz)}</div><span class="concept">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
-  <div class="stats4"><div><b>${caps.length}</b>captures</div><div><b>${holos.length}</b>holograms</div><div><b>${Object.values(YOU.follows).filter(Boolean).length}</b>following</div><div><b>${caps.length ? '100%' : '—'}</b>verified</div></div>
+  <div class="you-h"><span class="avatar xl" style="--h:205">Y</span><div><h2>Your eye</h2><div style="color:var(--text2);font-size:13px;margin:2px 0 8px">Watching from ${esc(GE.ME.name)} · ${esc(GE.ME.tz)}</div><span class="concept">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
+  <div class="stats4"><div><b>${GE.feed.user.length}</b>posts</div><div><b>${holos.length}</b>holograms</div><div><b>${Object.values(YOU.follows).filter(Boolean).length}</b>following</div><div><b>${caps.length ? '100%' : '—'}</b>verified</div></div>
   <div class="sec-h"><h2>Captures</h2><span>sealed on this device</span></div>
   <div class="capgrid">${caps.length ? caps.map((c, i) => `<div class="capc" data-c="${i}"><div class="im" style="background-image:url(${c.thumb})"><svg class="seal"><use href="#i-seal"/></svg></div><div class="cm"><b>${esc(c.place)}</b><span class="num">${fmt.utc(c.at)}</span><div class="mono">${c.hash ? c.hash.slice(0, 18) + '…' : 'sealing…'}</div></div></div>`).join('') : `<div style="grid-column:1/-1;color:var(--text3);font-size:14px;padding:6px 4px">No captures yet — open Capture › Witness and press the shutter.</div>`}</div>
+  <div class="sec-h"><h2>Your posts</h2><span>in rooms</span></div>
+  <div class="grp">${GE.feed.user.length ? GE.feed.user.map((x) => { const s = GE.SIT.byId[x.sit]; const p = GE.rooms.byId[x.sit]?.posts.find((q) => q.id === x.post); const t = p?.att?.tier || 'text'; return `<div class="row2" data-post="${x.sit}|${x.post}"><span class="ri" style="--c:var(--b-inside)">${ic(t === 'sealed-live' ? 'live' : t === 'unverified' ? 'gallery' : 'seal')}</span><span class="rt">${esc(x.title)}<small>${esc(s ? (s.short || s.title.split(' — ')[0]) : '')} · ${{ 'sealed-live': 'Sealed live' + (p?.att?.segs ? ' · ' + p.att.segs + ' segments' : ''), sealed: 'Sealed', unverified: 'Unverified upload' }[t] || 'Text'} · ${fmt.ago(Date.now() - x.at)}</small></span><button class="rv">${ic('chevr', 'sm')}</button></div>`; }).join('') : `<div class="row2"><span class="ri" style="--c:var(--b-inside)">${ic('viewfinder')}</span><span class="rt">Nothing posted yet<small>Capture › Witness, Live or Upload, then attach it to a room</small></span></div>`}</div>
   <div class="sec-h"><h2>Holograms</h2><span>left in places</span></div>
   <div class="grp">${(holos.length ? holos : [{ title: 'Drop one from a Witness capture', lat: 0, lon: 0, empty: true }]).map((x) => `<div class="row2"><span class="ri" style="--c:var(--gold)">${ic('cube')}</span><span class="rt">${esc(x.title)}<small>${x.empty ? 'Visible to people nearby' : fmt.ll(x.lat, x.lon, 3) + ' · visible to people nearby'}</small></span>${x.empty ? '' : `<button class="rv" data-fly="${x.lat},${x.lon}">${ic('chevr', 'sm')}</button>`}</div>`).join('')}</div>
   <div class="sec-h"><h2>Following</h2><span>alerts</span></div>
@@ -4733,6 +6262,7 @@ YOU.render = function () {
   <p style="margin:0"><b>Renderer:</b> hand-written WebGL2 — ray-traced planet with single-scatter atmosphere, day/night terminator from the real sun position, ocean glint, clouds, stars, procedural cities and terrain, GPU-propagated flights and orbits.</p></div></div>`;
   v.scrollTop = st;
   v.querySelectorAll('[data-c]').forEach((el) => el.addEventListener('click', () => YOU.inspect(+el.dataset.c)));
+  v.querySelectorAll('[data-post]').forEach((el) => el.addEventListener('click', () => { const [sid, pid] = el.dataset.post.split('|'); GE.now._item = { band: 'inside', sit: sid }; GE.sheet.open(sid, { post: pid }); }));
   v.querySelectorAll('[data-f]').forEach((el) => el.addEventListener('click', () => { const id = el.dataset.f; YOU.follows[id] = !YOU.follows[id]; el.classList.toggle('on', YOU.follows[id]); el.setAttribute('aria-checked', YOU.follows[id]); store.set('follows', YOU.follows); haptic(5); }));
   v.querySelectorAll('[data-q]').forEach((el) => el.addEventListener('click', () => { const k = el.dataset.q; W.quality[k] = !W.quality[k]; el.classList.toggle('on', W.quality[k]); haptic(5); }));
   v.querySelectorAll('[data-fly]').forEach((el) => el.addEventListener('click', () => { const [la, lo] = el.dataset.fly.split(',').map(Number); APP.setTab('globe'); Cam.flyTo({ lat: la, lon: lo, range: 0.002, tilt: 1.1 }); }));
@@ -4770,6 +6300,419 @@ YOU.inspect = async function (i) {
   const prev = i > 0 ? GE.captures[i - 1].hash : '0'.repeat(64); await mark(5, prev === c.prev, `prev ${c.prev.slice(0, 32)}…`);
 };
 
+// ---- 68-room.js
+/* Room UI (inside the situation sheet): AI synthesis that cites every line, evidence-first posts with
+   earned badges, place + time anchors that fly the globe and scrub the ribbon, community notes with the
+   bridging rule explained, presence + floating reactions, and Reply → Capture first. */
+const RUI = (GE.roomUI = { sort: 'evidence' });
+const KIND_ICON = { witness: 'eye', context: 'layers', question: 'bubble', correction: 'flag', prediction: 'clock' };
+const tierLabel = (a) => ({ 'sealed-live': `SEALED LIVE${a.segs ? ' · ' + a.segs + ' SEGMENTS' : ''}`, sealed: 'SEALED', unverified: 'UNVERIFIED UPLOAD', eye: 'PUBLIC CAMERA' })[a.tier] || a.tier.toUpperCase();
+function citeChips(cites) { return (cites || []).map((c) => `<button class="cite" data-cite="${c}">${c}</button>`).join(''); }
+RUI.postHTML = function (room, p) {
+  const who = GE.PEOPLE[p.by] || { h: p.by, hue: 205 }; const K = GE.rooms.KINDS[p.kind]; const pid = GE.rooms.pid(room, p);
+  const bd = GE.rooms.badges(room, p).map(([k, l]) => `<span class="bdg ${k}">${k === 'sealed' ? ic('seal', 'xs') : ''}${esc(l)}</span>`).join('');
+  const att = p.att ? `<div class="patt ${p.att.tier}"><canvas width="${p.att.img ? 480 : 480}" height="300" data-att></canvas><span class="tier">${p.att.tier.startsWith('sealed') ? ic('seal', 'xs') : ''}${tierLabel(p.att)}</span>${p.live ? '<span class="plive"><span class="dot pulse"></span>LIVE</span>' : ''}</div>` : '';
+  const anc = [p.place ? `<button class="anc" data-anc="place">${ic('location', 'xs')}${esc(p.place.label)}</button>` : '', `<button class="anc" data-anc="time">${ic('clock', 'xs')}${fmt.hm(p.time || p.at)}Z</button>`].join('');
+  const ans = p.answered ? (() => { const a = room.posts.find((q) => q.id === p.answered); return a ? `<div class="answered">${ic('check', 'xs')}Answered by <b>@${esc(GE.PEOPLE[a.by].h)}</b> · ${GE.rooms.badges(room, a).map(([, l]) => esc(l)).join(' · ')}</div>` : ''; })() : p.kind === 'question' ? `<div class="answered open">${ic('arrowup', 'xs')}Open question · pinned to the top until someone answers with evidence</div>` : '';
+  const note = p.note ? `<div class="note"><div class="nh">${ic('people', 'xs')}Readers added context</div><p>${esc(p.note.text)} ${citeChips(p.note.cites)}</p>
+    <div class="bridge"><div class="br"><span>Raters who usually lean <b>A</b></span><i style="--v:${p.note.helpfulA}"></i><b class="num">${Math.round(p.note.helpfulA * 100)}%</b></div><div class="br"><span>Raters who usually lean <b>B</b></span><i style="--v:${p.note.helpfulB}"></i><b class="num">${Math.round(p.note.helpfulB * 100)}%</b></div></div>
+    <details><summary>Why is this note showing?</summary><p>A note only appears when people who usually <i>disagree</i> with each other both rate it helpful. Raters are grouped by how they have voted on past notes, not by what they say about themselves. Here ${p.note.ratersA} raters from one side and ${p.note.ratersB} from the other agreed, so it is shown. Brigading by one side can't make a note visible.</p></details></div>` : '';
+  const rx = p.reacts || {}; const rxs = [['eye', rx.eye], ['heart', rx.heart], ['exclamation', rx.alert]].filter(([, n]) => n).map(([i, n]) => `<button class="rxb" data-rx="${i}">${ic(i, 'xs')}<span class="num">${fmt.k(n)}</span></button>`).join('');
+  return `<article class="post k-${p.kind}${p.note ? ' noted' : ''}${p.mine ? ' mine' : ''}" data-p="${p.id}">
+    <div class="ph">${GE.avatarHTML(p.by)}<div class="pw"><div><b>@${esc(who.h)}</b><span class="pid">${pid}</span><span class="tm">${fmt.ago(Date.now() - p.at)}</span></div><div class="bds">${bd}</div></div><span class="kind k-${p.kind}">${ic(KIND_ICON[p.kind], 'xs')}${K.name.toUpperCase()}</span></div>
+    <div class="pt">${esc(p.text)}${p.resolves ? `<span class="resolves">resolves ${esc(p.resolves)}</span>` : ''}</div>
+    ${att}<div class="ancs">${anc}${citeChips(p.cites)}</div>${note}${ans}
+    <div class="pf">${rxs}<span class="rep">${ic('bubble', 'xs')}<span class="num">${p.replies || 0}</span></span><button class="rcap" data-reply>${ic('viewfinder', 'xs')}Reply with a capture</button></div></article>`;
+};
+RUI.synthHTML = function (room) {
+  const S = room.synth; const sec = (k, lab, cls) => (S[k] || []).length ? `<div class="sy ${cls}"><b>${lab}</b>${S[k].map(([t, c]) => `<p>${esc(t)} ${citeChips(c)}</p>`).join('')}</div>` : `<div class="sy ${cls}"><b>${lab}</b><p class="none">Nothing ${k} right now.</p></div>`;
+  const L = room.ledger; const last = room.synthEntry || L[L.length - 1];
+  return `<div class="synth" id="synth"><div class="syh">${ic('sparkles', 'xs')}<span>AI synthesis · every line cites a post or an observation</span><button class="regen" id="regen">${ic('wand', 'xs')}Re-synthesize</button></div>
+    <div id="syBody">${sec('known', 'KNOWN', 'kn')}${sec('disputed', 'DISPUTED', 'di')}${sec('unknown', 'UNKNOWN', 'un')}</div>
+    <div class="syf mono" id="syFoot">${room.synthModel ? esc(room.synthModel) + ' · ' : ''}${room.dropped ? room.dropped + ' uncited line removed · ' : ''}prompt + ${room.posts.length + Object.keys(room.src || {}).length} inputs in the ledger${last ? ` · #${last.i} ${last.hash.slice(0, 10)}…` : ''}</div></div>`;
+};
+RUI.render = function (host, s, o = {}) {
+  const room = GE.rooms.get(s.id); RUI.room = room; RUI.sit = s;
+  const list = GE.rooms.ordered(room, RUI.sort);
+  host.innerHTML = `${RUI.synthHTML(room)}
+    <div class="sortrow"><span class="sl mono">ORDER</span>${[['evidence', 'Evidence first'], ['latest', 'Latest'], ['questions', 'Questions']].map(([k, l]) => `<button class="chip sm ${RUI.sort === k ? 'on' : ''}" data-sort="${k}">${l}</button>`).join('')}</div>
+    <div class="posts" id="posts">${list.map((p) => RUI.postHTML(room, p)).join('')}</div>
+    <div class="srcs room-srcs"><div class="h3">Sources in this room</div>${Object.entries(room.src || {}).map(([k, v]) => `<div class="r"><span class="tagid">${k}</span><b style="font-weight:500">${esc(v)}</b></div>`).join('')}</div>
+    <p class="fine">Posts are ordered by evidence, then time — never by followers. Concept · illustrative data; people and posts are fictional.</p>`;
+  RUI.bind(host, room, s);
+  if (o.post) setTimeout(() => RUI.focusPost(o.post, true), 60);
+};
+RUI.bind = function (host, room, s) {
+  host.querySelectorAll('[data-sort]').forEach((b) => b.addEventListener('click', () => { RUI.sort = b.dataset.sort; RUI.render(host, s); haptic(4); }));
+  $('#regen')?.addEventListener('click', () => RUI.resynth(room, s));
+  host.querySelectorAll('.post').forEach((el) => {
+    const p = room.posts.find((q) => q.id === el.dataset.p);
+    const cv = el.querySelector('[data-att]'); if (cv && p.att) RUI.paintAtt(cv, p);
+    el.addEventListener('click', (e) => {
+      const b = e.target.closest('button, summary, details'); if (b && !b.matches('[data-anc]')) return;
+      RUI.anchor(p, b?.dataset.anc); });
+    el.querySelector('[data-reply]')?.addEventListener('click', (e) => { e.stopPropagation(); RUI.replyCapture(s, p); });
+    el.querySelectorAll('[data-rx]').forEach((b) => b.addEventListener('click', (e) => { e.stopPropagation(); RUI.float(b.dataset.rx); const k = { eye: 'eye', heart: 'heart', exclamation: 'alert' }[b.dataset.rx]; p.reacts = p.reacts || {}; p.reacts[k] = (p.reacts[k] || 0) + 1; b.querySelector('.num').textContent = fmt.k(p.reacts[k]); haptic(4); }));
+  });
+  host.querySelectorAll('[data-cite]').forEach((b) => b.addEventListener('click', (e) => { e.stopPropagation(); RUI.cite(b.dataset.cite); }));
+};
+RUI.paintAtt = function (cv, p) {
+  if (p.att.img) { const im = new Image(); im.onload = () => { const cx = cv.getContext('2d'); const sc = Math.max(cv.width / im.width, cv.height / im.height); cx.drawImage(im, (cv.width - im.width * sc) / 2, (cv.height - im.height * sc) / 2, im.width * sc, im.height * sc); }; im.src = p.att.img; return; }
+  const draw = () => GE.paint.draw(p.att.paint, cv, { ...p.att.o, t: performance.now() / 1000 });
+  GE.thumbs.enqueue(draw);
+  if (GE.paint.animated(p.att.paint)) { RUI.animCvs = RUI.animCvs || new Set(); RUI.animCvs.add([cv, p]); }
+};
+setInterval(() => { if (!RUI.animCvs || APP.mode !== 'situation') return; for (const e of RUI.animCvs) { const [cv, p] = e; if (!document.body.contains(cv)) { RUI.animCvs.delete(e); continue; } const r = cv.getBoundingClientRect(); if (r.bottom < 0 || r.top > innerHeight) continue; GE.paint.draw(p.att.paint, cv, { ...p.att.o, t: performance.now() / 1000 }); } }, 160);
+RUI.focusPost = function (id, fly) {
+  const el = $(`.post[data-p="${id}"]`); if (!el) return; el.classList.add('hl'); setTimeout(() => el.classList.remove('hl'), 2200);
+  const sc = $('#sheetC'); if (sc && GE.sheet.detent === 'large') sc.scrollTo({ top: el.offsetTop - 80, behavior: 'smooth' });
+  if (fly) { const p = RUI.room.posts.find((q) => q.id === id); if (p?.place) RUI.anchor(p, 'place', true); }
+};
+RUI.anchor = function (p, which, quiet) {
+  const W = GE.world; const s = RUI.sit;
+  if (p.place && which !== 'time') { const wide = APP.isWide(); const hs = GE.sheet.heights(); Cam.flyTo({ lat: p.place.lat - 0.12, lon: p.place.lon - 0.05, range: 0.03, heading: 0.4, tilt: 0.95, shiftY: wide ? 0 : hs[GE.sheet.detent === 'large' ? 'medium' : GE.sheet.detent] / hs.H, shiftX: 0 }, { duration: 1.8 }); GE.roomUI.labels(s, p.id); }
+  const at = p.time || p.at; if (which !== 'place') W.setTime(at);
+  if (!quiet) APP.toast(`${ic(p.place && which !== 'time' ? 'location' : 'clock', 'sm')} ${p.place && which !== 'time' ? esc(p.place.label) + ' · ' : ''}${fmt.hm(at)} UTC · ${fmt.ago(Date.now() - at)}`);
+  if (GE.sheet.detent === 'large' && !APP.isWide()) GE.sheet.setDetent('medium');
+  haptic(5);
+};
+RUI.cite = function (c) {
+  const room = RUI.room; if (!room) return;
+  if (c[0] === 'P') { const p = GE.rooms.byPid(room, c); if (p) { if (GE.sheet.detent !== 'large' && !APP.isWide()) GE.sheet.setDetent('large'); setTimeout(() => RUI.focusPost(p.id), 120); } return; }
+  if (c[0] === 'N') { const p = room.posts.find((q) => q.note); if (p) { if (GE.sheet.detent !== 'large' && !APP.isWide()) GE.sheet.setDetent('large'); setTimeout(() => RUI.focusPost(p.id), 120); } return; }
+  APP.toast(`${ic('hash', 'sm')} ${c} · ${esc((room.src || {})[c] || 'observation')}`, 2600);
+};
+// speech glyphs on the globe for anchored posts
+RUI.labels = function (s, hl) {
+  const room = GE.rooms.get(s.id); for (const k of [...GE.extraLabels.keys()]) if (k.startsWith('p:')) GE.extraLabels.delete(k);
+  for (const p of room.posts) { if (!p.place) continue; const who = GE.PEOPLE[p.by] || { h: p.by }; GE.extraLabels.set('p:' + p.id, { lat: p.place.lat, lon: p.place.lon, alt: 0.03, html: `<i class="sg k-${p.kind}">${ic(KIND_ICON[p.kind], 'xs')}</i><span>@${esc(who.h)}</span>`, w: who.h.length * 6.4 + 46, cls: 'glass speech' + (p.id === hl ? ' hl' : ''), onclick: () => { if (GE.sheet.detent === 'peek') GE.sheet.setDetent('medium'); RUI.focusPost(p.id); } }); }
+};
+/* presence & reactions */
+RUI.float = function (icon) { const host = $('#rx'); if (!host) return; const sp = h('span', { html: ic(icon || ['heart', 'eye', 'heart', 'exclamation', 'bolt'][Math.floor(Math.random() * 5)], 'sm'), style: `--dx:${(Math.random() - 0.5) * 30}px` }); sp.dataset.i = icon || ''; host.append(sp); setTimeout(() => sp.remove(), 2700); };
+setInterval(() => { if (APP.mode === 'situation' && GE.sheet.seg === 'room' && !document.hidden) { if (Math.random() < 0.7) RUI.float(); const w = $('#sheetC [data-watch]'); if (w && RUI.room) w.textContent = fmt.n(RUI.room.watching); } }, 900);
+
+/* composer: Capture first, text second */
+RUI.composer = function (show) {
+  const c = $('#roomComp'); if (!c) return; c.classList.toggle('on', !!show); if (!show) return;
+  if (c.dataset.bound) return; c.dataset.bound = '1';
+  c.innerHTML = `<button class="capbtn" id="rcCap" aria-label="Reply with a capture">${ic('viewfinder')}<span>Capture</span></button><div class="rcin glass"><div class="kinds" id="rcKinds">${Object.entries(GE.rooms.KINDS).map(([k, K]) => `<button data-k="${k}" class="${k === 'context' ? 'on' : ''}">${ic(KIND_ICON[k], 'xs')}${K.name}</button>`).join('')}</div><div class="rcrow"><input id="rcText" placeholder="Add context, ask, correct…" autocomplete="off"><button class="send" id="rcSend" aria-label="Post">${ic('arrowup', 'sm')}</button></div></div>`;
+  let kind = 'context';
+  c.querySelectorAll('[data-k]').forEach((b) => b.addEventListener('click', () => { kind = b.dataset.k; c.querySelectorAll('[data-k]').forEach((x) => x.classList.toggle('on', x === b)); haptic(3); }));
+  $('#rcCap').addEventListener('click', () => RUI.replyCapture(RUI.sit));
+  const inp = $('#rcText'); inp.addEventListener('focus', () => c.classList.add('typing')); inp.addEventListener('blur', () => setTimeout(() => c.classList.remove('typing'), 150));
+  inp.addEventListener('keydown', (e) => { if (e.key === 'Enter') { e.preventDefault(); $('#rcSend').click(); } });
+  $('#rcSend').addEventListener('click', async () => {
+    const t = inp.value.trim(); if (!t || !RUI.room) return; inp.value = '';
+    const p = { id: 'u' + Date.now(), kind, by: 'you', at: Date.now(), text: t, mine: true, reacts: {}, replies: 0 };
+    RUI.room.posts.push(p); const e = await GE.rooms.append(RUI.room, 'post.' + kind, 'you', { id: p.id, text: t });
+    RUI.render($('#shSeg'), RUI.sit); setTimeout(() => RUI.focusPost(p.id), 80);
+    APP.toast(`${ic('link', 'sm')} Posted · ledger #${e.i} · text ranks below evidence`, 2600); haptic(8);
+  });
+};
+RUI.replyCapture = function (s, p) {
+  GE.capture.replyTo = { sit: s.id, post: p?.id };
+  APP.toast(`${ic('viewfinder', 'sm')} Capture a reply for ${esc(s.short || s.title.split(' — ')[0])}`, 2000);
+  GE.sheet.close(true); APP.setTab('capture'); GE.capture.setMode('witness');
+};
+
+/* AI synthesis: window.claude sample on click, scripted fallback; uncited lines are dropped */
+RUI.resynth = async function (room, s, o = {}) {
+  const btn = $('#regen'); if (!btn || btn.disabled) return; btn.disabled = true; btn.classList.add('busy');
+  const body = $('#syBody'); const foot = $('#syFoot');
+  const posts = room.posts.map((p) => `[${GE.rooms.pid(room, p)}] ${GE.rooms.KINDS[p.kind].name} by @${(GE.PEOPLE[p.by] || { h: p.by }).h} (${GE.rooms.badges(room, p).map((b) => b[1]).join(', ') || 'no evidence badges'}), ${fmt.ago(Date.now() - p.at)}: ${p.text}${p.note ? ` — Community note [N1]: ${p.note.text}` : ''}`).join('\n');
+  const srcs = Object.entries(room.src || {}).map(([k, v]) => `[${k}] ${v}`).join('\n');
+  const prompt = `You summarise a live discussion about a real-world situation for an app that separates evidence from claims.\nSituation: ${s.title} — ${s.place}. Posts and people are illustrative.\nObservations:\n${srcs}\nPosts:\n${posts}\nWrite at most 6 lines, each starting with exactly one of "KNOWN:", "DISPUTED:" or "UNKNOWN:". Every line must end with one or more citations in square brackets like [P1] [O2] [N1]. Prefer sealed witness posts and observations over unverified posts. Never state anything you cannot cite. Plain text, no markdown.`;
+  body.innerHTML = '<div class="sy kn"><b>WRITING</b><p class="stream" id="syStream">…</p></div>';
+  let out = '', model = 'scripted fallback (no AI available here)';
+  const show = (t) => { out = t; const el = $('#syStream'); if (el) el.textContent = t || '…'; };
+  let sample = null; if (!o.auto) { try { sample = window.claude?.use ? await window.claude.use('sample') : null; } catch { sample = null; } }
+  if (o.auto) model = 'auto-update (scripted) · tap Re-synthesize to ask AI';
+  if (sample) { try { const r = await sample(prompt, { onText: ({ text }) => show(text) }); show(r?.text ?? out); model = 'claude · window.claude sample'; } catch { sample = null; } }
+  if (!sample) {
+    const S = room.synth; const lines = [...S.known.map(([t, c]) => `KNOWN: ${t} ${c.map((x) => `[${x}]`).join(' ')}`), ...S.disputed.map(([t, c]) => `DISPUTED: ${t} ${c.map((x) => `[${x}]`).join(' ')}`), ...S.unknown.map(([t, c]) => `UNKNOWN: ${t} ${c.map((x) => `[${x}]`).join(' ')}`)];
+    const mine = room.posts.filter((p) => p.mine && p.att); if (mine.length) { const p = mine[mine.length - 1]; lines.splice(1, 0, `KNOWN: A new ${p.att.tier.startsWith('sealed') ? 'sealed' : 'unverified'} capture from @you at ${p.place?.label || 'the scene'} adds a view of the situation. [${GE.rooms.pid(room, p)}]`); }
+    lines.push('UNKNOWN: Whether conditions improve in the next hour — the posts do not say.');
+    const full = lines.join('\n'); for (let i = 1; i <= full.length; i += 4) { show(full.slice(0, i)); await new Promise((r) => setTimeout(r, prefersReduced() ? 0 : 8)); } show(full);
+  }
+  // parse: keep only cited lines
+  const next = { known: [], disputed: [], unknown: [] }; let dropped = 0;
+  for (const ln of out.split('\n')) { const m = /^\s*(KNOWN|DISPUTED|UNKNOWN)\s*:\s*(.+)$/i.exec(ln); if (!m) continue; const cites = [...m[2].matchAll(/\[([PONS]\d+)\]/g)].map((x) => x[1]); const text = m[2].replace(/\s*\[[^\]]+\]/g, '').trim(); if (!cites.length) { dropped++; continue; } next[m[1].toLowerCase()].push([text, [...new Set(cites)]]); }
+  if (next.known.length + next.disputed.length + next.unknown.length) room.synth = next;
+  room.dropped = dropped; room.synthModel = model;
+  const e = await GE.rooms.append(room, 'ai.synthesis', 'claude', { prompt: await sha256(prompt), inputs: room.posts.map((p) => GE.rooms.pid(room, p)).concat(Object.keys(room.src || {})), model, output: await sha256(out), dropped });
+  room.synthEntry = e;
+  const wrap = $('#synth'); if (wrap) { wrap.outerHTML = RUI.synthHTML(room); $('#regen')?.addEventListener('click', () => RUI.resynth(room, s)); $('#synth').querySelectorAll('[data-cite]').forEach((b) => b.addEventListener('click', (ev) => { ev.stopPropagation(); RUI.cite(b.dataset.cite); })); }
+  APP.toast(`${ic('sparkles', 'sm')} Synthesis recorded · ledger #${e.i}${dropped ? ' · ' + dropped + ' uncited line dropped' : ''}`, 2800);
+};
+
+// ---- 69-live.js
+/* Live, Upload and the Attach sheet.
+   Live: a simulated broadcast (rendered lakefront in a gale) that seals a segment every 10 s into a real
+   SHA-256 hash chain signed with the device key; you appear on the globe as an eye with a view cone.
+   Upload: a real file input; EXIF GPS/time are read with a tiny parser; you place it on a map; it is
+   labelled Unverified everywhere. Attach: suggests where it belongs, kind, precision, hologram; posting
+   lands in the room, the feed and on the globe. */
+const LV = (GE.live = { on: false, segs: [], viewers: 0 });
+GE.capture.live = LV;
+const CAPm = GE.capture; const SPOTm = CAPm.spot;
+/* ---------- eyes on the globe (people and cameras that are looking right now) ---------- */
+GE.EYES = [
+  { id: 'basco', lat: 20.4485, lon: 121.9705, hdg: 205, fov: 64, label: '@nadia_basco', kind: 'witness', live: true, sit: 'cyclone', post: 'cy1' },
+  { id: 'kaoh', lat: 22.612, lon: 120.268, hdg: 250, fov: 72, label: 'HBR-07', kind: 'cctv', sit: 'cyclone', post: 'cy5' },
+  { id: 'shib', lat: 35.6597, lon: 139.7002, hdg: 135, fov: 84, label: 'CAM 0412', kind: 'cctv', sit: 'shibuya' },
+  { id: 'ines', lat: 40.13, lon: -8.05, hdg: 80, fov: 60, label: '@ines_coimbra', kind: 'witness', sit: 'fires', post: 'fi1' },
+  { id: 'ola', lat: 69.649, lon: 18.957, hdg: 10, fov: 74, label: '@ola_tromso', kind: 'witness', sit: 'aurora' },
+  { id: 'sak', lat: 31.597, lon: 130.56, hdg: 95, fov: 48, label: 'VOLCANO CAM 2', kind: 'cctv', sit: 'sakurajima' },
+  { id: 'rafa', lat: 18.357, lon: 121.637, hdg: 40, fov: 60, label: '@rafa_aparri', kind: 'witness', sit: 'cyclone', post: 'cy6' },
+];
+GE.eyeLines = function (rangeR) {
+  const out = []; const D = clamp((rangeR || 1) * EARTH_KM * 0.07, 0.25, 420);
+  for (const e of GE.EYES) {
+    const col = e.kind === 'you' ? [1, 0.86, 0.5, 0.95] : e.kind === 'cctv' ? [1, 0.66, 0.26, 0.7] : [0.96, 0.82, 0.48, 0.8];
+    const tip = geo.vec(e.lat, e.lon, 0.03 + D * 0.004); const half = (e.fov / 2) * D2R; const h0 = e.hdg * D2R; const cs = [];
+    for (const [da, z] of [[-half, 0], [half, 0], [half, D * 0.32], [-half, D * 0.32]]) { const [la, lo] = geo.dest(e.lat, e.lon, h0 + da, D); cs.push(geo.vec(la, lo, z)); }
+    for (const c of cs) out.push({ pts: [tip, c], col });
+    out.push({ pts: [...cs, cs[0]], col: [col[0], col[1], col[2], col[3] * 0.8] });
+    const mid = geo.dest(e.lat, e.lon, h0, D); out.push({ pts: [tip, geo.vec(mid[0], mid[1], D * 0.16)], col: [col[0], col[1], col[2], 0.35], dashed: 1 });
+  }
+  return out;
+};
+
+/* ---------- Live ---------- */
+const CHAT_LIVE = [['amara', 'Same at Oak Street — the trail is underwater'], ['kora', 'Stay back from the edge please 🙏'], ['sky', 'That spray must be 8 m'], ['geo', 'Buoy says 3.4 m waves, matches what we see'], ['hydro', 'Is the harbour gate closed?'], ['amara', 'Streaming this into the gale room'], ['ais', 'Two freighters sheltering off the breakwater'], ['kora', 'The sealed badge is so reassuring tbh']];
+const nearestSits = (lat, lon, n = 3) => GE.SIT.list.filter((s) => !s.dyn).map((s) => ({ s, km: RM.kmBetween(lat, lon, s.lat, s.lon) })).sort((a, b) => a.km - b.km).slice(0, n);
+LV.renderUI = function (host) {
+  const near = nearestSits(SPOTm.lat, SPOTm.lon, 2); LV.sit = near[0].s;
+  if (!LV.on) {
+    host.innerHTML = `<div class="lv-pre glass strong"><div class="lvph"><span class="lvpill pre"><i></i>READY</span><b>Go live as a sealed eye</b></div>
+      <p>Your camera becomes a sensor on the globe. Every 10 seconds the stream is sealed into a hash chain and signed on this device, with GPS, heading and motion. Rooms nearby can watch.</p>
+      <div class="lvnear">${near.map(({ s, km }) => `<span>${ic('threads', 'xs')}${esc(s.short || s.title.split(' — ')[0])} · ${GE.feed.fmtDist(km)}</span>`).join('')}</div>
+      <div class="lvfine mono">SIMULATED CAMERA · RENDERED SCENE · NO CAMERA OR MIC IS USED</div></div>`;
+    return;
+  }
+  host.innerHTML = `<div class="lv-top"><span class="lvpill"><i></i>LIVE <b class="num" id="lvT">00:00</b></span><span class="lvv glass">${ic('eye', 'xs')}<b class="num" id="lvV">${LV.viewers}</b></span><span class="lvseal">${ic('seal', 'xs')}SEALED LIVE</span></div>
+    <div class="lv-to glass">${ic('threads', 'xs')}<span>In the <b>${esc(LV.sit.short || LV.sit.title)}</b> room · ${GE.feed.fmtDist(RM.kmBetween(SPOTm.lat, SPOTm.lon, LV.sit.lat, LV.sit.lon))}</span></div>
+    <div class="lv-chat" id="lvChat"></div><div class="lvrx" id="lvRx"></div>
+    <div class="lv-tele mono" id="lvTele"></div><div class="lv-chain" id="lvChain"></div>`;
+  LV.drawChain(); LV.chatRestore();
+};
+LV.start = async function () {
+  if (LV.on) return; await GE.crypto.KEY.get();
+  Object.assign(LV, { on: true, t0: Date.now(), segT: Date.now(), segs: [], viewers: 3, prev: '0'.repeat(64), chat: [], hdg: 64 });
+  GE.EYES.push({ id: 'you', lat: SPOTm.lat, lon: SPOTm.lon, hdg: LV.hdg, fov: 62, label: 'You · LIVE', kind: 'you', live: true, sit: LV.sit?.id });
+  LV.timer = setInterval(() => LV.seal(), 10000); LV.soc = setInterval(() => LV.social(), 1500);
+  haptic([10, 30, 10]); CAPm.render(); APP.renderAccessory(); APP.toast(`${ic('live', 'sm')} You’re live · first segment seals in 10 s`);
+};
+LV.stop = function () {
+  if (!LV.on) return; clearInterval(LV.timer); clearInterval(LV.soc); LV.on = false; LV.t1 = Date.now();
+  const me = GE.EYES.find((e) => e.id === 'you'); if (me) { me.live = false; me.label = 'You · replay'; }
+  CAPm.render(); APP.renderAccessory();
+  const seg = LV.segs[LV.segs.length - 1];
+  GE.attach.open({ kind: 'witness', tier: 'sealed-live', img: LV.posterImg || seg?.thumb, lat: SPOTm.lat, lon: SPOTm.lon, at: LV.t0, place: SPOTm.name, segs: LV.segs.length, dur: (LV.t1 - LV.t0) / 1000, hash: seg?.hash, hdg: LV.hdg, live: true });
+};
+LV.seal = async function () {
+  const cv = $('#liveCv'); const small = GE.paint.mk(320, 180);
+  if (cv && cv.width) small.getContext('2d').drawImage(cv, 0, 0, 320, 180); else GE.paint.draw('seawall', small, { skyline: true, noOSD: true, seed: 53, t: performance.now() / 1000 });
+  const blob = await new Promise((r) => small.toBlob(r, 'image/jpeg', 0.7)); const bytes = new Uint8Array(await blob.arrayBuffer());
+  const seg = { i: LV.segs.length, t0: LV.segT, t1: Date.now(), frame: await sha256(bytes), bytes: bytes.length, gps: { lat: +SPOTm.lat.toFixed(6), lon: +SPOTm.lon.toFixed(6), acc: 4 }, hdg: LV.hdg, imu: 500, prev: LV.prev };
+  seg.hash = await sha256(canon(seg)); seg.sig = await GE.crypto.signHex(seg.hash); seg.thumb = small.toDataURL('image/jpeg', 0.6);
+  if (!LV.posterImg) { const pc = GE.paint.mk(480, 300); pc.getContext('2d').drawImage(cv || small, 0, 0, 480, 300); LV.posterImg = pc.toDataURL('image/jpeg', 0.8); }
+  LV.segs.push(seg); LV.prev = seg.hash; LV.segT = seg.t1; haptic(6);
+  LV.drawChain(true); APP.renderAccessory();
+};
+LV.drawChain = function (flash) {
+  const host = $('#lvChain'); if (!host) return;
+  const blocks = LV.segs.map((s) => `<div class="seg ok" title="segment ${s.i} · ${s.hash}"><span class="si mono">#${String(s.i + 1).padStart(3, '0')}</span><img src="${s.thumb}" alt=""><span class="sh mono">${s.hash.slice(0, 8)}</span><span class="sk">${ic('seal', 'xs')}${s.sig ? 'signed' : 'hashed'}</span></div>`).join('<i class="ln"></i>');
+  host.innerHTML = `${blocks}${LV.segs.length ? '<i class="ln"></i>' : ''}<div class="seg cur"><span class="si mono">#${String(LV.segs.length + 1).padStart(3, '0')}</span><div class="fill"><i id="lvFill"></i></div><span class="sh mono">sealing…</span></div>`;
+  host.scrollLeft = host.scrollWidth; if (flash) host.lastElementChild.previousElementSibling?.previousElementSibling?.classList.add('flash');
+};
+LV.social = function () {
+  if (!LV.on) return; LV.viewers += 1 + Math.floor(Math.random() * (LV.viewers > 60 ? 18 : 6));
+  const chat = $('#lvChat'); const k = Math.floor((Date.now() - LV.t0) / 1500);
+  const ev = k % 3 === 0 ? { join: ['amara', 'kora', 'sky', 'geo', 'hydro', 'ais', 'ola'][k % 7] } : { msg: CHAT_LIVE[k % CHAT_LIVE.length] };
+  LV.chat.push(ev); if (LV.chat.length > 4) LV.chat.shift(); if (chat) LV.chatRestore();
+  const rx = $('#lvRx'); if (rx) for (let i = 0; i < 2; i++) { const sp = h('span', { html: ic(['heart', 'eye', 'heart', 'bolt'][Math.floor(Math.random() * 4)], 'sm'), style: `--dx:${(Math.random() - 0.5) * 30}px` }); rx.append(sp); setTimeout(() => sp.remove(), 2700); }
+};
+LV.chatRestore = function () {
+  const chat = $('#lvChat'); if (!chat) return;
+  chat.innerHTML = LV.chat.map((e) => e.join ? `<div class="lj">${GE.avatarHTML(e.join)}<span><b>@${esc(GE.PEOPLE[e.join].h)}</b> joined</span></div>` : `<div class="bub">${GE.avatarHTML(e.msg[0])}<div class="bx glass"><b>@${esc(GE.PEOPLE[e.msg[0]].h)}</b>${esc(e.msg[1])}</div></div>`).join('');
+};
+LV.frame = function () {
+  const cv = $('#liveCv'); if (!cv || CAPm.mode !== 'live') return;
+  const W0 = Math.round(cv.clientWidth * 0.8), H0 = Math.round(cv.clientHeight * 0.8); if (!W0 || !H0) return;
+  if (cv.width !== W0 || cv.height !== H0) { cv.width = W0; cv.height = H0; }
+  const now = performance.now(); if (LV._lf && now - LV._lf < 40) return; LV._lf = now;
+  GE.paint.draw('seawall', cv, { skyline: true, handheld: true, noOSD: true, seed: 53, t: now / 1000 });
+  if (!LV.on) return;
+  const tEl = $('#lvT'); if (tEl) tEl.textContent = fmt.dur((Date.now() - LV.t0) / 1000).slice(3);
+  const vEl = $('#lvV'); if (vEl) vEl.textContent = fmt.n(LV.viewers);
+  const f = $('#lvFill'); if (f) f.style.width = clamp((Date.now() - LV.segT) / 10000, 0, 1) * 100 + '%';
+  const te = $('#lvTele'); if (te) te.textContent = `${GE.feed.llz(SPOTm.lat, SPOTm.lon)} · HDG ${String(LV.hdg + Math.round(Math.sin(now / 900) * 3)).padStart(3, '0')}° · ±4 M · ALT 182 M · SEG ${String(LV.segs.length + 1).padStart(3, '0')} · ${GE.feed.hmsZ()}`;
+};
+LV.showOnGlobe = function () {
+  const back = LV.on; APP.setTab('globe'); Cam.flyTo({ lat: SPOTm.lat - 0.035, lon: SPOTm.lon - 0.05, range: 0.016, heading: 0.75, tilt: 1.0, shiftY: 0.06, shiftX: 0 }, { duration: 2.4 });
+  APP.toast(back ? `${ic('eye', 'sm')} That cone is you — still live` : `${ic('eye', 'sm')} Your view cone on the globe`, 2600);
+};
+
+/* ---------- EXIF (read + write) ---------- */
+const EX = (GE.exif = {});
+EX.parse = function (buf) {
+  try {
+    const v = new DataView(buf); if (v.getUint16(0) !== 0xffd8) return null; let o = 2;
+    while (o < v.byteLength - 4) { const m = v.getUint16(o); if ((m & 0xff00) !== 0xff00) break; const len = v.getUint16(o + 2); if (m === 0xffe1 && v.getUint32(o + 4) === 0x45786966) return EX.tiff(v, o + 10); if (m === 0xffda) break; o += 2 + len; }
+  } catch (e) { console.warn('exif', e); }
+  return null;
+};
+EX.tiff = function (v, t) {
+  const le = v.getUint16(t) === 0x4949; const u16 = (p) => v.getUint16(p, le), u32 = (p) => v.getUint32(p, le);
+  const ifd = (p) => { const n = u16(p); const e = {}; for (let i = 0; i < n; i++) { const q = p + 2 + i * 12; e[u16(q)] = { type: u16(q + 2), count: u32(q + 4), off: q + 8 }; } return e; };
+  const val = (en) => {
+    if (!en) return null; const { type, count } = en; const size = { 1: 1, 2: 1, 3: 2, 4: 4, 5: 8, 7: 1, 9: 4, 10: 8 }[type] || 1; const p = size * count > 4 ? t + u32(en.off) : en.off;
+    if (type === 2) { let s = ''; for (let i = 0; i < count; i++) { const c = v.getUint8(p + i); if (!c) break; s += String.fromCharCode(c); } return s.trim(); }
+    if (type === 5 || type === 10) { const out = []; for (let i = 0; i < count; i++) { const a = type === 5 ? u32(p + i * 8) : v.getInt32(p + i * 8, le), b = type === 5 ? u32(p + i * 8 + 4) : v.getInt32(p + i * 8 + 4, le); out.push(b ? a / b : 0); } return count === 1 ? out[0] : out; }
+    if (type === 3) return u16(p); if (type === 4) return u32(p); return v.getUint8(p);
+  };
+  const i0 = ifd(t + u32(t + 4)); const out = { make: val(i0[0x010f]), model: val(i0[0x0110]), date: val(i0[0x0132]) };
+  if (i0[0x8769]) { const ex = ifd(t + val(i0[0x8769])); out.date = val(ex[0x9003]) || out.date; }
+  if (i0[0x8825]) { const g = ifd(t + val(i0[0x8825])); const dms = (a) => (a && a.length === 3 ? a[0] + a[1] / 60 + a[2] / 3600 : null); const la = dms(val(g[2])), lo = dms(val(g[4])); if (la != null && lo != null) { out.lat = la * (val(g[1]) === 'S' ? -1 : 1); out.lon = lo * (val(g[3]) === 'W' ? -1 : 1); } const al = val(g[6]); if (al != null) out.alt = al; }
+  return out;
+};
+EX.when = (s) => { const m = /^(\d{4}):(\d\d):(\d\d) (\d\d):(\d\d):(\d\d)/.exec(s || ''); return m ? Date.UTC(+m[1], +m[2] - 1, +m[3], +m[4], +m[5], +m[6]) : null; };
+// write a little-endian TIFF/EXIF block with Make, Model, DateTimeOriginal and GPS (used by the sample)
+EX.build = function ({ make, model, date, lat, lon, alt }) {
+  const B = []; const u8 = (x) => B.push(x & 255), u16 = (x) => { u8(x); u8(x >> 8); }, u32 = (x) => { u16(x & 0xffff); u16(x >>> 16); };
+  const str = (s) => { const a = [...new TextEncoder().encode(s), 0]; if (a.length % 2) a.push(0); return a; };
+  const mk = str(make), md = str(model), dt = str(date);
+  const IFD0 = 8, D0 = IFD0 + 2 + 5 * 12 + 4, pMk = D0, pMd = pMk + mk.length, pDt = pMd + md.length, EXIF = pDt + dt.length, pDo = EXIF + 2 + 12 + 4, GPS = pDo + dt.length, pLa = GPS + 2 + 7 * 12 + 4, pLo = pLa + 24, pAl = pLo + 24;
+  const ent = (tag, type, count, v) => { u16(tag); u16(type); u32(count); u32(v); };
+  const asc2 = (c) => c.charCodeAt(0);
+  u16(0x4949); u16(42); u32(IFD0);
+  u16(5); ent(0x010f, 2, mk.length - (mk[mk.length - 1] === 0 && mk[mk.length - 2] === 0 ? 1 : 0), pMk); ent(0x0110, 2, md.length - (md[md.length - 1] === 0 && md[md.length - 2] === 0 ? 1 : 0), pMd); ent(0x0132, 2, 20, pDt); ent(0x8769, 4, 1, EXIF); ent(0x8825, 4, 1, GPS); u32(0);
+  B.push(...mk, ...md, ...dt);
+  u16(1); ent(0x9003, 2, 20, pDo); u32(0); B.push(...dt);
+  u16(7); ent(0, 1, 4, 0x00000302); ent(1, 2, 2, asc2(lat >= 0 ? 'N' : 'S')); ent(2, 5, 3, pLa); ent(3, 2, 2, asc2(lon >= 0 ? 'E' : 'W')); ent(4, 5, 3, pLo); ent(5, 1, 1, 0); ent(6, 5, 1, pAl); u32(0);
+  const rat = (x) => { const d = Math.floor(x), mm = Math.floor((x - d) * 60), ss = Math.round(((x - d) * 60 - mm) * 60 * 100); u32(d); u32(1); u32(mm); u32(1); u32(ss); u32(100); };
+  rat(Math.abs(lat)); rat(Math.abs(lon)); u32(Math.round((alt || 0) * 10)); u32(10);
+  const tiff = new Uint8Array(B); const seg = new Uint8Array(4 + 6 + tiff.length); const L = 2 + 6 + tiff.length;
+  seg.set([0xff, 0xe1, L >> 8, L & 255, 0x45, 0x78, 0x69, 0x66, 0, 0]); seg.set(tiff, 10); return seg;
+};
+EX.inject = (jpeg, app1) => { const out = new Uint8Array(jpeg.length + app1.length); out.set(jpeg.subarray(0, 2)); out.set(app1, 2); out.set(jpeg.subarray(2), 2 + app1.length); return out; };
+const exifDate = (ms) => { const d = new Date(ms); const z = (n) => String(n).padStart(2, '0'); return `${d.getUTCFullYear()}:${z(d.getUTCMonth() + 1)}:${z(d.getUTCDate())} ${z(d.getUTCHours())}:${z(d.getUTCMinutes())}:${z(d.getUTCSeconds())}`; };
+
+/* ---------- Upload ---------- */
+const UP = (GE.upload = { f: null });
+UP.renderUI = function (host) {
+  const f = UP.f;
+  if (!f) {
+    host.innerHTML = `<div class="up glass strong"><div class="uph"><b>Add a photo or video of a place</b><span class="tierb unv">UNVERIFIED</span></div>
+      <p>Uploads weren’t sealed when they were taken, so they carry an <b>Unverified</b> label everywhere. A hypothesis can cite one, but it can never become an observation.</p>
+      <label class="drop"><input type="file" id="upFile" accept="image/*,video/*" hidden>${ic('gallery', 'lg')}<b>Choose from your library</b><span>A JPEG with location in its EXIF places itself</span></label>
+      <button class="btn sm" id="upSample" style="width:100%">${ic('sparkles', 'sm')}No photo handy? Use a sample with GPS in its EXIF</button>
+      <p class="fine mono">READ LOCALLY WITH FILEREADER · NOTHING LEAVES THIS PAGE</p></div>`;
+    $('#upFile').addEventListener('change', (e) => { const file = e.target.files && e.target.files[0]; if (file) UP.load(file); });
+    $('#upSample').addEventListener('click', () => UP.sample());
+    return;
+  }
+  const ex = f.exif || {}; const has = f.lat != null;
+  host.innerHTML = `<div class="up glass strong loaded"><div class="upimg"><img src="${f.img}" alt="Your upload"><span class="tierb unv">UNVERIFIED</span></div>
+    <div class="exif mono"><div><span>FILE</span><b>${esc(f.name)} · ${fmt.k(f.size / 1024)} KB</b></div><div><span>CAMERA</span><b>${esc([ex.make, ex.model].filter(Boolean).join(' ') || '—')}</b></div><div><span>TAKEN</span><b>${ex.date ? esc(ex.date) : '—'}</b></div><div><span>GPS</span><b>${ex.lat != null ? GE.feed.llz(ex.lat, ex.lon) + ' · from EXIF' : 'none in file — place it'}</b></div></div>
+    <div class="placer"><canvas id="upMap" width="640" height="300"></canvas><div class="pin" id="upPin">${ic('location', 'sm')}</div><div class="hint mono" id="upLL"></div></div>
+    <div class="uptime"><span>When</span><input type="range" id="upT" min="-4320" max="0" step="5" value="${Math.round(((f.at || Date.now()) - Date.now()) / 60000)}"><b class="num" id="upTv"></b></div>
+    <div class="btnrow"><button class="btn sm" id="upRe">Choose another</button><button class="btn gold sm" id="upGo">${ic('threads', 'sm')}Continue</button></div></div>`;
+  UP.drawMap(); UP.bindPin();
+  const t = $('#upT'); const tv = $('#upTv'); const upd = () => { f.at = Date.now() + +t.value * 60000; tv.textContent = `${fmt.hm(f.at)} UTC · ${fmt.ago(Date.now() - f.at)}`; }; t.addEventListener('input', upd); upd();
+  $('#upRe').addEventListener('click', () => { UP.f = null; UP.renderUI(host); });
+  $('#upGo').addEventListener('click', () => GE.attach.open({ kind: 'witness', tier: 'unverified', img: f.img, lat: f.lat, lon: f.lon, at: f.at, place: f.name, upload: true }));
+};
+UP.load = function (file) {
+  const r = new FileReader();
+  r.onload = () => {
+    const buf = r.result; const ex = file.type === 'image/jpeg' || /\.jpe?g$/i.test(file.name) ? EX.parse(buf) : null;
+    const f = { name: file.name || 'upload', size: file.size, type: file.type, exif: ex, lat: ex?.lat ?? null, lon: ex?.lon ?? null, at: EX.when(ex?.date) || file.lastModified || Date.now() };
+    if (f.lat == null) { f.lat = GE.ME.lat; f.lon = GE.ME.lon; f.guess = true; }
+    const url = URL.createObjectURL(file);
+    const done = (cv) => { f.img = cv.toDataURL('image/jpeg', 0.82); UP.f = f; URL.revokeObjectURL(url); UP.renderUI($('#modeHost')); APP.toast(ex?.lat != null ? `${ic('location', 'sm')} Placed from EXIF GPS · ${GE.feed.llz(f.lat, f.lon)}` : `${ic('location', 'sm')} No GPS in this file — drag the pin`, 2600); };
+    if (file.type.startsWith('video')) { const v = document.createElement('video'); v.muted = true; v.playsInline = true; v.src = url; v.addEventListener('loadeddata', () => { v.currentTime = Math.min(0.5, v.duration / 2 || 0); }, { once: true }); v.addEventListener('seeked', () => { const cv = GE.paint.mk(640, Math.round(640 * (v.videoHeight / v.videoWidth || 0.56))); cv.getContext('2d').drawImage(v, 0, 0, cv.width, cv.height); done(cv); }, { once: true }); v.addEventListener('error', () => APP.toast('Could not read that video here'), { once: true }); return; }
+    const im = new Image(); im.onload = () => { const sc = Math.min(1, 1280 / Math.max(im.width, im.height)); const cv = GE.paint.mk(im.width * sc, im.height * sc); cv.getContext('2d').drawImage(im, 0, 0, cv.width, cv.height); done(cv); }; im.onerror = () => APP.toast('Could not read that image'); im.src = url;
+  };
+  r.onerror = () => APP.toast('Could not read that file'); r.readAsArrayBuffer(file);
+};
+UP.sample = async function () {
+  const cv = GE.paint.mk(1200, 900); GE.paint.draw('volcano', cv, { noOSD: true, t: 1 });
+  const blob = await new Promise((r) => cv.toBlob(r, 'image/jpeg', 0.86)); const jpg = new Uint8Array(await blob.arrayBuffer());
+  const app1 = EX.build({ make: 'Concept', model: 'Sample Phone', date: exifDate(Date.now() - 23 * 60000), lat: 31.5937, lon: 130.5626, alt: 4.2 });
+  const file = new File([EX.inject(jpg, app1)], 'IMG_4021.JPG', { type: 'image/jpeg', lastModified: Date.now() - 20 * 60000 }); UP.load(file);
+};
+UP.drawMap = function () {
+  const f = UP.f; const cv = $('#upMap'); if (!cv) return; const span = 4.2; const mv = GE.paint.mapView(f.lat, f.lon, span, cv.width, cv.height); UP.mv = mv;
+  const ctx = cv.getContext('2d'); GE.paint.mapBase(ctx, mv, { lights: 1.1, relief: 0.8, land: '#18202b', sea: '#05080c', coast: '#5b6e86' }); GE.paint.graticule(ctx, mv, 1);
+  for (const { s, km } of nearestSits(f.lat, f.lon, 6)) { const x = mv.X(s.lon), y = mv.Y(s.lat); if (x < 0 || y < 0 || x > cv.width || y > cv.height) continue; ctx.fillStyle = '#FF6A3D'; ctx.beginPath(); ctx.arc(x, y, 6, 0, TAU); ctx.fill(); GE.paint.label(ctx, (s.short || s.title).toUpperCase(), x + 10, y, 15, '#fff'); }
+  GE.paint.scaleBar(ctx, mv, 50, 18, cv.height - 18);
+};
+UP.bindPin = function () {
+  const f = UP.f; const pin = $('#upPin'), cv = $('#upMap'); const place = () => { const r = cv.getBoundingClientRect(); const sx = r.width / cv.width; pin.style.left = UP.mv.X(f.lon) * sx + 'px'; pin.style.top = UP.mv.Y(f.lat) * sx + 'px'; $('#upLL').textContent = `${GE.feed.llz(f.lat, f.lon)} · ${f.guess ? 'GUESSED — DRAG ME' : f.moved ? 'PLACED BY YOU' : 'FROM EXIF'}`; };
+  requestAnimationFrame(place); let drag = false;
+  const mv = (e) => { if (!drag) return; const r = cv.getBoundingClientRect(); const sx = cv.width / r.width; const x = clamp((e.clientX - r.left) * sx, 0, cv.width), y = clamp((e.clientY - r.top) * sx, 0, cv.height); f.lat = UP.mv.lat(y); f.lon = UP.mv.lon(x); f.moved = true; f.guess = false; place(); };
+  pin.addEventListener('pointerdown', (e) => { drag = true; pin.setPointerCapture(e.pointerId); e.preventDefault(); }); pin.addEventListener('pointermove', mv); pin.addEventListener('pointerup', () => { drag = false; haptic(4); });
+  cv.addEventListener('click', (e) => { drag = true; mv(e); drag = false; });
+};
+
+/* ---------- Attach sheet ---------- */
+const AT = (GE.attach = {});
+const bandOfFam = (f) => ({ orbit: 'orbit', sky: 'sky', wx: 'sky', eyes: 'ground' })[f] || 'ground';
+AT.open = function (c) {
+  AT.c = c; const near = nearestSits(c.lat, c.lon, 3); const pre = CAPm.replyTo?.sit || (near[0].km < 400 ? near[0].s.id : 'new');
+  AT.sel = pre; AT.kind = c.kind || 'witness'; AT.prec = c.upload ? '100' : 'exact'; AT.holo = !c.upload;
+  const opts = [...(CAPm.replyTo && !near.some((n) => n.s.id === CAPm.replyTo.sit) ? [{ s: GE.SIT.byId[CAPm.replyTo.sit], km: RM.kmBetween(c.lat, c.lon, GE.SIT.byId[CAPm.replyTo.sit].lat, GE.SIT.byId[CAPm.replyTo.sit].lon) }] : []), ...near];
+  const tier = c.tier === 'sealed-live' ? `SEALED LIVE · ${c.segs} SEGMENTS · ${fmt.dur(c.dur || 0).slice(3)}` : c.tier === 'sealed' ? 'SEALED · ECDSA P-256' : 'UNVERIFIED UPLOAD';
+  const ov = $('#attachOv');
+  ov.innerHTML = `<div class="att glass strong"><div class="grab"></div>
+    <div class="ath"><div class="atimg"><img src="${c.img || ''}" alt=""><span class="tierb ${c.tier === 'unverified' ? 'unv' : ''}">${c.tier === 'unverified' ? '' : ic('seal', 'xs')}${tier}</span></div><div><h2>Where does this belong?</h2><p class="mono">${GE.feed.llz(c.lat, c.lon)} · ${fmt.hm(c.at)} UTC${c.hash ? ' · ' + c.hash.slice(0, 10) + '…' : ''}</p></div></div>
+    <div class="ath2">Suggested from where and when it was taken</div>
+    <div class="sugs">${opts.map(({ s, km }) => `<button class="sug ${AT.sel === s.id ? 'on' : ''}" data-s="${s.id}" style="--c:${GE.BANDS[bandOfFam(s.fam)].c}"><i></i><span><b>${esc(s.short || s.title.split(' — ')[0])}</b><small>${GE.feed.fmtDist(km)} away · ${s.live ? 'live now' : 'replay'} · ${fmt.k(GE.rooms.watching(s.id))} in room</small></span><em>${ic('check', 'xs')}</em></button>`).join('')}
+      <button class="sug ${AT.sel === 'new' ? 'on' : ''}" data-s="new" style="--c:#fff"><i></i><span><b>New place</b><small>Start a room at ${GE.feed.llz(c.lat, c.lon)}</small></span><em>${ic('check', 'xs')}</em></button></div>
+    <div class="ath2">Post as</div><div class="kinds2">${Object.entries(GE.rooms.KINDS).map(([k, K]) => `<button data-k="${k}" class="${AT.kind === k ? 'on' : ''}">${K.name}</button>`).join('')}</div>
+    <textarea id="atNote" rows="2" placeholder="${c.live ? 'Waves are coming over the lakefront trail…' : 'What does this show? (optional)'}"></textarea>
+    <div class="ath2">Share location as</div><div class="prec">${[['exact', 'Exact'], ['100', '100 m'], ['1000', '1 km']].map(([k, l]) => `<button data-p="${k}" class="${AT.prec === k ? 'on' : ''}">${l}</button>`).join('')}</div>
+    <p class="fine2">${c.tier === 'unverified' ? 'An upload has no seal, so precision is all anyone gets.' : 'The seal still proves the exact point to verifiers without publishing it.'}</p>
+    <div class="row2 holo"><span class="ri" style="--c:var(--b-inside)">${ic('cube')}</span><span class="rt">Leave it here as a hologram<small>People who come to this spot later can find it</small></span><button class="sw2 ${AT.holo ? 'on' : ''}" id="atHolo" role="switch" aria-label="Hologram"></button></div>
+    <p class="fine2 priv">${ic('eyeslash', 'xs')} Faces and plates are blurred on-device before upload in the native build. This web concept does not blur — a disclosed limitation.</p>
+    <div class="btnrow"><button class="btn" id="atX">Cancel</button><button class="btn gold" id="atGo">${ic('arrowup', 'sm')}Post</button></div></div>`;
+  ov.classList.add('on');
+  ov.querySelectorAll('[data-s]').forEach((b) => b.addEventListener('click', () => { AT.sel = b.dataset.s; ov.querySelectorAll('[data-s]').forEach((x) => x.classList.toggle('on', x === b)); AT.label(); haptic(4); }));
+  ov.querySelectorAll('[data-k]').forEach((b) => b.addEventListener('click', () => { AT.kind = b.dataset.k; ov.querySelectorAll('[data-k]').forEach((x) => x.classList.toggle('on', x === b)); haptic(3); }));
+  ov.querySelectorAll('[data-p]').forEach((b) => b.addEventListener('click', () => { AT.prec = b.dataset.p; ov.querySelectorAll('[data-p]').forEach((x) => x.classList.toggle('on', x === b)); haptic(3); }));
+  $('#atHolo').addEventListener('click', (e) => { AT.holo = !AT.holo; e.currentTarget.classList.toggle('on', AT.holo); });
+  $('#atX').addEventListener('click', () => ov.classList.remove('on'));
+  $('#atGo').addEventListener('click', () => AT.post());
+  AT.label();
+};
+AT.label = function () { const b = $('#atGo'); if (!b) return; const s = GE.SIT.byId[AT.sel]; b.innerHTML = `${ic('arrowup', 'sm')}Post to ${esc(s ? (s.short || s.title.split(' — ')[0]) : 'a new room')}`; };
+AT.post = async function () {
+  const c = AT.c; let sitId = AT.sel;
+  if (sitId === 'new') { sitId = 'mine-' + Date.now(); GE.SIT.list.push({ id: sitId, short: 'Your place', fam: 'eyes', kind: 'place', title: 'New place · ' + (c.place || 'your capture'), place: GE.feed.llz(c.lat, c.lon), lat: c.lat, lon: c.lon, camera: { lat: c.lat - 0.01, lon: c.lon - 0.01, range: 0.01, heading: 0.4, tilt: 1.0 }, layers: ['signed', 'holo', 'cctv'], source: 'You', live: true, watchers: 12, updatedAt: Date.now(), metric: () => ['', ''], metrics: () => [{ v: 1, u: '', l: 'Captures', s: 'You' }, { v: 0, u: '', l: 'Replies', s: '' }, { v: '—', u: '', l: 'Nearby rooms', s: '' }], brief: { lede: 'A place you started. Others nearby will see it.', series: [], sources: [] } }); GE.SIT.byId[sitId] = GE.SIT.list[GE.SIT.list.length - 1]; }
+  const s = GE.SIT.byId[sitId]; const room = GE.rooms.get(sitId);
+  const q = AT.prec === 'exact' ? 0 : AT.prec === '100' ? 0.001 : 0.01; const rd = (x) => (q ? Math.round(x / q) * q : x);
+  const km = RM.kmBetween(c.lat, c.lon, s.lat, s.lon);
+  const note = ($('#atNote').value || '').trim() || (c.live ? 'Live from the lakefront: waves are breaking over the trail and the path is closed.' : c.upload ? 'Photo from my library, placed from its EXIF.' : 'Sealed capture from here.');
+  const p = { id: 'y' + Date.now(), kind: AT.kind, by: 'you', at: c.at || Date.now(), text: note, mine: true, place: { lat: rd(c.lat), lon: rd(c.lon), label: c.place || 'Your capture' }, att: { img: c.img, tier: c.tier, segs: c.segs, distKm: c.tier === 'unverified' ? null : Math.min(km, 4.9) }, reacts: {}, replies: 0, prec: AT.prec };
+  if (CAPm.replyTo?.post) p.replyTo = CAPm.replyTo.post;
+  room.posts.push(p); const e = await GE.rooms.append(room, 'post.' + AT.kind, 'you', { id: p.id, text: note, att: { tier: c.tier, hash: c.hash || null, segs: c.segs || 0 }, place: p.place, precision: AT.prec });
+  // feed
+  const tierT = c.tier === 'sealed-live' ? 'SEALED LIVE' : c.tier === 'sealed' ? 'SEALED' : 'UNVERIFIED';
+  GE.feed.user.unshift({ id: 'f' + p.id, mine: true, arch: 'witness', band: 'inside', sit: sitId, post: p.id, by: 'you', img: c.img, aspect: 0.75, title: note.length > 90 ? note.slice(0, 88) + '…' : note, place: c.place || s.place, lat: c.lat, lon: c.lon, ago: 0, at: Date.now(), dist: 0, prio: 999,
+    tele: () => `WITNESS · ${tierT} · ${AT.prec === 'exact' ? '±4 M' : AT.prec === '100' ? '±100 M' : '±1 KM'} · ${GE.feed.fmtDist(km).toUpperCase()} FROM EVENT` });
+  // globe: hologram + an eye with a cone for sealed captures
+  if (AT.holo) GE.world.userHolos.push({ lat: rd(c.lat), lon: rd(c.lon), title: 'Your capture · ' + (c.place || ''), by: 'you', at: c.at });
+  if (c.tier !== 'unverified' && !GE.EYES.some((x) => x.id === 'you')) GE.EYES.push({ id: 'you', lat: c.lat, lon: c.lon, hdg: c.hdg ?? 64, fov: 62, label: 'You', kind: 'you', sit: sitId, post: p.id });
+  const me = GE.EYES.find((x) => x.id === 'you'); if (me) { me.sit = sitId; me.post = p.id; }
+  $('#attachOv').classList.remove('on'); CAPm.replyTo = null; if (c.upload) UP.f = null;
+  GE.now.renderRail?.(); GE.now.renderFeed(); GE.you.render();
+  APP.toast(`${ic('threads', 'sm')} Posted to ${esc(s.short || s.title.split(' — ')[0])} · ledger #${e.i}`, 2600); haptic([8, 30, 8]);
+  GE.now._item = { band: 'inside', sit: sitId }; APP.setTab('globe', { force: true });
+  setTimeout(() => { GE.sheet.open(sitId, { post: p.id }); setTimeout(() => GE.roomUI.resynth(GE.rooms.get(sitId), s, { auto: true }), 900); }, 250);
+};
+
 // ---- 90-main.js
 /* Boot, render loop, adaptive-DPR governor, cold open. */
 const HASH = (() => { const o = {}; try { (location.hash || '').slice(1).split('&').forEach((kv) => { const [k, v] = kv.split('='); if (k) o[decodeURIComponent(k)] = v == null ? true : decodeURIComponent(v); }); } catch {} return o; })();
@@ -4807,7 +6750,8 @@ function frame(now) {
   W.simMs = Date.now() + W.offsetH * 3600000; W.t = (W.simMs - NOW) / 1000; W.sun = astro.sun(W.simMs);
   Cam.update(dt);
   if (APP.mode === 'situation' && !Cam.anim && GE.sheet.targetShift != null && !APP.isWide()) Cam.shiftY += (GE.sheet.targetShift - Cam.shiftY) * Math.min(1, dt * 7);
-  if (globeVisible()) {
+  if (globeVisible() && GE.capture.on && GE.capture.cover && !APP.isWide()) { GE.capture.frame(null); }
+  else if (globeVisible()) {
     const [cw, chh] = sizeCanvas();
     if (now - lastDyn > 40) { W.updateDynamic(); lastDyn = now; }
     const view = Cam.view(cw, chh); GE.mainView = view;
@@ -4823,36 +6767,52 @@ function frame(now) {
 }
 document.addEventListener('visibilitychange', () => { if (document.hidden) running = false; else if (!running) { running = true; lastT = performance.now(); requestAnimationFrame(frame); } });
 
-/* ---------- cold open ---------- */
+/* ---------- cold open: a descent from orbit to a person's sealed frame ---------- */
 function coldOpen() {
   const cold = $('#cold'); const app = $('#app');
   const skipAll = HASH.nointro || HASH.tab;
   const red = prefersReduced();
   W.sun = astro.sun(Date.now()); const finalCam = APP.heroCam();
+  const CITIES2 = [{ lat: 40.7585, lon: -73.9855, name: '7TH AVE & W 45TH ST', cam: { lat: 40.7525, lon: -73.9905, range: 0.0016, heading: 0.62, tilt: 1.18 } }, { lat: 35.6595, lon: 139.7005, name: 'SHIBUYA SCRAMBLE', cam: { lat: 35.652, lon: 139.694, range: 0.0024, heading: 0.6, tilt: 1.12 } }, { lat: 41.8789, lon: -87.6359, name: 'STATE & MADISON', cam: { lat: 41.872, lon: -87.643, range: 0.0018, heading: 0.6, tilt: 1.15 } }, { lat: 51.5136, lon: -0.1365, name: 'OXFORD CIRCUS', cam: { lat: 51.508, lon: -0.143, range: 0.0024, heading: 0.6, tilt: 1.12 } }];
+  const tgt = CITIES2.map((c) => ({ c, e: astro.elev(Date.now(), c.lat, c.lon) })).sort((a, b) => a.e - b.e)[0].c;
+  let ended = false;
   const end = () => {
-    if (!APP.intro) return; APP.intro = false; GE.introFade = 1; W.setTime(null);
+    if (ended) return; ended = true; APP.intro = false; GE.introFade = 1; W.setTime(null);
     cold.classList.add('out'); app.classList.remove('intro'); setTimeout(() => cold.remove(), 1100);
-    Cam.cancel(); if (Cam.range > 2.2 && !APP.isWide()) Cam.flyTo(finalCam, { duration: 0.6 });
+    Cam.cancel(); Cam.set(finalCam); if (!APP.isWide()) { Cam.set({ ...finalCam, range: finalCam.range * 0.7 }); Cam.flyTo(finalCam, { duration: 1.2 }); }
     Cam.autoSpin = 0.3; APP.updateChrome(); APP.moveLens();
     if (HASH.tab) APP.setTab(HASH.tab, { force: true });
   };
   APP.intro = true; app.classList.add('intro'); APP.updateChrome();
   if (skipAll) { Cam.set(finalCam); end(); return; }
-  Cam.set({ lat: 8, lon: finalCam.lon + 75, range: 5.8, heading: 0, tilt: 0, shiftY: 0.0, shiftX: 0 });
-  const T = (red ? 1.2 : 3.4) * (HASH.slow ? +HASH.slow : 1); const t0 = performance.now();
-  GE.introFade = 0;
-  if (!red) Cam.flyTo(finalCam, { duration: T });
+  const k = HASH.slow ? +HASH.slow : 1; const TA = (red ? 0.2 : 4.4) * k, TB = TA + 0.8 * k, TC = TB + 2.4 * k;
+  if (!red) { Cam.set({ lat: tgt.lat - 18, lon: tgt.lon - 50, range: 6.4, heading: 0, tilt: 0, shiftY: 0, shiftX: 0 }); Cam.flyTo({ ...tgt.cam, shiftY: 0, shiftX: 0 }, { duration: TA * 0.95 }); }
   else Cam.set(finalCam);
+  GE.introFade = 0; const t0 = performance.now(); const cv = $('#coldCv'); $('#coldTele').textContent = `WITNESS · SEALED · ±4 M · ${tgt.name}`;
+  const caps = [[120, 'ORBIT · GEO IR · 35,786 KM'], [30, 'ORBIT · ISS · 412 KM · 7.66 KM/S'], [0.8, 'SKY · FL350 · 487 KT · ADS-B'], [-1, 'GROUND · CAM 0412 · 1.2 KM']];
+  const pos = (altKm) => clamp(1 - (Math.log10(Math.max(0.05, altKm)) + 1.3) / (Math.log10(36000) + 1.3), 0, 1) * 0.72;
   const tick = () => {
-    if (!APP.intro) return; const u = clamp((performance.now() - t0) / 1000 / T, 0, 1);
-    GE.introFade = ease.out(clamp(u * 2.2, 0, 1));
-    if (!red) W.setTime(Date.now() - (1 - ease.outQuint(u)) * 9 * 3600000);
-    if (u > 0.12) cold.classList.add('s1'); if (u > 0.36) cold.classList.add('s2');
-    if (u >= 1) { setTimeout(end, red ? 200 : 500); return; } requestAnimationFrame(tick);
+    if (ended) return; const el = (performance.now() - t0) / 1000;
+    GE.introFade = ease.out(clamp(el / 1.2, 0, 1)); cold.classList.add('s0');
+    const alt = GE.mainView ? Math.max(0.05, geo.ll(GE.mainView.eye)[2]) : 36000;
+    const lad = $('#ladder'); const H = lad.clientHeight;
+    if (el < TA) {
+      const band = alt > 120 ? 'orbit' : alt > 0.8 ? 'sky' : 'ground';
+      lad.querySelectorAll('.lr').forEach((r) => r.classList.toggle('on', r.dataset.b === band));
+      $('#lmark').style.top = (pos(alt) * H).toFixed(1) + 'px';
+      $('#coldAlt').textContent = 'ALT ' + (alt >= 10 ? fmt.n(Math.round(alt)) + ' KM' : alt >= 1 ? alt.toFixed(1) + ' KM' : fmt.n(Math.round(alt * 1000)) + ' M');
+      const cp = caps.find(([a]) => alt > a) || caps[3]; $('#coldCap').textContent = cp[1];
+    } else {
+      cold.classList.add('s3'); lad.querySelectorAll('.lr').forEach((r) => r.classList.toggle('on', r.dataset.b === 'inside')); $('#lmark').style.top = H - 8 + 'px';
+      GE.paint.draw('crossing', cv, { seed: 31, cam: '@', rec: false, noOSD: true, osdY: -1, t: el });
+      if (el > TB) cold.classList.add('s4');
+      if (el > TC) { setTimeout(end, 300); return; }
+    }
+    requestAnimationFrame(tick);
   };
   requestAnimationFrame(tick);
-  $('#skip').addEventListener('click', (e) => { e.stopPropagation(); Cam.set(finalCam); end(); });
-  cold.addEventListener('click', () => { Cam.set(finalCam); end(); });
+  $('#skip').addEventListener('click', (e) => { e.stopPropagation(); end(); });
+  cold.addEventListener('click', () => end());
 }
 
 /* ---------- boot ---------- */
diff --git a/mobile/vision/src/app.css b/mobile/vision/src/app.css
index 9dbe4726b..1dc9e00bd 100644
--- a/mobile/vision/src/app.css
+++ b/mobile/vision/src/app.css
@@ -572,3 +572,366 @@ input, textarea { font: inherit; color: inherit; }
 @media (prefers-reduced-motion: reduce) {
   *, *::before, *::after { animation-duration: .01ms !important; animation-iteration-count: 1 !important; transition-duration: .12s !important; }
 }
+
+/* =====================================================================================
+   ROUND TWO — God's Eye identity: altitude bands, sensor framing, telemetry voice
+   ===================================================================================== */
+:root {
+  --b-orbit: #B79CFF; --b-sky: #8CD4FF; --b-ground: #FFA53D; --b-inside: #F2CF7A; --harm: #FF3B30;
+  --mono: "JetBrains Mono", ui-monospace, "SF Mono", Menlo, Consolas, "DejaVu Sans Mono", monospace;
+  --bg: #050608; --card: #0B0D11; --card2: #10131a;
+}
+.mono { font-family: var(--mono); letter-spacing: .02em; }
+.tab.on { color: #fff; }
+.tablens { background: rgba(255,255,255,.14); }
+.dot { background: var(--harm); }
+
+/* ---------- hero: the orbit view with a reticle and burned-in telemetry ---------- */
+.now-hero { height: calc(var(--sat) + clamp(330px, 46vh, 440px)); }
+.now-hero .hud { position: absolute; inset: calc(var(--sat) + 8px) 12px auto 12px; height: calc(100% - 150px - var(--sat)); pointer-events: none; }
+.now-hero .hud .wm { position: absolute; left: 6px; top: 4px; font: 800 13px/1 var(--display); letter-spacing: .34em; color: #fff; text-shadow: 0 0 18px rgba(0,0,0,.8); }
+.hb { position: absolute; width: 22px; height: 22px; border: 0 solid rgba(255,255,255,.55); }
+.hb.a { left: 0; top: 26px; border-width: 1.5px 0 0 1.5px; } .hb.b { right: 0; top: 26px; border-width: 1.5px 1.5px 0 0; }
+.hb.c { left: 0; bottom: 0; border-width: 0 0 1.5px 1.5px; } .hb.d { right: 0; bottom: 0; border-width: 0 1.5px 1.5px 0; }
+.xh { position: absolute; left: 50%; top: 52%; width: 46px; height: 46px; margin: -23px; border-radius: 50%; box-shadow: inset 0 0 0 1px rgba(255,255,255,.35); }
+.xh::before, .xh::after { content: ""; position: absolute; background: rgba(255,255,255,.45); }
+.xh::before { left: -14px; right: -14px; top: 50%; height: 1px; } .xh::after { top: -14px; bottom: -14px; left: 50%; width: 1px; }
+.hud-t { position: absolute; left: 30px; right: 30px; bottom: 6px; font-size: 9.5px; color: rgba(220,210,255,.82); letter-spacing: .08em; text-align: center; text-shadow: 0 1px 6px #000; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.now-hero .lt .kicker { font-size: 10.5px; letter-spacing: .12em; color: rgba(255,255,255,.7); }
+.now-hero .lt h1 { font: 800 30px/1.08 var(--display); letter-spacing: -.02em; margin-top: 6px; max-width: 13ch; }
+.counts { display: flex; flex-wrap: wrap; gap: 4px 12px; margin-top: 10px; font-size: 10.5px; letter-spacing: .06em; text-transform: uppercase; color: var(--text3); }
+.counts b { color: var(--text); font-weight: 600; } .counts .w b { color: var(--b-inside); }
+.navbar .wm { font: 800 13px/1 var(--display); letter-spacing: .34em; }
+
+/* ---------- altitude rail (band filter) ---------- */
+.bandrail { position: sticky; top: 0; z-index: 6; display: flex; align-items: stretch; gap: 0; padding: calc(var(--sat) + 8px) 10px 10px; margin-top: -2px; background: linear-gradient(180deg, rgba(5,6,8,.96) 70%, rgba(5,6,8,0)); }
+.bcell { flex: 1; min-width: 0; display: flex; flex-direction: column; align-items: flex-start; gap: 1px; padding: 8px 7px 7px; border-radius: 12px; position: relative; color: var(--text2); transition: background .2s, color .2s; }
+.bcell i { width: 100%; height: 2.5px; border-radius: 2px; background: var(--c); opacity: .45; margin-bottom: 5px; }
+.bcell b { font: 700 10.5px/1.1 var(--mono); letter-spacing: .1em; color: var(--text); }
+.bcell span { font: 600 15px/1.1 var(--display); color: var(--text); }
+.bcell em { font: 500 8.5px/1.2 var(--mono); font-style: normal; letter-spacing: .04em; color: var(--text3); text-transform: uppercase; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; max-width: 100%; }
+.bcell.on { background: color-mix(in oklab, var(--c) 14%, rgba(255,255,255,.04)); box-shadow: inset 0 0 0 1px color-mix(in oklab, var(--c) 55%, transparent); }
+.bcell.on i { opacity: 1; box-shadow: 0 0 10px var(--c); } .bcell.on b { color: var(--c); }
+.rarr { flex: none; width: 6px; align-self: center; height: 1px; background: rgba(255,255,255,.18); }
+.band-h { margin: 2px 16px 10px; padding: 10px 12px; border-radius: 12px; background: color-mix(in oklab, var(--c) 9%, transparent); box-shadow: inset 2px 0 0 var(--c); font-size: 12.5px; color: var(--text2); display: flex; gap: 10px; align-items: baseline; }
+.band-h b { color: var(--c); font: 700 12px var(--mono); letter-spacing: .12em; text-transform: uppercase; }
+.feed-end { text-align: center; font-size: 9.5px; letter-spacing: .1em; color: rgba(246,223,160,.55); padding: 26px 20px 10px; display: flex; gap: 6px; justify-content: center; align-items: center; }
+#feed { display: flex; flex-direction: column; gap: 10px; padding-bottom: 6px; }
+#feed > .fc.wide { margin: 0 12px; }
+
+/* ---------- feed cards: sensor frames ---------- */
+.fc { border-radius: 14px; background: var(--card); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.08); }
+.fc .fr { position: relative; width: 100%; overflow: hidden; background: #06080c; border-radius: 14px 14px 0 0; }
+.fc .fr canvas { position: absolute; inset: 0; width: 100%; height: 100%; display: block; }
+.fc .fr::after { content: ""; position: absolute; inset: 0; pointer-events: none; background: linear-gradient(180deg, rgba(0,0,0,.42), transparent 22%, transparent 74%, rgba(0,0,0,.7)); }
+.bk { position: absolute; z-index: 2; width: 14px; height: 14px; border: 0 solid color-mix(in oklab, var(--c) 85%, white); opacity: .9; pointer-events: none; }
+.bk.a { left: 7px; top: 7px; border-width: 1.5px 0 0 1.5px; } .bk.b { right: 7px; top: 7px; border-width: 1.5px 1.5px 0 0; }
+.bk.c { left: 7px; bottom: 7px; border-width: 0 0 1.5px 1.5px; } .bk.d { right: 7px; bottom: 7px; border-width: 0 1.5px 1.5px 0; }
+.ftop { position: absolute; z-index: 3; left: 14px; right: 14px; top: 11px; display: flex; gap: 6px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .12em; pointer-events: none; }
+.ftop .bt, .tags .bt, .rhead .bt { color: var(--c); padding: 3px 5px 2px; border-radius: 4px; background: rgba(0,0,0,.55); box-shadow: inset 0 0 0 .5px color-mix(in oklab, var(--c) 60%, transparent); font: 700 9px/1 var(--mono); letter-spacing: .12em; }
+.ftop .at { color: rgba(255,255,255,.75); }
+.ftop .lv, .ftop .mine { margin-left: auto; display: inline-flex; gap: 4px; align-items: center; color: #fff; background: rgba(255,59,48,.9); padding: 3px 5px 2px; border-radius: 4px; }
+.ftop .mine { background: var(--b-inside); color: #1b1408; }
+.ftop .lv i { width: 5px; height: 5px; border-radius: 50%; background: #fff; animation: blink 1.2s steps(2) infinite; }
+@keyframes blink { 50% { opacity: 0; } }
+.tele { position: absolute; z-index: 3; left: 14px; right: 14px; bottom: 11px; font: 600 8.5px/1.25 var(--mono); letter-spacing: .07em; color: rgba(255,255,255,.88); text-shadow: 0 1px 3px #000, 0 0 6px #000; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; pointer-events: none; }
+.fc.wide .tele { font-size: 10px; }
+.readout { position: absolute; z-index: 3; left: 14px; bottom: 26px; font: 700 16px/1 var(--mono); letter-spacing: .02em; color: #fff; text-shadow: 0 1px 10px rgba(0,0,0,.9); }
+.a-track.b-sky .readout { color: #fff; } .fc[data-fid="squawk"] .readout { color: #FF6B61; }
+.fseal { position: absolute; z-index: 3; right: 12px; top: 30px; width: 24px; height: 24px; filter: drop-shadow(0 0 8px rgba(233,196,106,.7)); }
+.numov { position: absolute; z-index: 3; inset: auto 14px 26px 14px; }
+.a-number .fr canvas { filter: brightness(.62) saturate(1.1); }
+.numov .big { font: 800 40px/1 var(--display); letter-spacing: -.03em; color: #fff; text-shadow: 0 2px 20px rgba(0,0,0,.8); }
+.numov .big small { font: 600 12px var(--mono); letter-spacing: .06em; color: var(--c); margin-left: 5px; text-transform: uppercase; }
+.numov .nl { font-size: 12px; color: rgba(255,255,255,.82); margin-top: 3px; line-height: 1.25; }
+.numov .nsp { width: 100%; height: 30px; margin-top: 6px; overflow: visible; }
+.r4d { position: absolute; z-index: 3; left: 14px; top: 30px; display: flex; gap: 6px; }
+.fm { padding: 9px 11px 11px; }
+.fm .ttl { font-size: 14.5px; font-weight: 650; line-height: 1.26; letter-spacing: -.01em; display: -webkit-box; -webkit-line-clamp: 3; -webkit-box-orient: vertical; overflow: hidden; }
+.fc.wide .fm .ttl { font-size: 17px; }
+.where { display: flex; flex-wrap: wrap; gap: 2px 8px; margin-top: 6px; font-size: 11.5px; color: var(--text3); }
+.where .d { color: var(--text2); font-weight: 600; font-family: var(--mono); font-size: 10.5px; letter-spacing: .02em; }
+.where span + span::before { content: "·"; margin-right: 8px; color: var(--text4); }
+.soc { display: flex; align-items: center; flex-wrap: wrap; gap: 4px 10px; margin-top: 8px; font-size: 11.5px; color: var(--text3); }
+.soc b { color: var(--text); font-weight: 600; }
+.soc .sl { display: inline-flex; align-items: center; gap: 4px; color: var(--b-inside); } .soc .sl b { color: var(--b-inside); }
+.soc .sl .ic { width: 13px; height: 13px; }
+.who { display: flex; align-items: center; gap: 6px; flex-wrap: wrap; margin-bottom: 6px; font-size: 12px; }
+.who b { font-weight: 650; }
+.bdg { display: inline-flex; align-items: center; gap: 3px; height: 18px; padding: 0 6px; border-radius: 5px; font: 650 9.5px/1 var(--font); letter-spacing: .02em; white-space: nowrap; }
+.bdg .ic { width: 11px; height: 11px; }
+.bdg.there { background: rgba(242,207,122,.16); color: var(--b-inside); box-shadow: inset 0 0 0 .5px rgba(242,207,122,.5); }
+.bdg.sealed { background: rgba(242,207,122,.08); color: var(--gold2); }
+.bdg.local { background: rgba(255,165,61,.12); color: var(--b-ground); }
+.bdg.domain { background: rgba(140,212,255,.12); color: var(--b-sky); }
+.bdg.unv { background: repeating-linear-gradient(135deg, rgba(255,255,255,.06) 0 4px, transparent 4px 8px); color: var(--text3); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.2); }
+.fc .cta { margin-top: 9px; display: inline-flex; align-items: center; gap: 6px; height: 30px; padding: 0 12px; border-radius: 8px; background: color-mix(in oklab, var(--c) 16%, transparent); color: var(--c); font-size: 12.5px; font-weight: 700; box-shadow: inset 0 0 0 .5px color-mix(in oklab, var(--c) 50%, transparent); }
+.fc.mine { box-shadow: inset 0 0 0 1px rgba(242,207,122,.55), 0 0 30px rgba(242,207,122,.12); }
+.fc.flash { animation: flash 1.2s ease; }
+
+/* room card */
+.fc.room { padding: 12px 13px 12px; background: linear-gradient(180deg, rgba(242,207,122,.06), rgba(255,255,255,.015) 40%), var(--card); box-shadow: inset 0 0 0 .5px rgba(242,207,122,.22); }
+.rhead { display: flex; align-items: center; gap: 7px; font-size: 11.5px; color: var(--text2); --c: var(--b-inside); }
+.rtag { display: inline-flex; align-items: center; gap: 4px; font: 700 9px/1 var(--mono); letter-spacing: .12em; color: #1a1306; background: var(--b-inside); padding: 3px 5px 2px; border-radius: 4px; }
+.rtag .ic { width: 11px; height: 11px; stroke-width: 2.4; }
+.lvw { display: inline-flex; align-items: center; gap: 5px; margin-left: 2px; } .lvw b { color: var(--text); }
+.rhead .stack { margin-left: auto; }
+.fc.room h3 { margin: 9px 0 0; font: 750 19px/1.15 var(--display); letter-spacing: -.01em; }
+.claims { margin-top: 10px; display: flex; flex-direction: column; gap: 6px; }
+.cl { display: grid; grid-template-columns: 74px 1fr; gap: 2px 8px; font-size: 13px; line-height: 1.35; color: rgba(240,244,250,.9); }
+.cl b { font: 700 9px/1.9 var(--mono); letter-spacing: .12em; color: var(--text3); }
+.cl.known b { color: var(--b-inside); } .cl.disputed b { color: #FFB25C; } .cl.open b { color: #fff; } .cl.unknown b { color: var(--text3); }
+.cl .cites { grid-column: 2; display: flex; gap: 4px; } .cl .cites i { font: 600 9px/1 var(--mono); font-style: normal; padding: 3px 4px; border-radius: 4px; background: rgba(255,255,255,.07); color: var(--text2); }
+.evs { display: grid; grid-template-columns: repeat(4, 1fr); gap: 6px; margin-top: 12px; }
+.evs .evc { width: 100%; aspect-ratio: 4/3; border-radius: 8px; display: block; background: #06080c; }
+.rfoot { display: flex; justify-content: space-between; align-items: center; margin-top: 11px; font-size: 11.5px; color: var(--text3); }
+.rfoot b { color: var(--text); font-weight: 600; } .rfoot .join { color: var(--b-inside); font-weight: 700; display: inline-flex; gap: 2px; align-items: center; }
+
+/* ---------- sheet: room ---------- */
+.sh-hd .tags { display: flex; gap: 6px; align-items: center; } .sh-hd .tags .age { font-size: 12px; color: var(--text3); }
+.sh-hd .pl b { color: var(--text); font-weight: 600; }
+.presence-row { display: flex; align-items: center; gap: 10px; margin-top: 10px; font-size: 12.5px; color: var(--text2); }
+.presence-row b { color: var(--text); } .presence-row .rate { color: var(--text3); font-family: var(--mono); font-size: 10.5px; }
+.seg2 { display: grid; grid-template-columns: 1fr 1fr; gap: 4px; margin: 12px 0 10px; padding: 3px; border-radius: 12px; background: rgba(255,255,255,.06); }
+.seg2 button { height: 34px; border-radius: 9px; display: flex; align-items: center; justify-content: center; gap: 6px; font-size: 13px; font-weight: 650; color: var(--text2); }
+.seg2 button.on { background: rgba(255,255,255,.14); color: #fff; box-shadow: inset 0 .5px 0 rgba(255,255,255,.3); }
+.seg2 button span { font-size: 11px; color: var(--text3); }
+.synth { border-radius: 14px; padding: 11px 12px 9px; background: linear-gradient(180deg, rgba(183,156,255,.09), rgba(183,156,255,.02)); box-shadow: inset 0 0 0 .5px rgba(183,156,255,.3); }
+.syh { display: flex; align-items: center; gap: 6px; font-size: 11px; color: #CDBBFF; font-weight: 600; }
+.syh span { flex: 1; min-width: 0; }
+.regen { display: inline-flex; gap: 4px; align-items: center; height: 26px; padding: 0 9px; border-radius: 8px; font-size: 11.5px; font-weight: 700; background: rgba(183,156,255,.16); color: #E2D6FF; flex: none; }
+.regen.busy { opacity: .5; }
+.sy { display: grid; grid-template-columns: 74px 1fr; gap: 0 8px; margin-top: 8px; }
+.sy b { font: 700 9px/2.1 var(--mono); letter-spacing: .12em; grid-row: span 9; }
+.sy.kn b { color: var(--b-inside); } .sy.di b { color: #FFB25C; } .sy.un b { color: var(--text3); }
+.sy p { margin: 0 0 4px; font-size: 13px; line-height: 1.38; color: rgba(240,244,250,.9); grid-column: 2; }
+.sy p.none { color: var(--text3); } .sy p.stream { white-space: pre-wrap; font-family: var(--mono); font-size: 11.5px; }
+.syf { margin-top: 6px; font-size: 9.5px; color: var(--text3); letter-spacing: .03em; }
+.cite { display: inline-block; font: 650 9.5px/1 var(--mono); padding: 3px 4px 2px; border-radius: 4px; background: rgba(255,255,255,.08); color: var(--text2); vertical-align: 1px; margin-right: 2px; }
+.cite:active { background: rgba(255,255,255,.2); }
+.sortrow { display: flex; gap: 6px; align-items: center; margin: 14px 0 8px; } .sortrow .sl { font-size: 9.5px; letter-spacing: .12em; color: var(--text3); margin-right: 2px; }
+.chip.sm { height: 28px; padding: 0 11px; font-size: 12.5px; }
+.posts { display: flex; flex-direction: column; gap: 8px; }
+.post { border-radius: 14px; padding: 10px 11px 9px; background: rgba(255,255,255,.035); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.07); transition: box-shadow .4s, background .4s; cursor: pointer; }
+.post.hl { background: rgba(242,207,122,.08); box-shadow: inset 0 0 0 1px rgba(242,207,122,.6); }
+.post.k-question { box-shadow: inset 2px 0 0 #fff, inset 0 0 0 .5px rgba(255,255,255,.07); }
+.post.noted { background: rgba(255,255,255,.02); }
+.post.noted .pt { color: var(--text3); text-decoration: line-through; text-decoration-color: rgba(255,255,255,.25); }
+.post.mine { box-shadow: inset 0 0 0 1px rgba(242,207,122,.45); }
+.ph { display: flex; align-items: flex-start; gap: 8px; }
+.ph .avatar { margin-top: 1px; }
+.pw { flex: 1; min-width: 0; font-size: 12.5px; } .pw b { font-weight: 650; } .pw .pid { font: 600 9.5px var(--mono); color: var(--text3); margin-left: 6px; } .pw .tm { color: var(--text3); margin-left: 6px; font-size: 11.5px; }
+.bds { display: flex; flex-wrap: wrap; gap: 4px; margin-top: 3px; }
+.kind { flex: none; display: inline-flex; align-items: center; gap: 4px; font: 700 9px/1 var(--mono); letter-spacing: .1em; padding: 4px 6px 3px; border-radius: 5px; background: rgba(255,255,255,.07); color: var(--text2); }
+.kind .ic { width: 11px; height: 11px; }
+.kind.k-witness { color: var(--b-inside); background: rgba(242,207,122,.12); } .kind.k-question { color: #fff; background: rgba(255,255,255,.14); }
+.kind.k-correction { color: #FFB25C; background: rgba(255,178,92,.12); } .kind.k-context { color: var(--b-sky); background: rgba(140,212,255,.1); } .kind.k-prediction { color: var(--b-orbit); background: rgba(183,156,255,.12); }
+.pt { margin: 7px 0 0; font-size: 14px; line-height: 1.42; color: rgba(242,245,250,.92); }
+.resolves { display: inline-block; margin-left: 6px; font: 600 9.5px var(--mono); color: var(--b-orbit); letter-spacing: .04em; text-transform: uppercase; }
+.patt { position: relative; margin-top: 8px; border-radius: 10px; overflow: hidden; background: #06080c; aspect-ratio: 16/10; }
+.patt canvas { width: 100%; height: 100%; display: block; }
+.patt .tier { position: absolute; left: 8px; bottom: 8px; display: inline-flex; gap: 4px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .1em; padding: 4px 6px 3px; border-radius: 4px; background: rgba(0,0,0,.6); color: var(--b-inside); }
+.patt .tier .ic { width: 12px; height: 12px; }
+.patt.unverified .tier { color: var(--text2); } .patt.eye .tier { color: var(--b-ground); }
+.patt .plive { position: absolute; right: 8px; top: 8px; display: inline-flex; gap: 5px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .1em; background: rgba(255,59,48,.9); padding: 4px 6px 3px; border-radius: 4px; }
+.patt .plive .dot { background: #fff; width: 5px; height: 5px; }
+.ancs { display: flex; flex-wrap: wrap; gap: 5px; margin-top: 8px; align-items: center; }
+.anc { display: inline-flex; align-items: center; gap: 4px; height: 24px; padding: 0 8px; border-radius: 7px; font-size: 11.5px; font-weight: 600; color: var(--text2); background: rgba(255,255,255,.06); }
+.anc .ic { width: 12px; height: 12px; color: var(--b-ground); }
+.note { margin-top: 9px; border-radius: 10px; padding: 9px 10px; background: rgba(140,212,255,.07); box-shadow: inset 0 0 0 .5px rgba(140,212,255,.3); }
+.note .nh { display: flex; gap: 5px; align-items: center; font-size: 11.5px; font-weight: 700; color: var(--b-sky); }
+.note p { margin: 5px 0 0; font-size: 13px; line-height: 1.4; color: rgba(240,244,250,.92); text-decoration: none; }
+.bridge { margin-top: 8px; display: flex; flex-direction: column; gap: 4px; }
+.br { display: grid; grid-template-columns: 1fr 90px 34px; gap: 8px; align-items: center; font-size: 11px; color: var(--text3); }
+.br b { color: var(--text); font-weight: 600; text-align: right; }
+.br i { height: 5px; border-radius: 3px; background: linear-gradient(90deg, var(--b-sky) calc(var(--v) * 100%), rgba(255,255,255,.1) 0); }
+.note details { margin-top: 6px; font-size: 11.5px; color: var(--text2); } .note summary { cursor: pointer; color: var(--b-sky); font-weight: 600; }
+.note details p { font-size: 12px; color: var(--text2); }
+.answered { margin-top: 8px; display: flex; gap: 5px; align-items: center; font-size: 11.5px; color: var(--b-inside); }
+.answered.open { color: var(--text2); } .answered b { font-weight: 650; }
+.pf { display: flex; align-items: center; gap: 6px; margin-top: 8px; }
+.rxb, .rep { display: inline-flex; align-items: center; gap: 4px; height: 24px; padding: 0 7px; border-radius: 7px; font-size: 11.5px; color: var(--text2); background: rgba(255,255,255,.05); }
+.rcap { margin-left: auto; display: inline-flex; align-items: center; gap: 5px; height: 26px; padding: 0 9px; border-radius: 8px; font-size: 11.5px; font-weight: 700; color: var(--b-inside); background: rgba(242,207,122,.12); }
+.room-srcs { margin-top: 18px; } .room-srcs .h3 { font-size: 11px; font-weight: 700; letter-spacing: .1em; text-transform: uppercase; color: var(--text3); margin-bottom: 4px; }
+.room-srcs .r { grid-template-columns: 30px 1fr; }
+.fine { font-size: 11px; color: var(--text3); margin: 14px 0 90px; }
+/* composer & reactions */
+.roomcomp { position: absolute; z-index: 41; left: 10px; right: 10px; bottom: calc(var(--sab) + 10px); display: none; gap: 8px; align-items: flex-end; }
+.roomcomp.on { display: flex; animation: rise .4s var(--spring); }
+.capbtn { flex: none; width: 66px; height: 58px; border-radius: 18px; display: flex; flex-direction: column; align-items: center; justify-content: center; gap: 2px; background: var(--b-inside); color: #1b1408; font-size: 10.5px; font-weight: 800; box-shadow: 0 8px 30px rgba(242,207,122,.25); }
+.capbtn .ic { width: 22px; height: 22px; stroke-width: 2; }
+.rcin { flex: 1; min-width: 0; border-radius: 18px; padding: 6px; }
+.rcin .kinds { display: none; gap: 4px; overflow-x: auto; scrollbar-width: none; padding: 2px 2px 6px; }
+.roomcomp.typing .kinds { display: flex; }
+.rcin .kinds button { flex: none; display: inline-flex; gap: 4px; align-items: center; height: 26px; padding: 0 9px; border-radius: 8px; font-size: 11.5px; font-weight: 650; color: var(--text2); background: rgba(255,255,255,.06); }
+.rcin .kinds button.on { background: #fff; color: #05070B; }
+.rcrow { display: flex; gap: 6px; align-items: center; }
+.rcrow input { flex: 1; min-width: 0; height: 44px; border: 0; outline: 0; background: transparent; padding: 0 10px; font-size: 15px; }
+.rcrow .send { width: 38px; height: 38px; border-radius: 50%; display: grid; place-items: center; background: rgba(255,255,255,.14); }
+.app[data-mode="situation"] .sheet .sc { padding-bottom: 96px; }
+.rx { position: absolute; z-index: 40; right: 14px; bottom: calc(var(--sab) + 84px); width: 36px; height: 260px; pointer-events: none; display: none; }
+.app[data-mode="situation"] .rx { display: block; }
+.rx span { position: absolute; bottom: 0; left: 6px; animation: floatUp 2.6s ease-out forwards; color: var(--harm); filter: drop-shadow(0 2px 6px rgba(0,0,0,.6)); }
+.rx span:nth-child(3n) { color: var(--b-inside); } .rx span:nth-child(3n+1) { color: #fff; }
+.lbl.speech { padding: 4px 9px 4px 4px; font-size: 11.5px; border-radius: 12px 12px 12px 3px; }
+.lbl.speech .sg { width: 20px; height: 20px; border-radius: 50%; display: grid; place-items: center; background: rgba(255,255,255,.12); color: #fff; }
+.lbl.speech .sg.k-witness { background: var(--b-inside); color: #1b1408; } .lbl.speech .sg.k-question { background: #fff; color: #05070B; }
+.lbl.speech .sg .ic { width: 12px; height: 12px; stroke-width: 2.2; }
+.lbl.speech.hl { box-shadow: inset 0 0 0 1.5px var(--b-inside); }
+@media (min-width: 600px) {
+  .roomcomp { left: 10px; right: auto; width: calc(var(--paneW) - 20px); z-index: 36; }
+  .rx { left: calc(var(--paneW) - 50px); right: auto; z-index: 36; }
+  .bandrail { padding-top: 8px; }
+  .now-hero .hud { display: none; }
+  .now-hero .lt h1 { font-size: 26px; max-width: none; }
+}
+.where { display: block; margin-top: 6px; }
+.where .pl { font-size: 12px; color: var(--text2); white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.where .d { font-size: 9.5px; letter-spacing: .06em; color: var(--text3); margin-top: 2px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.where span + span::before { content: none; }
+.soc span { display: inline-flex; align-items: center; gap: 4px; } .soc .ic { width: 13px; height: 13px; }
+/* accessory: a person live, with a moving thumbnail */
+.accessory .accdot { width: 10px; display: grid; place-items: center; }
+.accessory .accv { width: 54px; height: 30px; border-radius: 6px; flex: none; background: #06080c; }
+/* concept tag sits above the sticky rail on Now */
+.app[data-tab="now"] .concept-tag { top: calc(var(--sat) + 8px); font-size: 8.5px; padding: 2px 6px; }
+.bandrail { padding-top: calc(var(--sat) + 28px); }
+.now-hero .hud { top: calc(var(--sat) + 30px); }
+.now-hero .hud .wm { top: -22px; }
+.hb.a, .hb.b { top: 0; }
+
+/* ---------- capture: dial of four, live, upload, attach ---------- */
+.status .alt { font-size: 10.5px; letter-spacing: .06em; margin-left: 4px; }
+.dial button { padding: 0 2px; }
+.dial { gap: 18px; }
+.livecv { position: absolute; inset: 0; width: 100%; height: 100%; display: none; background: #000; }
+.livecv.on { display: block; }
+.cap-ui.m-live .compass-tape, .cap-ui.m-live .callouts, .cap-ui.m-upload .callouts { display: none; }
+.cap-ui.m-upload::before { content: ""; position: absolute; inset: 0; background: rgba(3,4,7,.62); backdrop-filter: blur(16px); -webkit-backdrop-filter: blur(16px); pointer-events: none; }
+.replyto { position: absolute; top: calc(var(--sat) + 60px); left: 12px; right: 12px; height: 38px; border-radius: 12px; display: flex; align-items: center; gap: 8px; padding: 0 6px 0 12px; font-size: 13px; color: var(--b-inside); }
+.replyto span { flex: 1; } .replyto b { color: #fff; } .replyto button { width: 28px; height: 28px; border-radius: 50%; display: grid; place-items: center; background: rgba(255,255,255,.1); }
+.shutter.s-live i { background: #FF3B30; }
+.shutter.s-live.rec i { border-radius: 8px; transform: scale(.5); }
+.shutter.s-upload i { background: var(--b-inside); }
+#modeHost { position: absolute; inset: 0; pointer-events: none; }
+#modeHost > * { pointer-events: auto; }
+.lv-pre { position: absolute; left: 14px; right: 14px; bottom: calc(var(--sab) + 300px); border-radius: 18px; padding: 14px 15px; font-size: 13.5px; color: var(--text2); }
+.lv-pre b { color: #fff; font-size: 16px; } .lv-pre p { margin: 8px 0 10px; line-height: 1.45; }
+.lvph { display: flex; gap: 10px; align-items: center; }
+.lvnear { display: flex; flex-wrap: wrap; gap: 6px; } .lvnear span { display: inline-flex; gap: 5px; align-items: center; font-size: 12px; height: 26px; padding: 0 9px; border-radius: 8px; background: rgba(242,207,122,.12); color: var(--b-inside); }
+.lvfine { margin-top: 10px; font-size: 9px; letter-spacing: .1em; color: var(--text3); }
+.lv-top { position: absolute; top: calc(var(--sat) + 60px); left: 12px; right: 12px; display: flex; gap: 8px; align-items: center; }
+.lvpill { display: inline-flex; align-items: center; gap: 6px; height: 30px; padding: 0 10px; border-radius: 8px; background: #FF3B30; font: 800 12px/1 var(--mono); letter-spacing: .08em; color: #fff; }
+.lvpill i { width: 7px; height: 7px; border-radius: 50%; background: #fff; animation: blink 1.2s steps(2) infinite; }
+.lvpill.pre { background: rgba(255,255,255,.12); } .lvpill b { font-weight: 700; }
+.lvv { display: inline-flex; align-items: center; gap: 5px; height: 30px; padding: 0 10px; border-radius: 8px; font-size: 13px; }
+.lvseal { margin-left: auto; display: inline-flex; align-items: center; gap: 5px; height: 30px; padding: 0 9px; border-radius: 8px; background: rgba(0,0,0,.45); color: var(--b-inside); font: 700 10px/1 var(--mono); letter-spacing: .1em; }
+.lv-to { position: absolute; top: calc(var(--sat) + 100px); left: 12px; height: 30px; border-radius: 8px; display: inline-flex; align-items: center; gap: 6px; padding: 0 10px; font-size: 12px; color: var(--text2); } .lv-to b { color: var(--b-inside); }
+.lv-chat { position: absolute; left: 12px; right: 70px; bottom: calc(var(--sab) + 330px); display: flex; flex-direction: column; gap: 6px; justify-content: flex-end; mask-image: linear-gradient(to top, #000 70%, transparent); -webkit-mask-image: linear-gradient(to top, #000 70%, transparent); pointer-events: none !important; }
+.lv-chat .bub .bx { padding: 6px 10px; font-size: 12.5px; } .lv-chat .lj { display: flex; gap: 6px; align-items: center; font-size: 11.5px; color: rgba(255,255,255,.75); text-shadow: 0 1px 4px #000; }
+.lvrx { position: absolute; right: 14px; bottom: calc(var(--sab) + 330px); width: 36px; height: 260px; pointer-events: none !important; }
+.lvrx span { position: absolute; bottom: 0; left: 6px; animation: floatUp 2.6s ease-out forwards; color: var(--harm); } .lvrx span:nth-child(2n) { color: #fff; }
+.lv-tele { position: absolute; left: 14px; right: 14px; bottom: calc(var(--sab) + 302px); font-size: 9.5px; letter-spacing: .06em; color: rgba(255,255,255,.88); text-shadow: 0 1px 3px #000; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.lv-chain { position: absolute; left: 0; right: 0; bottom: calc(var(--sab) + 214px); display: flex; align-items: center; gap: 0; overflow-x: auto; padding: 0 14px; scrollbar-width: none; }
+.lv-chain::-webkit-scrollbar { display: none; }
+.lv-chain .seg { flex: none; width: 86px; border-radius: 10px; padding: 5px; background: rgba(8,10,14,.78); box-shadow: inset 0 0 0 .5px rgba(242,207,122,.45); display: flex; flex-direction: column; gap: 3px; }
+.lv-chain .seg img { width: 100%; height: 34px; object-fit: cover; border-radius: 6px; display: block; }
+.lv-chain .seg .si { font-size: 9px; color: var(--text3); } .lv-chain .seg .sh { font-size: 9px; color: var(--b-inside); }
+.lv-chain .seg .sk { display: inline-flex; gap: 3px; align-items: center; font-size: 9px; color: var(--text2); } .lv-chain .seg .sk .ic { width: 11px; height: 11px; }
+.lv-chain .seg.cur { box-shadow: inset 0 0 0 .5px rgba(255,255,255,.25); }
+.lv-chain .seg .fill { height: 34px; border-radius: 6px; background: rgba(255,255,255,.06); overflow: hidden; } .lv-chain .seg .fill i { display: block; height: 100%; width: 0; background: linear-gradient(90deg, rgba(242,207,122,.15), rgba(242,207,122,.45)); }
+.lv-chain .ln { flex: none; width: 12px; height: 2px; background: linear-gradient(90deg, var(--b-inside), rgba(242,207,122,.3)); }
+.lv-chain .seg.flash { animation: flash 1.2s ease; }
+.up { position: absolute; left: 12px; right: 12px; top: calc(var(--sat) + 62px); max-height: calc(100% - var(--sat) - 62px - var(--sab) - 230px); overflow: auto; border-radius: 20px; padding: 14px; font-size: 13.5px; color: var(--text2); scrollbar-width: none; }
+.uph { display: flex; justify-content: space-between; align-items: center; gap: 10px; } .uph b { color: #fff; font-size: 16px; }
+.up p { margin: 8px 0 12px; line-height: 1.45; } .up p b { color: #fff; }
+.tierb { display: inline-flex; gap: 4px; align-items: center; font: 700 9px/1 var(--mono); letter-spacing: .1em; padding: 4px 6px 3px; border-radius: 4px; background: rgba(0,0,0,.6); color: var(--b-inside); }
+.tierb.unv { color: var(--text2); background: repeating-linear-gradient(135deg, rgba(255,255,255,.08) 0 4px, rgba(0,0,0,.5) 4px 8px); box-shadow: inset 0 0 0 .5px rgba(255,255,255,.25); }
+.drop { display: flex; flex-direction: column; align-items: center; gap: 4px; padding: 22px 12px; border-radius: 16px; border: 1.5px dashed rgba(255,255,255,.22); color: var(--text2); cursor: pointer; margin-bottom: 10px; text-align: center; }
+.drop b { color: #fff; font-size: 15px; } .drop span { font-size: 12px; color: var(--text3); }
+.up .fine { margin: 10px 0 0; font-size: 9px; letter-spacing: .1em; text-align: center; }
+.upimg { position: relative; border-radius: 12px; overflow: hidden; } .upimg img { width: 100%; display: block; max-height: 220px; object-fit: cover; } .upimg .tierb { position: absolute; left: 8px; top: 8px; }
+.exif { display: grid; grid-template-columns: 1fr 1fr; gap: 6px 12px; margin: 10px 0; font-size: 10px; letter-spacing: .03em; }
+.exif div { display: flex; flex-direction: column; gap: 2px; min-width: 0; } .exif span { color: var(--text3); font-size: 8.5px; letter-spacing: .12em; } .exif b { color: #fff; font-weight: 600; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
+.placer { position: relative; border-radius: 12px; overflow: hidden; touch-action: none; } .placer canvas { width: 100%; display: block; }
+.placer .pin { position: absolute; width: 34px; height: 34px; margin: -34px 0 0 -17px; display: grid; place-items: center; color: #1b1408; background: var(--b-inside); border-radius: 50% 50% 50% 4px; transform: rotate(-45deg); box-shadow: 0 6px 18px rgba(0,0,0,.6); cursor: grab; touch-action: none; }
+.placer .pin .ic { transform: rotate(45deg); }
+.placer .hint { position: absolute; left: 8px; bottom: 8px; font-size: 9.5px; letter-spacing: .06em; color: #fff; background: rgba(0,0,0,.6); padding: 4px 6px; border-radius: 4px; }
+.uptime { display: grid; grid-template-columns: auto 1fr auto; gap: 10px; align-items: center; margin: 12px 0; font-size: 12px; } .uptime input { accent-color: var(--b-inside); } .uptime b { color: #fff; font-size: 11.5px; }
+.attach-ov { position: absolute; inset: 0; z-index: 78; display: none; align-items: flex-end; justify-content: center; background: rgba(0,0,0,.5); }
+.attach-ov.on { display: flex; animation: viewIn .3s var(--out); }
+.att { width: 100%; max-width: 560px; max-height: 92%; overflow: auto; border-radius: 28px 28px 0 0; padding: 6px 16px calc(var(--sab) + 16px); scrollbar-width: none; }
+.att .grab { height: 18px; display: grid; place-items: center; } .att .grab::before { content: ""; width: 38px; height: 5px; border-radius: 3px; background: rgba(255,255,255,.3); }
+.ath { display: grid; grid-template-columns: 112px 1fr; gap: 12px; align-items: center; }
+.atimg { position: relative; border-radius: 12px; overflow: hidden; aspect-ratio: 4/3; background: #06080c; } .atimg img { width: 100%; height: 100%; object-fit: cover; display: block; } .atimg .tierb { position: absolute; left: 6px; bottom: 6px; font-size: 7.5px; }
+.ath h2 { margin: 0; font: 750 21px/1.15 var(--display); } .ath p { margin: 4px 0 0; font-size: 10.5px; color: var(--text3); letter-spacing: .02em; }
+.ath2 { margin: 14px 0 7px; font-size: 11px; font-weight: 700; letter-spacing: .08em; text-transform: uppercase; color: var(--text3); }
+.sugs { display: flex; flex-direction: column; gap: 6px; }
+.sug { display: flex; align-items: center; gap: 10px; padding: 10px 12px; border-radius: 14px; background: rgba(255,255,255,.05); text-align: left; box-shadow: inset 0 0 0 .5px rgba(255,255,255,.08); }
+.sug i { width: 9px; height: 9px; border-radius: 50%; background: var(--c); box-shadow: 0 0 10px var(--c); flex: none; }
+.sug span { flex: 1; min-width: 0; } .sug b { display: block; font-size: 14.5px; } .sug small { font-size: 12px; color: var(--text3); }
+.sug em { width: 22px; height: 22px; border-radius: 50%; display: grid; place-items: center; box-shadow: inset 0 0 0 1.5px rgba(255,255,255,.25); color: transparent; flex: none; }
+.sug.on { background: rgba(242,207,122,.1); box-shadow: inset 0 0 0 1px rgba(242,207,122,.55); } .sug.on em { background: var(--b-inside); color: #1b1408; box-shadow: none; }
+.kinds2, .prec { display: flex; gap: 6px; flex-wrap: wrap; }
+.kinds2 button, .prec button { height: 32px; padding: 0 12px; border-radius: 10px; font-size: 13px; font-weight: 650; color: var(--text2); background: rgba(255,255,255,.06); }
+.kinds2 button.on, .prec button.on { background: #fff; color: #05070B; }
+.prec { display: grid; grid-template-columns: repeat(3, 1fr); }
+.att textarea { width: 100%; margin-top: 10px; border: 0; outline: 0; resize: none; border-radius: 12px; padding: 10px 12px; background: rgba(255,255,255,.06); font-size: 14.5px; }
+.fine2 { font-size: 11.5px; color: var(--text3); margin: 7px 2px 0; line-height: 1.4; } .fine2.priv { display: flex; gap: 6px; align-items: flex-start; margin: 10px 2px 12px; }
+.att .row2.holo { margin-top: 10px; border-radius: 14px; background: rgba(255,255,255,.04); }
+.lbl.eyelbl { font-size: 11px; padding: 4px 9px 4px 4px; }
+.lbl.eyelbl .ei { width: 20px; height: 20px; border-radius: 50%; display: grid; place-items: center; background: var(--b-inside); color: #1b1408; }
+.lbl.eyelbl .ei.k-cctv { background: var(--b-ground); } .lbl.eyelbl.k-you { box-shadow: inset 0 0 0 1.5px var(--b-inside), 0 0 24px rgba(242,207,122,.35); }
+.app[data-tab="capture"] .concept-tag { top: auto; bottom: calc(var(--sab) + 200px); left: 14px; right: auto; }
+.cap-top .st { white-space: nowrap; overflow: hidden; text-overflow: ellipsis; min-width: 0; }
+.cap-top .st:first-child { flex: 1 1 auto; } .cap-top .st:last-child { flex: 0 1 auto; }
+.lv-chat { right: 120px; } .lv-chat .bub { max-width: 100%; }
+.att { background: linear-gradient(180deg, rgba(255,255,255,.05), rgba(255,255,255,.01)), rgba(13,16,22,.97); }
+
+/* ---------- cold open: the descent ---------- */
+.cold { justify-content: center; padding: 0; background: radial-gradient(120% 80% at 50% 50%, transparent 40%, rgba(0,0,0,.55)); }
+.ladder { position: absolute; left: 16px; top: 50%; transform: translateY(-50%); height: 300px; width: 120px; display: flex; flex-direction: column; justify-content: space-between; opacity: 0; transition: opacity .6s; }
+.cold.s0 .ladder { opacity: 1; }
+.ladder::before { content: ""; position: absolute; left: 4px; top: 6px; bottom: 6px; width: 1px; background: linear-gradient(var(--b-orbit), var(--b-sky), var(--b-ground), var(--b-inside)); opacity: .5; }
+.lr { position: relative; padding-left: 18px; display: flex; flex-direction: column; gap: 2px; opacity: .38; transition: opacity .4s; }
+.lr i { position: absolute; left: 0; top: 3px; width: 9px; height: 9px; border-radius: 50%; box-shadow: inset 0 0 0 1.5px var(--c); }
+.lr b { font: 700 11px/1 var(--mono); letter-spacing: .16em; color: var(--c); } .lr span { font: 500 9px/1 var(--mono); letter-spacing: .06em; color: rgba(255,255,255,.6); }
+.lr.on { opacity: 1; } .lr.on i { background: var(--c); box-shadow: 0 0 12px var(--c); }
+.lmark { position: absolute; left: -3px; width: 15px; height: 2px; background: #fff; box-shadow: 0 0 10px #fff; top: 0; transition: top .15s linear; }
+.calt { position: absolute; left: 16px; top: calc(50% + 172px); font-size: 22px; font-weight: 700; letter-spacing: .02em; color: #fff; text-shadow: 0 2px 16px #000; opacity: 0; transition: opacity .5s; }
+.cold.s0 .calt { opacity: 1; }
+.ccap { position: absolute; left: 16px; right: 16px; bottom: calc(var(--sab) + 40px); font-size: 11px; letter-spacing: .12em; color: rgba(255,255,255,.85); text-shadow: 0 1px 8px #000; }
+.cwit { position: absolute; left: 50%; top: 50%; width: min(78vw, 360px); aspect-ratio: 440/560; transform: translate(-50%, -50%) scale(1.25); opacity: 0; border-radius: 6px; overflow: hidden; transition: opacity .7s ease, transform 1.4s var(--out); --c: var(--b-inside); box-shadow: 0 30px 80px rgba(0,0,0,.6); }
+.cwit canvas { width: 100%; height: 100%; display: block; }
+.cwit .tele { position: absolute; left: 14px; right: 14px; bottom: 11px; font: 600 9.5px/1.2 var(--mono); letter-spacing: .08em; color: #fff; text-shadow: 0 1px 4px #000; }
+.cold.s3 .cwit { opacity: 1; transform: translate(-50%, -58%) scale(1); }
+.cold.s3 .ladder, .cold.s3 .calt { opacity: .0; }
+.cttl { position: absolute; left: 0; right: 0; bottom: calc(var(--sab) + 9vh); text-align: center; }
+.cttl .word { font: 800 34px/1 var(--display); letter-spacing: .3em; margin-left: .3em; opacity: 0; transition: opacity 1s ease, letter-spacing 1.8s var(--out); }
+.cttl .tag { font: 600 12px/1.4 var(--mono); letter-spacing: .2em; text-transform: uppercase; color: var(--b-inside); margin-top: 12px; opacity: 0; transition: opacity 1s ease .3s; }
+.cold.s4 .cttl .word { opacity: 1; letter-spacing: .2em; } .cold.s4 .cttl .tag { opacity: 1; }
+.cold.s3 .ccap { opacity: 0; }
+.rooms-why { margin: 8px 20px 4px; font-size: 13px; line-height: 1.45; color: var(--text2); }
+.rooms-why b { color: var(--text); font-weight: 600; }
+.rooms-live { display: flex; flex-direction: column; gap: 10px; padding: 0 12px; }
+@media (min-width: 600px) {
+  .now-hero { height: auto; padding-top: calc(var(--sat) + 46px); }
+  .now-hero .hud { display: block; position: absolute; top: calc(var(--sat) + 30px); left: 20px; right: 20px; height: 1px; }
+  .now-hero .hud .hb, .now-hero .hud .xh, .now-hero .hud .hud-t { display: none; }
+  .now-hero .hud .wm { left: 0; top: -14px; }
+  .concept-tag, .app[data-tab] .concept-tag, .app[data-mode="situation"] .concept-tag { top: calc(var(--sat) + 62px); right: 66px; left: auto; bottom: auto; }
+  .app[data-tab="now"] .concept-tag { top: calc(var(--sat) + 62px); }
+}
+/* LIVE is not harm: hazard red stays reserved for things that hurt people */
+.dot { background: #fff; }
+@keyframes pulse { 0% { box-shadow: 0 0 0 0 rgba(255,255,255,.55); } 70% { box-shadow: 0 0 0 7px rgba(255,255,255,0); } 100% { box-shadow: 0 0 0 0 rgba(255,255,255,0); } }
+.ftop .lv, .patt .plive { background: rgba(255,255,255,.94); color: #05070B; }
+.ftop .lv i, .patt .plive .dot { background: #05070B; }
+.lvpill { background: #fff; color: #05070B; } .lvpill i { background: #FF3B30; }
+.ribbon .nowbtn.live { background: rgba(255,255,255,.14); color: #fff; }
+.ribbon.breath::before { animation: none; }
+.badge.live .dot { background: #fff; }
+/* instrument readouts in the brief */
+.metric .v { font: 700 21px/1.1 var(--mono); letter-spacing: -.02em; }
+.metric .v small { font-family: var(--font); }
+.metric .l { font-size: 11.5px; } .metric .s { font-family: var(--mono); font-size: 9.5px; letter-spacing: .03em; }
diff --git a/mobile/vision/src/app.html b/mobile/vision/src/app.html
index dc0cadfb3..345de35cc 100644
--- a/mobile/vision/src/app.html
+++ b/mobile/vision/src/app.html
@@ -129,6 +129,8 @@
   <button class="backbtn circ glass" id="back" aria-label="Back"><svg class="ic"><use href="#i-chevl"/></svg></button>
   <div class="sitbtns" id="sitbtns"><button class="circ glass" id="sitFollow" aria-label="Follow"><svg class="ic"><use href="#i-bellplus"/></svg></button><button class="circ glass" id="sitShare" aria-label="Share"><svg class="ic"><use href="#i-share"/></svg></button></div>
   <div class="sheet glass strong" id="sheet"><div class="grab" id="grab"></div><div class="sc" id="sheetC"></div></div>
+  <div class="rx" id="rx" aria-hidden="true"></div>
+  <div class="roomcomp" id="roomComp"></div>
 
   <div class="ride" id="ride"></div>
   <section id="v-capture" class="view" aria-label="Capture"></section>
@@ -142,7 +144,7 @@
       <button class="tab on" data-tab="now" role="tab"><svg class="ic"><use href="#i-radiowaves"/></svg><span>Now</span></button>
       <button class="tab" data-tab="globe" role="tab"><svg class="ic"><use href="#i-globe"/></svg><span>Globe</span></button>
       <button class="tab" data-tab="capture" role="tab"><svg class="ic"><use href="#i-viewfinder"/></svg><span>Capture</span></button>
-      <button class="tab" data-tab="threads" role="tab"><svg class="ic"><use href="#i-threads"/></svg><span>Threads</span></button>
+      <button class="tab" data-tab="threads" role="tab"><svg class="ic"><use href="#i-threads"/></svg><span>Rooms</span></button>
       <button class="tab" data-tab="you" role="tab"><svg class="ic"><use href="#i-person"/></svg><span>You</span></button>
     </div>
     <button class="accessory glass" id="accMini"></button>
@@ -151,14 +153,17 @@
 
   <div class="morph" id="morph"></div>
   <div class="seal-ov" id="sealOv"></div>
+  <div class="attach-ov" id="attachOv"></div>
   <div class="inspector" id="inspector"></div>
   <div class="toastp glass" id="toast"></div>
   <div class="concept-tag">Concept · illustrative data</div>
   <div class="cold" id="cold">
     <button class="skip glass" id="skip">Skip</button>
-    <svg class="eye" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.1"><path d="M2.6 12S6 5.6 12 5.6 21.4 12 21.4 12 18 18.4 12 18.4 2.6 12 2.6 12Z"/><circle cx="12" cy="12" r="3.6"/><circle cx="12" cy="12" r="1.2" fill="currentColor"/></svg>
-    <div class="word">God’s Eye</div>
-    <div class="tag">The window to the world.</div>
+    <div class="ladder" id="ladder"><div class="lr" data-b="orbit" style="--c:var(--b-orbit)"><i></i><b>ORBIT</b><span>36,000–400 KM</span></div><div class="lr" data-b="sky" style="--c:var(--b-sky)"><i></i><b>SKY</b><span>15 KM</span></div><div class="lr" data-b="ground" style="--c:var(--b-ground)"><i></i><b>GROUND</b><span>0 M</span></div><div class="lr" data-b="inside" style="--c:var(--b-inside)"><i></i><b>INSIDE</b><span>A WITNESS</span></div><div class="lmark" id="lmark"></div></div>
+    <div class="calt mono" id="coldAlt">ALT 35,786 KM</div>
+    <div class="ccap mono" id="coldCap"></div>
+    <div class="cwit" id="coldWit"><canvas id="coldCv" width="440" height="560"></canvas><i class="bk a"></i><i class="bk b"></i><i class="bk c"></i><i class="bk d"></i><svg class="fseal"><use href="#i-seal"/></svg><div class="tele mono" id="coldTele">WITNESS · SEALED · ±4 M</div></div>
+    <div class="cttl"><div class="word">GOD’S EYE</div><div class="tag">From orbit to the witness.</div></div>
   </div>
 </div>
 <!--@TEX-->
diff --git a/mobile/vision/src/js/10-data.js b/mobile/vision/src/js/10-data.js
index 2b3f9055a..cf0051c2f 100644
--- a/mobile/vision/src/js/10-data.js
+++ b/mobile/vision/src/js/10-data.js
@@ -279,6 +279,24 @@ const PEOPLE = {
   crowd: { h: 'row_m_seat14', name: 'Lena', hue: 300 },
   news: { h: 'chopper_cam9', name: 'Desk 9', hue: 10 },
   ai: { h: 'claude', name: 'AI (proposal)', hue: 260, ai: true },
+  // round two: people across the bands (all fictional)
+  nadia: { h: 'nadia_basco', name: 'Nadia R.', hue: 18, home: [20.45, 121.97], where: 'Basco, Batanes' },
+  rafa: { h: 'rafa_aparri', name: 'Rafael D.', hue: 140, home: [18.36, 121.64], where: 'Aparri' },
+  mei: { h: 'mei_taitung', name: 'Mei-Ling C.', hue: 345, home: [22.76, 121.14], where: 'Taitung' },
+  joon: { h: 'joon_pilotboat', name: 'Joon-ho P.', hue: 190, domain: 'Mariner', home: [22.61, 120.28], where: 'Kaohsiung' },
+  lin: { h: 'lin_forecasts', name: 'Lin W.', hue: 225, domain: 'Met', where: 'Taipei' },
+  repost: { h: 'breaking_now_24', name: 'breaking_now_24', hue: 0 },
+  aiko: { h: 'aiko_sendai', name: 'Aiko S.', hue: 300, home: [38.27, 140.87], where: 'Sendai' },
+  tetsu: { h: 'tetsu_rail', name: 'Tetsuya O.', hue: 60, domain: 'Rail ops', where: 'Fukushima' },
+  tomas: { h: 'tomas_atc', name: 'Tomás V.', hue: 205, domain: 'Pilot', where: 'Reykjavík' },
+  seat: { h: 'seat_23F', name: 'Passenger, 23F', hue: 40 },
+  ines: { h: 'ines_coimbra', name: 'Inês M.', hue: 330, home: [40.2, -8.42], where: 'Coimbra' },
+  bomb: { h: 'bombeiro_ruiz', name: 'Cpt. Ruiz', hue: 8, domain: 'First responder', home: [40.1, -8.0], where: 'Pampilhosa' },
+  carla: { h: 'carla_avellaneda', name: 'Carla G.', hue: 280, home: [-34.66, -58.37], where: 'Avellaneda' },
+  dev: { h: 'dev_storms', name: 'Devansh K.', hue: 110, domain: 'Storm spotter', where: 'Arlington, TX' },
+  yuki: { h: 'yuki_kagoshima', name: 'Yuki T.', hue: 170, home: [31.6, 130.56], where: 'Kagoshima' },
+  ola: { h: 'ola_tromso', name: 'Ola B.', hue: 150, home: [69.65, 18.96], where: 'Tromsø' },
+  amara: { h: 'amara_lakefront', name: 'Amara J.', hue: 25, home: [41.88, -87.62], where: 'Chicago' },
 };
 
 Object.assign(GE, { AP, apByIata, FLIGHTS, flightAt, OPNAME, LANES, LANE_V, SHIPS, shipAt, SATS, ISS, CSS, satAt, QUAKES, BIGQ, FIRES, FIRE_CLUSTERS, CYCLONE, CITY_V, PEOPLE });
diff --git a/mobile/vision/src/js/30-world.js b/mobile/vision/src/js/30-world.js
index 8781d7cd6..6c0b5919f 100644
--- a/mobile/vision/src/js/30-world.js
+++ b/mobile/vision/src/js/30-world.js
@@ -320,6 +320,9 @@ W.updateDynamic = function () {
   if (W.on('wind')) for (const w of WIND) { const age = ((t / w.life + w.ph) % 1 + 1) % 1; let la = w.lat, lo = w.lon; const steps = 4, dtH = (age * w.life) / 3600 / steps; for (let k = 0; k < steps; k++) { const [u, v] = windVel(la, lo, t); la += v * dtH; lo += u * dtH; } const [u, v] = windVel(la, lo, t); const fade = Math.sin(age * Math.PI); pushSpr(a, geo.vec(la, lo, 3), [0.75, 0.85, 1, 0.55 * fade], 14, 15, Math.atan2(u * Math.cos(la * D2R), v), -1e9, 1e9, 0, 0, 0.1); }
   for (const hh of W.userHolos) pushSpr(a, geo.vec(hh.lat, hh.lon, 0.06), [1, 0.85, 0.45, 1], 24, 6, -10, -1e9, 1e9, 0, 0.2, 0.4);
   if (W.activeExtrasId === 'climb') { const f = clamp((W.simMs - GE.T_CLIMB) / (2.23 * 3600000), 0, 1); const [la, lo] = geo.offset(40.7553, -73.9838, 16, 23.5); pushSpr(a, geo.vec(la, lo, (12 + f * 372) / 1000), [1, 0.3, 0.3, 1], 16, 9, -10, -1e9, 1e9, 0, 0.7, 0.9); }
+  for (const sp of W.extraSprites || []) pushSpr(a, sp.v, sp.col, sp.size || 24, sp.glyph ?? 9, -10, -1e9, 1e9, 0, sp.seed || 0.3, 0.8);
+  // eyes: people and cameras looking right now
+  if (W.on('cctv') || W.on('signed') || W.on('streams')) for (const e of GE.EYES || []) pushSpr(a, geo.vec(e.lat, e.lon, 0.05), e.kind === 'you' ? [1, 0.9, 0.55, 1] : e.kind === 'cctv' ? [1, 0.66, 0.26, 1] : [0.96, 0.82, 0.48, 1], e.kind === 'you' ? 26 : 15, 9, -10, -1e9, 1e9, 0, e.lat * 0.1, 0.6);
   // situation pins
   for (const p of W.situationPins) pushSpr(a, geo.vec(p.lat, p.lon, 0.2), p.col, p.size || 16, 9, -10, -1e9, 1e9, 0, p.seed || 0, 0.6);
   // selection highlight
@@ -336,6 +339,7 @@ W.updateDynamic = function () {
   }
   if (W.selRoute) pushPolyline(ln, W.selRoute, [1, 0.85, 0.45, 0.8], 1);
   for (const extra of W.extraLines) pushPolyline(ln, extra.pts, extra.col, extra.dashed || 0);
+  if (GE.eyeLines && (W.on('cctv') || W.on('signed') || W.on('streams'))) for (const ex of GE.eyeLines(W.lastRange)) pushPolyline(ln, ex.pts, ex.col, ex.dashed || 0);
   for (const hh of W.userHolos) pushPolyline(ln, [geo.vec(hh.lat, hh.lon, 0), geo.vec(hh.lat, hh.lon, 0.06)], [1, 0.85, 0.5, 0.9]);
   uploadDyn('dynLineBuf', 'dynLineVao', 'dynLineCap', 'dynLineCount', ln, 'line');
 };
@@ -526,14 +530,14 @@ W.post = function (chain, outFb, outW, outH, mode, opts) {
   gl.viewport(0, 0, opts.vpW ?? (outFb ? outW : gl.drawingBufferWidth), opts.vpH ?? (outFb ? outH : gl.drawingBufferHeight));
   GL.bindTex(Cp, 'uScene', chain.scene.tex, 0); GL.bindTex(Cp, 'uBloom', bloomOn ? lv[0].b.tex : lv[0].a.tex, 1);
   gl.uniform2f(Cp.u.uTexel, 1 / chain.w, 1 / chain.h);
-  gl.uniform1f(Cp.u.uExposure, (opts.exposure ?? 1) * (mode === 2 ? 1.25 : 0.62));
+  gl.uniform1f(Cp.u.uExposure, (opts.exposure ?? 1) * (mode === 2 ? 1.25 : mode === 0 ? 0.58 : 0.62));
   gl.uniform1f(Cp.u.uBloomK, bloomOn ? (mode === 4 ? 0.3 : 0.16) : 0);
   gl.uniform1f(Cp.u.uVig, opts.vig ?? (mode === 1 ? 0.25 : 0.9));
   gl.uniform1f(Cp.u.uGrain, (opts.grain ?? W.quality.grain) && mode !== 1 ? 0.022 : 0);
   gl.uniform1f(Cp.u.uT, performance.now() / 1000 % 100);
   gl.uniform1f(Cp.u.uFade, opts.fade ?? 1);
   gl.uniform1f(Cp.u.uFxaa, 1);
-  gl.uniform1f(Cp.u.uSat, mode === 1 ? 1.0 : 1.08);
+  gl.uniform1f(Cp.u.uSat, mode === 1 ? 1.0 : 1.12);
   gl.uniform1i(Cp.u.uMode, mode);
   gl.uniform3fv(Cp.u.uLift, [0.00017, 0.00038, 0.001]);
   gl.uniform3fv(Cp.u.uGain, mode === 0 ? [1.02, 1.0, 0.97] : [1, 1, 1]);
diff --git a/mobile/vision/src/js/36-paint.js b/mobile/vision/src/js/36-paint.js
new file mode 100644
index 000000000..4ebb40d2d
--- /dev/null
+++ b/mobile/vision/src/js/36-paint.js
@@ -0,0 +1,747 @@
+/* Painters — procedural sensor frames. Every feed card, room attachment and capture scene is drawn
+   here as the instrument that saw it would show it: IR cloud tops with an enhancement table, radar
+   reflectivity in dBZ bins over a street grid, CCTV frames with burned-in OSD, SAR speckle, shake maps,
+   long-exposure launch arcs. Geography comes from the bundled NASA masks; weather and people are
+   synthetic (Concept · illustrative data). */
+const PT = (GE.paint = {});
+const MONO = 'ui-monospace, "SF Mono", "JetBrains Mono", Menlo, Consolas, "DejaVu Sans Mono", monospace';
+PT.MONO = MONO;
+const hexrgb = (s) => [parseInt(s.slice(1, 3), 16), parseInt(s.slice(3, 5), 16), parseInt(s.slice(5, 7), 16)];
+const mk = (w, h) => { const c = document.createElement('canvas'); c.width = Math.max(1, w | 0); c.height = Math.max(1, h | 0); return c; };
+PT.mk = mk;
+
+/* ---------- value noise + fbm ---------- */
+function noiseGen(seed) {
+  const r = rng(seed * 7919 + 13); const p = new Uint8Array(512); const v = new Float32Array(256);
+  for (let i = 0; i < 256; i++) { p[i] = i; v[i] = r(); }
+  for (let i = 255; i > 0; i--) { const j = Math.floor(r() * (i + 1)); const t = p[i]; p[i] = p[j]; p[j] = t; }
+  for (let i = 0; i < 256; i++) p[i + 256] = p[i];
+  const n = (x, y) => {
+    const xi = Math.floor(x), yi = Math.floor(y), xf = x - xi, yf = y - yi, X = xi & 255, Y = yi & 255;
+    const u = xf * xf * (3 - 2 * xf), w = yf * yf * (3 - 2 * yf);
+    const a = v[p[p[X] + Y]], b = v[p[p[X + 1] + Y]], c = v[p[p[X] + Y + 1]], d = v[p[p[X + 1] + Y + 1]];
+    return a + (b - a) * u + (c - a) * w + (a - b - c + d) * u * w;
+  };
+  n.fbm = (x, y, o = 5, g = 0.5, l = 2.03) => { let s = 0, a = 0.5, f = 1, t = 0; for (let i = 0; i < o; i++) { s += a * n(x * f + i * 17.3, y * f - i * 9.1); t += a; a *= g; f *= l; } return s / t; };
+  n.ridge = (x, y, o = 5) => { let s = 0, a = 0.5, f = 1, t = 0; for (let i = 0; i < o; i++) { const q = 1 - Math.abs(n(x * f + i * 5.2, y * f + i * 1.7) * 2 - 1); s += a * q * q; t += a; a *= 0.5; f *= 2.1; } return s / t; };
+  return n;
+}
+PT.noise = noiseGen;
+
+/* ---------- colour ramps → 256 LUT ---------- */
+function lut(stops) {
+  const L = new Uint8ClampedArray(256 * 3); const S = stops.map(([t, c]) => [t, hexrgb(c)]);
+  for (let i = 0; i < 256; i++) { const t = i / 255; let k = 1; while (k < S.length - 1 && S[k][0] < t) k++; const a = S[k - 1], b = S[k]; const f = clamp((t - a[0]) / (b[0] - a[0] || 1), 0, 1); for (let j = 0; j < 3; j++) L[i * 3 + j] = a[1][j] + (b[1][j] - a[1][j]) * f; }
+  return L;
+}
+const LUT = {
+  inferno: lut([[0, '#000004'], [0.15, '#1f0c48'], [0.3, '#550f6d'], [0.45, '#88226a'], [0.6, '#ba3655'], [0.72, '#e35933'], [0.84, '#f98e09'], [0.94, '#f6d746'], [1, '#fcffa4']]),
+  mmi: lut([[0, '#bfccff'], [0.14, '#a0e6ff'], [0.28, '#80ffff'], [0.42, '#7aff93'], [0.56, '#ffff00'], [0.7, '#ffc800'], [0.84, '#ff6a00'], [1, '#c80000']]),
+};
+PT.LUT = LUT;
+// IR enhancement (BD-style): warm = dark grey; cold cloud tops step through cyan, blue, green, yellow, red, black, white
+function irColor(T, out) {
+  if (T > -30) { const g = clamp(lerp(28, 196, (30 - T) / 60), 0, 255); out[0] = g; out[1] = g; out[2] = g + 4; return; }
+  const st = [[-30, [150, 222, 245]], [-38, [52, 150, 225]], [-44, [28, 70, 200]], [-50, [40, 190, 70]], [-56, [235, 232, 70]], [-61, [246, 150, 40]], [-66, [226, 46, 30]], [-71, [120, 14, 18]], [-75, [12, 12, 14]], [-79, [96, 96, 100]], [-83, [236, 236, 240]], [-95, [255, 255, 255]]];
+  for (let i = 1; i < st.length; i++) if (T >= st[i][0]) { const a = st[i - 1], b = st[i]; const f = (a[0] - T) / (a[0] - b[0]); for (let j = 0; j < 3; j++) out[j] = a[1][j] + (b[1][j] - a[1][j]) * f; return; }
+  out[0] = out[1] = out[2] = 255;
+}
+const DBZ = [[18, '#03b33a'], [25, '#02d802'], [30, '#019a00'], [35, '#f4ec00'], [40, '#e4b800'], [45, '#fd8e00'], [50, '#fb0d00'], [55, '#cf0000'], [60, '#a80000'], [65, '#f400f6'], [70, '#9a52cc'], [75, '#ffffff']].map(([d, c]) => [d, hexrgb(c)]);
+function dbzColor(z, out) { if (z < 18) { out[3] = 0; return; } let k = 0; while (k < DBZ.length - 1 && DBZ[k + 1][0] <= z) k++; const c = DBZ[k][1]; out[0] = c[0]; out[1] = c[1]; out[2] = c[2]; out[3] = 225; }
+
+/* ---------- raster helpers ---------- */
+// fn(u, v, out, x, y) fills out[0..3] for each cell of a w/k × h/k field; drawn scaled onto ctx
+function field(ctx, w, h, k, fn, smoothOn = true, comp) {
+  const fw = Math.max(1, Math.round(w / k)), fh = Math.max(1, Math.round(h / k));
+  const c = mk(fw, fh), cx = c.getContext('2d'); const id = cx.createImageData(fw, fh); const d = id.data; const out = [0, 0, 0, 255];
+  for (let y = 0; y < fh; y++) for (let x = 0; x < fw; x++) { out[3] = 255; fn(x / fw, y / fh, out, x, y, fw, fh); const o = (y * fw + x) * 4; d[o] = out[0]; d[o + 1] = out[1]; d[o + 2] = out[2]; d[o + 3] = out[3]; }
+  cx.putImageData(id, 0, 0);
+  ctx.save(); if (comp) ctx.globalCompositeOperation = comp; ctx.imageSmoothingEnabled = smoothOn; ctx.imageSmoothingQuality = 'high'; ctx.drawImage(c, 0, 0, w, h); ctx.restore();
+}
+PT.field = field;
+let GRAIN = null;
+function grain(ctx, w, h, a = 0.07) {
+  if (!GRAIN) { GRAIN = mk(192, 192); const g = GRAIN.getContext('2d'); const id = g.createImageData(192, 192); const r = rng(99); for (let i = 0; i < id.data.length; i += 4) { const v = r() * 255; id.data[i] = id.data[i + 1] = id.data[i + 2] = v; id.data[i + 3] = 255; } g.putImageData(id, 0, 0); }
+  ctx.save(); ctx.globalAlpha = a; ctx.globalCompositeOperation = 'overlay'; ctx.fillStyle = ctx.createPattern(GRAIN, 'repeat'); const ox = (Math.random() * 192) | 0, oy = (Math.random() * 192) | 0; ctx.translate(-ox, -oy); ctx.fillRect(0, 0, w + 192, h + 192); ctx.restore();
+}
+function vignette(ctx, w, h, a = 0.55, inner = 0.35) { const g = ctx.createRadialGradient(w / 2, h / 2, Math.min(w, h) * inner, w / 2, h / 2, Math.hypot(w, h) * 0.6); g.addColorStop(0, 'rgba(0,0,0,0)'); g.addColorStop(1, `rgba(0,0,0,${a})`); ctx.fillStyle = g; ctx.fillRect(0, 0, w, h); }
+function scan(ctx, w, h, a = 0.08, step = 3) { ctx.save(); ctx.fillStyle = `rgba(0,0,0,${a})`; for (let y = 0; y < h; y += step) ctx.fillRect(0, y, w, 1); ctx.restore(); }
+function glow(ctx, x, y, r, col, a = 1) { const g = ctx.createRadialGradient(x, y, 0, x, y, r); g.addColorStop(0, col.replace('A', a)); g.addColorStop(0.35, col.replace('A', a * 0.35)); g.addColorStop(1, col.replace('A', 0)); ctx.fillStyle = g; ctx.fillRect(x - r, y - r, r * 2, r * 2); }
+// OSD text, camera style
+function osd(ctx, txt, x, y, px, align = 'left', col = 'rgba(255,255,255,.92)', base = 'top') {
+  ctx.save(); ctx.font = `600 ${px}px ${MONO}`; ctx.textAlign = align; ctx.textBaseline = base; ctx.lineJoin = 'round';
+  ctx.lineWidth = Math.max(2, px / 3.4); ctx.strokeStyle = 'rgba(0,0,0,.72)'; ctx.strokeText(txt, x, y); ctx.fillStyle = col; ctx.fillText(txt, x, y); ctx.restore();
+}
+function label(ctx, txt, x, y, px, col = 'rgba(235,240,248,.75)', align = 'left') { ctx.save(); ctx.font = `600 ${px}px ${MONO}`; ctx.textAlign = align; ctx.textBaseline = 'middle'; ctx.fillStyle = col; ctx.shadowColor = 'rgba(0,0,0,.9)'; ctx.shadowBlur = 4; ctx.fillText(txt, x, y); ctx.restore(); }
+Object.assign(PT, { grain, vignette, scan, glow, osd, label, lut, irColor });
+const z2 = (n) => String(n).padStart(2, '0');
+PT.stamp = (ms, sep = ' ') => { const d = new Date(ms); return `${d.getUTCFullYear()}-${z2(d.getUTCMonth() + 1)}-${z2(d.getUTCDate())}${sep}${z2(d.getUTCHours())}:${z2(d.getUTCMinutes())}:${z2(d.getUTCSeconds())}`; };
+
+/* ---------- maps (equirectangular, square km pixels) ---------- */
+function mapView(lat0, lon0, spanLon, w, h) {
+  const spanLat = spanLon * Math.cos(lat0 * D2R) * (h / w);
+  return { lat0, lon0, spanLon, spanLat, w, h, X: (lon) => ((((lon - lon0) + 540) % 360) - 180) / spanLon * w + w / 2, Y: (lat) => h / 2 - ((lat - lat0) / spanLat) * h, lon: (x) => lon0 + ((x - w / 2) / w) * spanLon, lat: (y) => lat0 + ((h / 2 - y) / h) * spanLat, kmPx: (spanLon * 111.32 * Math.cos(lat0 * D2R)) / w };
+}
+PT.mapView = mapView;
+const cropCache = new Map();
+function cropData(name, mv, w, h) {
+  const key = [name, mv.lat0.toFixed(3), mv.lon0.toFixed(3), mv.spanLon.toFixed(3), w, h].join('|');
+  if (cropCache.has(key)) return cropCache.get(key);
+  const img = GE.world.img && GE.world.img[name]; const c = mk(w, h), cx = c.getContext('2d', { willReadFrequently: true });
+  if (img) { cx.imageSmoothingQuality = 'high'; const iw = img.width, ih = img.height; const sx = ((mv.lon0 - mv.spanLon / 2 + 180) / 360) * iw, sy = ((90 - (mv.lat0 + mv.spanLat / 2)) / 180) * ih; cx.drawImage(img, sx, sy, (mv.spanLon / 360) * iw, (mv.spanLat / 180) * ih, 0, 0, w, h); }
+  const d = cx.getImageData(0, 0, w, h).data; if (cropCache.size > 40) cropCache.clear(); cropCache.set(key, d); return d;
+}
+PT.cropData = cropData;
+// dark instrument map: land/sea from the water mask, optional relief (topo) and night lights
+function mapBase(ctx, mv, o = {}) {
+  const { w, h } = mv; const k = o.k || 1; const fw = Math.round(w / k), fh = Math.round(h / k);
+  const wm = cropData('water', mv, fw, fh); const tp = o.relief ? cropData('topo', mv, fw, fh) : null; const nl = o.lights ? cropData('night', mv, fw, fh) : null;
+  const land = hexrgb(o.land || '#121922'), sea = hexrgb(o.sea || '#05080c'), coast = hexrgb(o.coast || '#46566c');
+  field(ctx, w, h, k, (u, v, out, x, y) => {
+    const i = (y * fw + x) * 4; const m = wm[i] / 255; const l = smooth(0.62, 0.38, m);
+    let r = lerp(sea[0], land[0], l), g = lerp(sea[1], land[1], l), b = lerp(sea[2], land[2], l);
+    if (tp && l > 0.3) { const e0 = tp[i], ex = tp[Math.min(i + 4, tp.length - 4)] - tp[Math.max(i - 4, 0)], ey = tp[Math.min(i + fw * 4, tp.length - 4)] - tp[Math.max(i - fw * 4, 0)]; const s = clamp(1 + (ey - ex) * 0.035 * (o.relief || 1) + e0 / 255 * 0.5, 0.55, 1.9); r *= s; g *= s; b *= s; }
+    if (nl) { const L = Math.max(0, nl[i + 1] - 10) / 245 * o.lights; r += L * 255; g += L * 190; b += L * 110; }
+    const e = smooth(0.6, 0.95, 1 - Math.abs(m - 0.5) * 2) * (o.coastA ?? 1); r = lerp(r, coast[0], e); g = lerp(g, coast[1], e); b = lerp(b, coast[2], e);
+    out[0] = r; out[1] = g; out[2] = b;
+  });
+}
+PT.mapBase = mapBase;
+function graticule(ctx, mv, step, col = 'rgba(160,190,230,.10)') {
+  ctx.save(); ctx.strokeStyle = col; ctx.lineWidth = 1; ctx.setLineDash([2, 4]);
+  for (let lo = Math.ceil((mv.lon0 - mv.spanLon / 2) / step) * step; lo < mv.lon0 + mv.spanLon / 2; lo += step) { const x = mv.X(lo); ctx.beginPath(); ctx.moveTo(x, 0); ctx.lineTo(x, mv.h); ctx.stroke(); }
+  for (let la = Math.ceil((mv.lat0 - mv.spanLat / 2) / step) * step; la < mv.lat0 + mv.spanLat / 2; la += step) { const y = mv.Y(la); ctx.beginPath(); ctx.moveTo(0, y); ctx.lineTo(mv.w, y); ctx.stroke(); }
+  ctx.restore();
+}
+function scaleBar(ctx, mv, km, x, y, col = 'rgba(235,240,248,.8)') { const px = km / mv.kmPx; ctx.save(); ctx.strokeStyle = col; ctx.lineWidth = 1.5; ctx.beginPath(); ctx.moveTo(x, y - 4); ctx.lineTo(x, y); ctx.lineTo(x + px, y); ctx.lineTo(x + px, y - 4); ctx.stroke(); ctx.restore(); label(ctx, km + ' KM', x + px + 5, y - 2, Math.max(8, mv.w / 42), col); }
+function plane(ctx, x, y, hdg, s, col) { ctx.save(); ctx.translate(x, y); ctx.rotate(hdg); ctx.scale(s / 24, s / 24); ctx.translate(-12, -12); ctx.fillStyle = col; ctx.fill(new Path2D('M12 2.8c.9 0 1.4.9 1.4 2v4.6l7.1 4.2v1.9l-7.1-2.1v4.4l2.2 1.7v1.6L12 20.2l-3.6.9v-1.6l2.2-1.7v-4.4l-7.1 2.1v-1.9l7.1-4.2V4.8c0-1.1.5-2 1.4-2Z')); ctx.restore(); }
+function cross(ctx, x, y, r, col, lw = 1.4) { ctx.save(); ctx.strokeStyle = col; ctx.lineWidth = lw; ctx.beginPath(); ctx.moveTo(x - r, y); ctx.lineTo(x + r, y); ctx.moveTo(x, y - r); ctx.lineTo(x, y + r); ctx.stroke(); ctx.restore(); }
+function poly(ctx, pts, close) { ctx.beginPath(); pts.forEach((p, i) => (i ? ctx.lineTo(p[0], p[1]) : ctx.moveTo(p[0], p[1]))); if (close) ctx.closePath(); }
+Object.assign(PT, { graticule, scaleBar, plane, cross, poly });
+
+/* =====================================================================================
+   ORBIT
+   ===================================================================================== */
+// IR cloud tops of a tropical cyclone with eyewall lightning and the advisory track
+PT.ir = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 3);
+  const C = GE.CYCLONE.at(0); const mv = mapView(C.lat + (o.dy ?? 0.6), C.lon + (o.dx ?? -0.8), o.span || 13, w, h);
+  const k = 2, fw = Math.round(w / k), fh = Math.round(h / k); const wm = cropData('water', mv, fw, fh); const col = [0, 0, 0];
+  const cl = Math.cos(C.lat * D2R);
+  field(ctx, w, h, k, (u, v, out, x, y) => {
+    const lat = mv.lat(v * h), lon = mv.lon(u * w); const dx = (lon - C.lon) * cl / 1.7, dy = (lat - C.lat) / 1.7; const r = Math.hypot(dx, dy), th = Math.atan2(dy, dx);
+    const wn = N.fbm(dx * 0.8 + 11, dy * 0.8 + 3, 4);
+    const arms = 0.5 + 0.5 * Math.sin(3 * (th - 2.1 * Math.log(r + 0.15)) + wn * 5.5);
+    const conv = N.fbm(dx * 1.9 + 4, dy * 1.9 - 2, 5);
+    const cdo = smooth(2.3, 0.9, r + (wn - 0.5) * 0.9), eye = smooth(0.16, 0.34, r), wall = Math.exp(-(((r - 0.4) / 0.15) ** 2));
+    let c = Math.max(cdo * (0.8 + 0.22 * conv), arms * smooth(7.5, 1.8, r) * (0.3 + 0.7 * conv) * smooth(0.28, 0.62, conv));
+    c = Math.max(c, wall * 0.97) * eye;
+    const bg = smooth(0.64, 0.86, N.fbm(dx * 0.55 + 40, dy * 0.55 + 9, 5)) * 0.62; c = Math.max(c, bg * (1 - cdo) * smooth(1.5, 4, r));
+    c += wall * smooth(0.6, 0.95, N(dx * 8, dy * 8)) * 0.12 + cdo * smooth(0.72, 0.98, N(dx * 5 + 3, dy * 5)) * 0.08;
+    const i = (y * fw + x) * 4; const land = 1 - wm[i] / 255;
+    irColor(26 - c * 114 + (c < 0.2 ? land * -10 : 0), col);
+    const edge = smooth(0.62, 0.95, 1 - Math.abs(wm[i] / 255 - 0.5) * 2) * (c < 0.55 ? 0.9 : 0.35);
+    out[0] = lerp(col[0], 236, edge); out[1] = lerp(col[1], 214, edge); out[2] = lerp(col[2], 96, edge);
+  });
+  graticule(ctx, mv, 5, 'rgba(255,255,255,.16)');
+  // advisory track: past (solid dots), forecast (dashed + cone)
+  const tr = GE.CYCLONE.track; ctx.save(); ctx.lineWidth = Math.max(1.2, w / 260);
+  const P = (q) => [mv.X(q[2]), mv.Y(q[1])];
+  ctx.strokeStyle = 'rgba(255,255,255,.85)'; poly(ctx, tr.filter((q) => q[0] <= 0).map(P)); ctx.stroke();
+  ctx.setLineDash([4, 4]); poly(ctx, tr.filter((q) => q[0] >= 0).map(P)); ctx.stroke(); ctx.setLineDash([]);
+  const fut = tr.filter((q) => q[0] >= 0); const L = [], Rr = [];
+  for (let i = 0; i < fut.length; i++) { const q = fut[i], n = fut[Math.min(i + 1, fut.length - 1)], p0 = fut[Math.max(i - 1, 0)]; const b = geo.bearing(p0[1], p0[2], n[1], n[2]); const km = GE.CYCLONE.cone(q[0]); const a = geo.dest(q[1], q[2], b - Math.PI / 2, km), c2 = geo.dest(q[1], q[2], b + Math.PI / 2, km); L.push([mv.X(a[1]), mv.Y(a[0])]); Rr.push([mv.X(c2[1]), mv.Y(c2[0])]); }
+  ctx.strokeStyle = 'rgba(255,255,255,.5)'; ctx.lineWidth = 1; poly(ctx, [...L, ...Rr.reverse()], true); ctx.stroke();
+  for (const q of tr) { const [x, y] = P(q); ctx.beginPath(); ctx.arc(x, y, q[0] === 0 ? w / 70 : w / 150, 0, TAU); ctx.fillStyle = q[0] < 0 ? '#fff' : q[0] === 0 ? 'rgba(0,0,0,0)' : 'rgba(255,255,255,.4)'; ctx.fill(); if (q[0] === 0) { ctx.strokeStyle = '#fff'; ctx.lineWidth = 1.5; ctx.stroke(); } }
+  ctx.restore();
+  // lightning in the eyewall and bands
+  const R = rng(o.seed || 5); const cx0 = mv.X(C.lon), cy0 = mv.Y(C.lat); const pxDeg = w / mv.spanLon;
+  ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let i = 0; i < (o.flashes ?? 34); i++) { const rr = (i < 12 ? 0.35 + R() * 0.25 : 0.7 + R() * 3.2) * 1.7, a = R() * TAU; const x = cx0 + Math.cos(a) * rr * pxDeg, y = cy0 - Math.sin(a) * rr * pxDeg; glow(ctx, x, y, w / (i < 4 ? 9 : 26), 'rgba(200,230,255,A)', i < 4 ? 0.55 : 0.4); cross(ctx, x, y, w / 90, 'rgba(255,255,255,.95)', 1.2); }
+  ctx.restore();
+  label(ctx, 'IR 10.4 µm', w * 0.05, h * PT.topY, Math.max(9, w / 34), 'rgba(255,255,255,.85)');
+  // enhancement legend
+  const lx = w * 0.6, ly = h * PT.botY, lw = w * 0.34, lh = Math.max(4, h / 90);
+  for (let i = 0; i < 60; i++) { irColor(10 - (i / 59) * 100, col); ctx.fillStyle = `rgb(${col[0]},${col[1]},${col[2]})`; ctx.fillRect(lx + (i / 60) * lw, ly, lw / 60 + 0.5, lh); }
+  label(ctx, '+10', lx, ly - lh, Math.max(7, w / 48), 'rgba(255,255,255,.7)'); label(ctx, '−90 °C', lx + lw, ly - lh, Math.max(7, w / 48), 'rgba(255,255,255,.7)', 'right');
+};
+
+// ISS external camera: the night side raycast from 418 km, airglow on the limb, truss in frame
+PT.isscam = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const lat0 = o.lat ?? 25.5, lon0 = o.lon ?? 31.0; const altKm = 418;
+  const reg = mapView(lat0 + 14, lon0 + 2, 46, 900, 900 * 0.75);
+  const RW = 900, RH = Math.round(900 * 0.75); const night = cropData('night', reg, RW, RH), clouds = cropData('clouds', reg, RW, RH), day = cropData('day', reg, RW, RH);
+  const en = geo.enu(lat0, lon0); const eye = geo.vec(lat0, lon0, altKm); const hd = (o.hdg ?? 8) * D2R, pitch = (o.pitch ?? 24) * D2R;
+  const fwdH = v3.add(v3.scale(en.north, Math.cos(hd)), v3.scale(en.east, Math.sin(hd)));
+  const fwd = v3.norm(v3.add(v3.scale(fwdH, Math.cos(pitch)), v3.scale(en.up, -Math.sin(pitch))));
+  const right = v3.norm(v3.cross(fwd, en.up)), up = v3.cross(right, fwd); const tanF = Math.tan((o.fov ?? 64) * D2R / 2), asp = w / h;
+  const N = noiseGen(31); const R2 = rng(4);
+  const samp = (D, lat, lon) => { const x = clamp(Math.round(((lon - (reg.lon0 - reg.spanLon / 2)) / reg.spanLon) * RW), 0, RW - 1), y = clamp(Math.round((((reg.lat0 + reg.spanLat / 2) - lat) / reg.spanLat) * RH), 0, RH - 1); return (y * RW + x) * 4; };
+  field(ctx, w, h, 2, (u, v, out) => {
+    const sx = (u * 2 - 1) * tanF * asp, sy = (1 - v * 2) * tanF; const d = v3.norm(v3.add(fwd, v3.add(v3.scale(right, sx), v3.scale(up, sy))));
+    const b = v3.dot(eye, d), c = v3.dot(eye, eye) - 1, disc = b * b - c;
+    if (disc > 0 && -b - Math.sqrt(disc) > 0) {
+      const t = -b - Math.sqrt(disc); const p = v3.madd(eye, d, t); const [la, lo] = geo.ll(p); const i = samp(null, la, lo);
+      const graz = clamp(-v3.dot(d, v3.norm(p)), 0, 1); const haze = Math.pow(1 - graz, 3);
+      const L = Math.pow(night[i + 1] / 255, 1.25) * 1.5; const cl = clouds[i] / 255;
+      out[0] = clamp(L * 255 * 1.05 + day[i] * 0.03 + cl * 14 + haze * 24, 0, 255); out[1] = clamp(L * 190 + day[i + 1] * 0.035 + cl * 18 + haze * 34, 0, 255); out[2] = clamp(L * 95 + day[i + 2] * 0.05 + cl * 26 + haze * 56, 0, 255);
+      const lit = (1 - cl * 0.6); out[0] *= lit; out[1] *= lit; out[2] *= lit; out[0] += cl * 10; out[1] += cl * 12; out[2] += cl * 20;
+    } else {
+      const tc = Math.max(0, -b); const cp = v3.madd(eye, d, tc); const a = (v3.len(cp) - 1) * EARTH_KM;
+      const glowG = Math.exp(-(((a - 92) / 9) ** 2)) * 0.95, glowR = Math.exp(-(((a - 110) / 14) ** 2)) * 0.35, sc = Math.exp(-Math.max(0, a) / 18) * 0.55;
+      out[0] = clamp(glowR * 150 + sc * 40, 0, 255); out[1] = clamp(glowG * 150 + sc * 70, 0, 255); out[2] = clamp(glowG * 70 + sc * 120 + 6, 0, 255);
+      if (a > 140 && R2() < 0.006) { const s = 120 + R2() * 135; out[0] = s; out[1] = s; out[2] = s + 10; }
+    }
+  });
+  // a lightning flash under cloud near the horizon
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, w * 0.28, h * 0.36, w * 0.12, 'rgba(170,200,255,A)', 0.7); glow(ctx, w * 0.31, h * 0.37, w * 0.05, 'rgba(240,248,255,A)', 0.8); ctx.restore();
+  // truss & solar array in the corner, rim-lit
+  ctx.save(); ctx.translate(w * 0.98, h * 0.02); ctx.rotate(0.42); ctx.fillStyle = '#07080b';
+  ctx.fillRect(-w * 0.62, -h * 0.07, w * 0.9, h * 0.1); ctx.strokeStyle = 'rgba(214,170,90,.55)'; ctx.lineWidth = 1;
+  for (let i = 0; i < 16; i++) { ctx.beginPath(); ctx.moveTo(-w * 0.62 + i * w * 0.056, -h * 0.07); ctx.lineTo(-w * 0.62 + i * w * 0.056, h * 0.03); ctx.stroke(); }
+  ctx.strokeStyle = 'rgba(255,214,140,.7)'; ctx.beginPath(); ctx.moveTo(-w * 0.62, h * 0.03); ctx.lineTo(w * 0.3, h * 0.03); ctx.stroke(); ctx.restore();
+  vignette(ctx, w, h, 0.45, 0.4); grain(ctx, w, h, 0.09);
+  osd(ctx, `ISS EXT CAM 2 · ${altKm} KM`, w * 0.05, h * PT.topY, Math.max(9, w / 36));
+};
+
+// your sky: the station's pass drawn as an arc on an alt-az chart
+PT.skychart = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const cx = w / 2, cy = h * 0.47, R = Math.min(w, h) * 0.4;
+  const g = ctx.createRadialGradient(cx, cy, 0, cx, cy, Math.max(w, h)); g.addColorStop(0, '#0d1430'); g.addColorStop(0.55, '#070a18'); g.addColorStop(1, '#020308'); ctx.fillStyle = g; ctx.fillRect(0, 0, w, h);
+  const r = rng(o.seed || 12); ctx.save();
+  for (let i = 0; i < 420; i++) { const a = r() * TAU, d = Math.sqrt(r()) * R * 1.35; const x = cx + Math.cos(a) * d, y = cy + Math.sin(a) * d; const m = Math.pow(r(), 6); ctx.fillStyle = `rgba(${220 + m * 35},${225 + m * 30},255,${0.25 + m * 0.75})`; ctx.fillRect(x, y, 1 + m * 2, 1 + m * 2); }
+  // a dipper-shaped asterism
+  const ast = [[-0.62, 0.3], [-0.48, 0.25], [-0.34, 0.29], [-0.22, 0.37], [-0.18, 0.51], [-0.02, 0.53], [0.02, 0.39]].map(([a, b]) => [cx + a * R, cy + b * R]);
+  ctx.strokeStyle = 'rgba(160,190,255,.22)'; ctx.lineWidth = 1; poly(ctx, ast); ctx.stroke(); for (const [x, y] of ast) { ctx.fillStyle = '#fff'; ctx.beginPath(); ctx.arc(x, y, w / 200 + 0.8, 0, TAU); ctx.fill(); }
+  ctx.strokeStyle = 'rgba(183,156,255,.28)'; ctx.setLineDash([2, 4]);
+  for (const k of [1, 2 / 3, 1 / 3]) { ctx.beginPath(); ctx.arc(cx, cy, R * k, 0, TAU); ctx.stroke(); }
+  ctx.setLineDash([]); ctx.strokeStyle = 'rgba(183,156,255,.6)'; ctx.lineWidth = 1.4; ctx.beginPath(); ctx.arc(cx, cy, R, 0, TAU); ctx.stroke();
+  const fs = Math.max(9, w / 30); for (const [t, a] of [['N', -90], ['E', 0], ['S', 90], ['W', 180]]) label(ctx, t, cx + Math.cos(a * D2R) * (R + fs * 0.9), cy + Math.sin(a * D2R) * (R + fs * 0.9), fs, t === 'N' ? '#FF6A3D' : 'rgba(220,210,255,.8)', 'center');
+  label(ctx, '30°', cx + 3, cy - R * 2 / 3 + 7, fs * 0.72, 'rgba(183,156,255,.6)'); label(ctx, '60°', cx + 3, cy - R / 3 + 7, fs * 0.72, 'rgba(183,156,255,.6)');
+  // the pass: rises WSW, culminates ~54°, sets ENE
+  const az0 = 245 * D2R, az1 = 62 * D2R, maxEl = (o.max ?? 54) * D2R; const pts = [];
+  for (let i = 0; i <= 60; i++) { const f = i / 60; let az = az0 + (((az1 - az0 + TAU * 1.5) % TAU) - Math.PI) * 0 + f * (((az1 - az0 + 3 * Math.PI) % TAU) - Math.PI); const el = Math.sin(f * Math.PI) * maxEl; const rr = R * (1 - el / (Math.PI / 2)); pts.push([cx + Math.sin(az) * rr, cy - Math.cos(az) * rr, f]); }
+  ctx.lineWidth = Math.max(2, w / 120); const gr = ctx.createLinearGradient(pts[0][0], pts[0][1], pts[60][0], pts[60][1]); gr.addColorStop(0, 'rgba(201,167,255,.25)'); gr.addColorStop(0.5, 'rgba(230,214,255,1)'); gr.addColorStop(1, 'rgba(201,167,255,.25)'); ctx.strokeStyle = gr; poly(ctx, pts); ctx.stroke();
+  const p0 = o.at ?? Date.now() + 3.2 * 3600000;
+  for (const k of [0, 20, 30, 40, 60]) { const [x, y] = pts[k]; ctx.fillStyle = '#E6D6FF'; ctx.beginPath(); ctx.arc(x, y, k === 30 ? w / 60 : w / 120, 0, TAU); ctx.fill(); if (k % 20 === 0 || k === 30) label(ctx, fmt.hm(p0 + (k / 60) * 6.5 * 60000), x + 7, y - 9, fs * 0.8, 'rgba(240,232,255,.9)'); }
+  ctx.globalCompositeOperation = 'lighter'; glow(ctx, pts[30][0], pts[30][1], w / 10, 'rgba(200,170,255,A)', 0.55); ctx.restore();
+  // moon
+  ctx.save(); ctx.translate(cx + R * 0.62, cy + R * 0.45); ctx.fillStyle = '#E8E4D8'; ctx.beginPath(); ctx.arc(0, 0, w / 40, 0, TAU); ctx.fill(); ctx.fillStyle = '#070a18'; ctx.beginPath(); ctx.arc(w / 110, -w / 160, w / 42, 0, TAU); ctx.fill(); ctx.restore();
+  label(ctx, `MAX ${Math.round(maxEl * R2D)}°`, pts[30][0], pts[30][1] + fs * 1.6, fs * 0.85, '#E6D6FF', 'center');
+};
+
+// long-range tracking camera: launch arc + sunlit "jellyfish" plume in twilight
+PT.plume = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const r = rng(o.seed || 21); const N = noiseGen(8);
+  const hz = h * 0.78; const sky = ctx.createLinearGradient(0, 0, 0, hz);
+  sky.addColorStop(0, '#02040c'); sky.addColorStop(0.45, '#0a1638'); sky.addColorStop(0.78, '#1d3a6a'); sky.addColorStop(0.93, '#5a5e7a'); sky.addColorStop(1, '#c47b4a');
+  ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz);
+  for (let i = 0; i < 260; i++) { const y = r() * hz * 0.7; ctx.fillStyle = `rgba(255,255,255,${0.15 + r() * 0.6 * (1 - y / hz)})`; ctx.fillRect(r() * w, y, 1, 1); }
+  // arc: pad at lower left, pitching over to the right
+  const pad = [w * 0.16, hz - 2]; const top = [w * 0.66, h * 0.22]; const ctrl = [w * 0.2, h * 0.18];
+  const B = (t) => [(1 - t) ** 2 * pad[0] + 2 * (1 - t) * t * ctrl[0] + t * t * top[0], (1 - t) ** 2 * pad[1] + 2 * (1 - t) * t * ctrl[1] + t * t * top[1]];
+  // sunlit plume (behind the arc): dome expanding up/right, iridescent rim
+  const pc = B(0.86); ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let i = 0; i < 90; i++) { const t = 0.55 + (i / 90) * 0.45; const p = B(t); const s = (t - 0.55) * w * 0.95; const a = (0.022 + 0.02 * N(i * 0.3, 2)) * (t > 0.7 ? 1 : (t - 0.55) / 0.15);
+    const g = ctx.createRadialGradient(p[0] + s * 0.25, p[1] - s * 0.2, s * 0.05, p[0] + s * 0.25, p[1] - s * 0.2, s * 0.85); g.addColorStop(0, `rgba(210,235,255,${a * 1.2})`); g.addColorStop(0.55, `rgba(120,190,255,${a * 0.7})`); g.addColorStop(0.85, `rgba(255,160,120,${a * 0.35})`); g.addColorStop(1, 'rgba(0,0,0,0)'); ctx.fillStyle = g; ctx.fillRect(0, 0, w, h); }
+  // jellyfish tendrils
+  ctx.strokeStyle = 'rgba(190,225,255,.22)'; ctx.lineWidth = 1;
+  for (let i = 0; i < 26; i++) { const a = -0.3 + (i / 25) * 2.2; ctx.beginPath(); ctx.moveTo(pc[0], pc[1]); for (let k = 1; k <= 12; k++) { const d = k * w * 0.028; ctx.lineTo(pc[0] + Math.cos(a) * d + N(i, k * 0.4) * 10, pc[1] + Math.sin(a) * d * 0.6 + k * k * 0.5); } ctx.stroke(); }
+  ctx.restore();
+  // the long-exposure streak
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; ctx.lineCap = 'round';
+  for (const [lw, col] of [[w / 22, 'rgba(255,120,40,.10)'], [w / 50, 'rgba(255,150,60,.35)'], [w / 120, 'rgba(255,220,170,.95)'], [w / 300, 'rgba(255,255,255,1)']]) {
+    ctx.lineWidth = lw; ctx.strokeStyle = col; ctx.beginPath(); for (let i = 0; i <= 80; i++) { const t = i / 80; const p = B(t * 0.88); i ? ctx.lineTo(p[0], p[1]) : ctx.moveTo(p[0], p[1]); } ctx.stroke(); }
+  glow(ctx, pad[0], pad[1], w * 0.2, 'rgba(255,150,70,A)', 0.55); ctx.restore();
+  // coast: land silhouette with lights, water reflecting the streak
+  ctx.fillStyle = '#040508'; ctx.beginPath(); ctx.moveTo(0, hz); for (let x = 0; x <= w; x += 6) ctx.lineTo(x, hz - 3 - N.fbm(x / 60, 1, 3) * 12 * (x < w * 0.5 ? 1 : 0.4)); ctx.lineTo(w, hz + 8); ctx.lineTo(0, hz + 8); ctx.fill();
+  for (let i = 0; i < 70; i++) { const x = r() * w; ctx.fillStyle = `rgba(255,${190 + r() * 50},${120 + r() * 60},${0.5 + r() * 0.5})`; ctx.fillRect(x, hz - 2 - r() * 6, 1.4, 1.4); }
+  const wg = ctx.createLinearGradient(0, hz, 0, h); wg.addColorStop(0, '#0d1424'); wg.addColorStop(1, '#030407'); ctx.fillStyle = wg; ctx.fillRect(0, hz + 6, w, h - hz);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; for (let y = hz + 8; y < h; y += 2) { const f = (y - hz) / (h - hz); const jit = (N(y * 0.2, 3) - 0.5) * 18 * f; ctx.fillStyle = `rgba(255,140,60,${0.35 * (1 - f)})`; ctx.fillRect(pad[0] - 4 - f * 10 + jit, y, 8 + f * 22, 1.4); ctx.fillStyle = `rgba(150,190,255,${0.08 * (1 - f)})`; ctx.fillRect(w * 0.5 + jit * 2, y, w * 0.3, 1); } ctx.restore();
+  vignette(ctx, w, h, 0.4); grain(ctx, w, h, 0.1);
+  osd(ctx, 'TRK CAM 3 · 400 MM · LONG EXPOSURE', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.8)');
+};
+
+// active fire seen from orbit: hillshaded terrain, burn scar, front, hotspot pixels, smoke plume
+PT.firesat = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 17); const s = 2.1 / w;
+  const scarC = [w * 0.62, h * 0.6], scarR = w * 0.26; const front = [];
+  const H = (x, y) => N.ridge(x * s, y * s, 5) * 0.9 + N.fbm(x * s * 0.4 + 5, y * s * 0.4, 3) * 0.6;
+  const scarAt = (x, y) => { const dx = x - scarC[0], dy = (y - scarC[1]) * 1.35; const a = Math.atan2(dy, dx); const rr = scarR * (0.75 + 0.45 * N(Math.cos(a) * 1.4 + 3, Math.sin(a) * 1.4 + 7)); return Math.hypot(dx, dy) / rr; };
+  field(ctx, w, h, 2, (u, v, out) => {
+    const x = u * w, y = v * h; const e = 2.2; const hc = H(x, y), hx = H(x + e, y), hy = H(x, y + e); const shade = clamp(0.82 + (hc - hx) * 15 - (hc - hy) * 11, 0.45, 1.35);
+    const veg = smooth(0.42, 0.7, N.fbm(x * s * 1.8 + 30, y * s * 1.8, 4));
+    let r = lerp(150, 62, veg), g = lerp(132, 82, veg), b = lerp(88, 48, veg);
+    const fld = N(x * s * 6 + 70, y * s * 6) > 0.72 && hc < 0.55 ? 1 : 0; if (fld) { r = 168; g = 150; b = 98; }
+    r *= shade; g *= shade; b *= shade;
+    const sc = scarAt(x, y); const burnt = smooth(1.02, 0.94, sc); const rim = Math.exp(-(((sc - 1) / 0.05) ** 2));
+    r = lerp(r, 34 + hc * 18, burnt); g = lerp(g, 30 + hc * 14, burnt); b = lerp(b, 28 + hc * 12, burnt);
+    r = lerp(r, 92, rim * 0.6); g = lerp(g, 60, rim * 0.6); b = lerp(b, 40, rim * 0.6);
+    out[0] = r; out[1] = g; out[2] = b;
+  });
+  // river & roads & a village
+  ctx.save(); ctx.strokeStyle = 'rgba(40,70,90,.9)'; ctx.lineWidth = w / 120; ctx.beginPath(); for (let i = 0; i <= 40; i++) { const t = i / 40; const x = t * w, y = h * 0.18 + Math.sin(t * 5) * h * 0.05 + N(t * 4, 9) * h * 0.08; i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke();
+  ctx.strokeStyle = 'rgba(225,215,190,.45)'; ctx.lineWidth = w / 260; for (const k of [0, 1, 2]) { ctx.beginPath(); for (let i = 0; i <= 30; i++) { const t = i / 30; const x = t * w, y = h * (0.35 + k * 0.28) + Math.sin(t * 3 + k) * h * 0.06 + N(t * 3, k * 5) * 20; i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke(); }
+  const vr = rng(3); for (let i = 0; i < 55; i++) { ctx.fillStyle = `rgba(${200 + vr() * 40},${190 + vr() * 30},${170 + vr() * 30},.8)`; ctx.fillRect(w * 0.2 + vr.gauss() * w * 0.04, h * 0.42 + vr.gauss() * h * 0.03, 2, 2); }
+  ctx.restore();
+  // fire front on the downwind (west) edge + hotspot pixels
+  const R = rng(9); ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let i = 0; i < 160; i++) { const a = Math.PI * (0.55 + R() * 0.95); let lo = 0.5, hi = 1.6; for (let k = 0; k < 14; k++) { const m = (lo + hi) / 2; const x = scarC[0] + Math.cos(a) * scarR * m, y = scarC[1] + (Math.sin(a) * scarR * m) / 1.35; if (scarAt(x, y) < 1) lo = m; else hi = m; } const x = scarC[0] + Math.cos(a) * scarR * lo, y = scarC[1] + (Math.sin(a) * scarR * lo) / 1.35; front.push([x, y]); glow(ctx, x, y, w / 36, 'rgba(255,90,20,A)', 0.4); }
+  for (const [x, y] of front) { const q = R(); const ps = Math.max(2, w / 110); ctx.fillStyle = q > 0.8 ? 'rgba(255,240,150,.95)' : q > 0.4 ? 'rgba(255,140,30,.9)' : 'rgba(230,40,20,.85)'; ctx.fillRect(Math.round(x / ps) * ps, Math.round(y / ps) * ps, ps, ps); }
+  ctx.restore();
+  // smoke: drifts WNW from the front
+  const src = [scarC[0] - scarR * 0.85, scarC[1] - scarR * 0.1], dir = v3.norm([-1, -0.55, 0]);
+  field(ctx, w, h, 3, (u, v, out) => {
+    const x = u * w - src[0], y = v * h - src[1]; const al = x * dir[0] + y * dir[1], ac = -x * dir[1] + y * dir[0]; if (al < -20) { out[3] = 0; return; }
+    const wd = 16 + Math.max(0, al) * 0.5; const n = N.fbm(al / 46 + 4, ac / 22, 5); const dn = Math.exp(-((ac / wd) ** 2) * (1.4 - n)) * smooth(-20, 30, al) * Math.exp(-Math.max(0, al) / (w * 2.6)) * (0.5 + 0.8 * n);
+    const a = clamp(dn * 1.1, 0, 0.92); out[0] = lerp(215, 160, n); out[1] = lerp(212, 160, n); out[2] = lerp(206, 170, n); out[3] = a * 255;
+  }, true);
+  label(ctx, 'VIIRS-CLASS 375 M · FRP 840 MW', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+  const mv = { kmPx: 18 / w, w }; scaleBar(ctx, mv, 5, w * 0.06, h * PT.botY);
+  // wind arrow
+  ctx.save(); ctx.translate(w * 0.86, h * PT.botY - 6); ctx.rotate(Math.atan2(dir[1], dir[0])); ctx.strokeStyle = 'rgba(255,255,255,.85)'; ctx.lineWidth = 1.5; ctx.beginPath(); ctx.moveTo(-14, 0); ctx.lineTo(14, 0); ctx.lineTo(8, -5); ctx.moveTo(14, 0); ctx.lineTo(8, 5); ctx.stroke(); ctx.restore();
+};
+
+// synthetic-aperture radar pass over an anchorage: speckle, bright hull returns with sidelobes
+PT.sar = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 23); const R = rng(o.seed || 23);
+  const coast = (v) => w * (0.3 + 0.08 * Math.sin(v * 5) + 0.06 * N(v * 4, 2));
+  field(ctx, w, h, 1.5, (u, v, out) => {
+    const x = u * w, cxl = coast(v); const sea = smooth(cxl - 3, cxl + 3, x); const sp = -Math.log(Math.max(1e-4, R())) * 0.55;
+    const fieldsTex = N(u * 26, v * 26) > 0.55 ? 0.22 : 0; const town = Math.exp(-(((u - 0.12) / 0.08) ** 2 + ((v - 0.62) / 0.12) ** 2)) * (N(u * 90, v * 90) > 0.5 ? 0.9 : 0.25);
+    const land = (0.26 + N.fbm(u * 10, v * 10, 5) * 0.36 + fieldsTex + town) * (0.55 + sp * 0.6);
+    const wave = (0.035 + N.fbm(u * 24 + 2, v * 6, 3) * 0.05) * (0.3 + sp * 1.3) + Math.exp(-(((x - cxl) / 7) ** 2)) * 0.25;
+    const g = clamp(lerp(land, wave, sea), 0, 1) * 255; out[0] = g * 0.93; out[1] = g * 0.97; out[2] = g;
+  }, false);
+  // dredged channel + breakwater
+  ctx.save(); ctx.strokeStyle = 'rgba(0,0,0,.75)'; ctx.lineWidth = w / 60; ctx.beginPath(); ctx.moveTo(coast(0.05) + 4, 0); ctx.lineTo(w * 0.42, h * 0.45); ctx.stroke(); ctx.strokeStyle = 'rgba(255,255,255,.8)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(coast(0.5), h * 0.5); ctx.lineTo(w * 0.5, h * 0.47); ctx.stroke(); ctx.restore();
+  // anchorage: hull returns with cross-shaped sidelobes
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; const n = o.ships || 48;
+  for (let i = 0; i < n; i++) { const cl = i % 3; const x = w * ([0.62, 0.78, 0.56][cl] + R.gauss() * 0.08), y = h * ([0.3, 0.55, 0.78][cl] + R.gauss() * 0.07); const L = w / 30 * (0.6 + R() * 0.9); const a = 0.4 + R() * 0.5; ctx.save(); ctx.translate(x, y); ctx.rotate(a); ctx.fillStyle = 'rgba(255,255,255,.95)'; ctx.fillRect(-L / 2, -1.6, L, 3.2); ctx.restore(); ctx.fillStyle = 'rgba(255,255,255,.16)'; ctx.fillRect(x - L * 1.6, y - 0.5, L * 3.2, 1); ctx.fillRect(x - 0.5, y - L * 1.3, 1, L * 2.6); glow(ctx, x, y, L * 0.7, 'rgba(255,255,255,A)', 0.22); }
+  // one moving ship with a wake and Doppler offset
+  ctx.fillStyle = 'rgba(255,255,255,.9)'; ctx.fillRect(w * 0.44, h * 0.18, w / 22, 3); ctx.strokeStyle = 'rgba(255,255,255,.25)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(w * 0.44, h * 0.18 + 1); ctx.lineTo(w * 0.3, h * 0.12); ctx.stroke(); ctx.fillStyle = 'rgba(255,255,255,.35)'; ctx.fillRect(w * 0.47, h * 0.24, w / 22, 2);
+  ctx.restore();
+  label(ctx, 'SAR · C-BAND · VV · 10 M', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+  scaleBar(ctx, { kmPx: 22 / w, w }, 5, w * 0.06, h * PT.botY);
+};
+
+/* =====================================================================================
+   SKY
+   ===================================================================================== */
+// radar reflectivity: a bowing squall line crossing a city's street grid, lightning, warning box
+PT.radar = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(o.seed || 41); const R = rng(o.seed || 41);
+  ctx.fillStyle = '#0a0e14'; ctx.fillRect(0, 0, w, h);
+  const cores = [[w * 0.62, h * 0.5, w * 0.34], [w * 0.22, h * 0.56, w * 0.22]];
+  const urb = (x, y) => Math.max(...cores.map(([cx, cy, r]) => Math.exp(-((x - cx) ** 2 + (y - cy) ** 2) / (r * r))));
+  field(ctx, w, h, 2, (u, v, out) => { const x = u * w, y = v * h; const k = urb(x, y) * (0.6 + 0.5 * N.fbm(u * 9, v * 9, 3)); out[0] = 10 + k * 22; out[1] = 14 + k * 24; out[2] = 20 + k * 30; });
+  // street grid
+  ctx.save(); ctx.lineWidth = 1; const step = Math.max(5, w / 60);
+  for (let x = 0; x < w; x += step) for (let y = 0; y < h; y += step) { const k = urb(x, y); if (R() > k * 1.3) continue; ctx.strokeStyle = `rgba(170,190,220,${0.06 + k * 0.1})`; ctx.beginPath(); ctx.moveTo(x, y); ctx.lineTo(x + step, y); ctx.moveTo(x, y); ctx.lineTo(x, y + step); ctx.stroke(); }
+  // lakes, river, highways
+  ctx.fillStyle = '#0f2236'; for (const [x, y, rx, ry] of [[0.42, 0.22, 0.05, 0.03], [0.86, 0.3, 0.04, 0.06], [0.1, 0.8, 0.05, 0.025]]) { ctx.beginPath(); ctx.ellipse(x * w, y * h, rx * w, ry * h, 0.4, 0, TAU); ctx.fill(); }
+  ctx.strokeStyle = 'rgba(70,120,170,.6)'; ctx.lineWidth = w / 200; ctx.beginPath(); for (let i = 0; i <= 50; i++) { const t = i / 50; const x = t * w, y = h * 0.62 + Math.sin(t * 9) * h * 0.03 + N(t * 5, 2) * h * 0.06; i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke();
+  ctx.strokeStyle = 'rgba(190,205,230,.32)'; ctx.lineWidth = w / 170;
+  for (const [x1, y1, x2, y2] of [[0, 0.5, 1, 0.47], [0.62, 0, 0.6, 1], [0.22, 0, 0.25, 1], [0, 0.15, 1, 0.92], [0, 0.9, 1, 0.12]]) { ctx.beginPath(); ctx.moveTo(x1 * w, y1 * h); ctx.lineTo(x2 * w, y2 * h); ctx.stroke(); }
+  ctx.beginPath(); ctx.ellipse(w * 0.62, h * 0.5, w * 0.16, h * 0.13, 0, 0, TAU); ctx.stroke(); ctx.beginPath(); ctx.ellipse(w * 0.22, h * 0.56, w * 0.1, h * 0.08, 0, 0, TAU); ctx.stroke(); ctx.restore();
+  // reflectivity: bowing line (arc), trailing stratiform, isolated cells ahead
+  const ac = [w * 0.05, h * 0.5], AR = w * 0.58;
+  const col = [0, 0, 0, 0];
+  field(ctx, w, h, 3, (u, v, out) => {
+    const x = u * w, y = v * h; const dx = x - ac[0], dy = y - ac[1]; const r = Math.hypot(dx, dy), a = Math.atan2(dy, dx);
+    const span = smooth(1.25, 0.75, Math.abs(a)); const d = (r - AR - Math.cos(a * 2) * w * 0.05) / w;
+    const n = N.fbm(x / 26, y / 26, 4), n2 = N(x / 9, y / 9);
+    const core = Math.exp(-((d / 0.035) ** 2)) * span * (0.65 + 0.6 * n) * (1 + 0.5 * Math.exp(-((a / 0.22) ** 2)));
+    const strat = Math.exp(-(((d + 0.12) / 0.11) ** 2)) * span * (0.5 + 0.7 * n);
+    let cell = 0; for (const [cx, cy, cr] of [[0.82, 0.25, 0.04], [0.9, 0.62, 0.03], [0.76, 0.82, 0.035]]) cell = Math.max(cell, Math.exp(-((x - cx * w) ** 2 + (y - cy * h) ** 2) / (cr * w) ** 2) * (0.7 + 0.4 * n2));
+    const z = 8 + Math.max(core * 58, strat * 28, cell * 52) + (n2 - 0.5) * 6; dbzColor(z, col); out[0] = col[0]; out[1] = col[1]; out[2] = col[2]; out[3] = col[3];
+  }, false);
+  // tornado-warning polygon at the bow apex (harm → hazard red)
+  const ap = [ac[0] + AR + w * 0.05, ac[1]]; ctx.save(); ctx.strokeStyle = '#FF3B30'; ctx.lineWidth = Math.max(1.5, w / 160); poly(ctx, [[ap[0] - w * 0.06, ap[1] - h * 0.09], [ap[0] + w * 0.13, ap[1] - h * 0.06], [ap[0] + w * 0.12, ap[1] + h * 0.07], [ap[0] - w * 0.05, ap[1] + h * 0.08]], true); ctx.stroke(); ctx.restore();
+  // lightning
+  for (let i = 0; i < 40; i++) { const a = (R() - 0.5) * 1.6, rr = AR + (R() - 0.6) * w * 0.07; const x = ac[0] + Math.cos(a) * rr, y = ac[1] + Math.sin(a) * rr; cross(ctx, x, y, w / 110, i % 5 ? 'rgba(255,255,255,.9)' : 'rgba(255,230,0,1)', 1.2); }
+  // storm motion
+  ctx.save(); ctx.translate(ap[0] + w * 0.16, ap[1] + h * 0.17); ctx.strokeStyle = '#fff'; ctx.lineWidth = 1.6; ctx.beginPath(); ctx.moveTo(-18, 0); ctx.lineTo(16, 0); ctx.lineTo(10, -5); ctx.moveTo(16, 0); ctx.lineTo(10, 5); ctx.stroke(); ctx.restore();
+  label(ctx, '72 KM/H', ap[0] + w * 0.16, ap[1] + h * 0.21, Math.max(8, w / 44), 'rgba(255,255,255,.85)', 'center');
+  for (const [t, x, y] of [['FORT WORTH', 0.22, 0.6], ['DALLAS', 0.62, 0.55], ['ARLINGTON', 0.43, 0.66]]) label(ctx, t, x * w, y * h, Math.max(7, w / 50), 'rgba(220,230,245,.55)', 'center');
+  label(ctx, '0.5° REFLECTIVITY · dBZ', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+  const lx = w * 0.05, ly = h * PT.botY; DBZ.forEach(([d, c], i) => { ctx.fillStyle = `rgb(${c[0]},${c[1]},${c[2]})`; ctx.fillRect(lx + i * (w * 0.035), ly, w * 0.035, Math.max(4, h / 90)); }); label(ctx, '20', lx, ly - 6, Math.max(7, w / 52), 'rgba(255,255,255,.7)'); label(ctx, '75', lx + DBZ.length * w * 0.035, ly - 6, Math.max(7, w / 52), 'rgba(255,255,255,.7)', 'right');
+};
+
+// one aircraft squawking 7700: the track turns red where it declared, diverts and descends
+PT.track = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const T = o.track;
+  const lats = T.pts.map((p) => p[0]).concat(T.div.lat), lons = T.pts.map((p) => p[1]).concat(T.div.lon);
+  const la0 = (Math.min(...lats) + Math.max(...lats)) / 2, lo0 = (Math.min(...lons) + Math.max(...lons)) / 2;
+  const span = Math.max(8, (Math.max(...lons) - Math.min(...lons)) * 1.5, ((Math.max(...lats) - Math.min(...lats)) * 1.6 * w) / h / Math.cos(la0 * D2R));
+  const mv = mapView(la0, lo0, span, w, h);
+  mapBase(ctx, mv, { lights: 0.9, relief: 0.6, land: '#151c26', sea: '#04070b', coast: '#3a4a60' });
+  graticule(ctx, mv, 5);
+  const P = T.pts.map(([la, lo]) => [mv.X(lo), mv.Y(la)]); const k = T.sqAt;
+  ctx.save(); ctx.lineCap = 'round'; ctx.lineJoin = 'round';
+  ctx.lineWidth = Math.max(1.5, w / 200); ctx.strokeStyle = 'rgba(190,215,240,.75)'; poly(ctx, P.slice(0, k + 1)); ctx.stroke();
+  ctx.lineWidth = Math.max(2.2, w / 130); ctx.strokeStyle = '#FF3B30'; ctx.shadowColor = 'rgba(255,59,48,.8)'; ctx.shadowBlur = 10; poly(ctx, P.slice(k)); ctx.stroke(); ctx.shadowBlur = 0;
+  // remaining leg to the diversion field
+  const cur = P[P.length - 1]; const dv = [mv.X(T.div.lon), mv.Y(T.div.lat)]; ctx.setLineDash([5, 5]); ctx.lineWidth = 1.4; ctx.strokeStyle = 'rgba(255,120,110,.8)'; ctx.beginPath(); ctx.moveTo(cur[0], cur[1]); ctx.quadraticCurveTo((cur[0] + dv[0]) / 2 + w * 0.05, (cur[1] + dv[1]) / 2, dv[0], dv[1]); ctx.stroke(); ctx.setLineDash([]);
+  for (const r of [w / 30, w / 18]) { ctx.strokeStyle = 'rgba(255,255,255,.7)'; ctx.lineWidth = 1; ctx.beginPath(); ctx.arc(dv[0], dv[1], r, 0, TAU); ctx.stroke(); }
+  ctx.restore();
+  label(ctx, T.div.iata, dv[0] + w / 16, dv[1], Math.max(9, w / 30), '#fff');
+  const p0 = P[P.length - 2] || P[0]; plane(ctx, cur[0], cur[1], Math.atan2(cur[0] - p0[0], -(cur[1] - p0[1])), Math.max(14, w / 14), '#fff');
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, cur[0], cur[1], w / 6, 'rgba(255,59,48,A)', 0.55); ctx.restore();
+  // squawk tag
+  const tx = clamp(cur[0] + w * 0.04, 4, w - w * 0.36), ty = clamp(cur[1] - h * 0.12, 4, h * 0.7); ctx.fillStyle = '#FF3B30'; ctx.fillRect(tx, ty, w * 0.3, h * 0.065); label(ctx, 'SQ 7700', tx + w * 0.15, ty + h * 0.034, Math.max(9, w / 26), '#fff', 'center');
+  // descent profile inset
+  const ix = w * 0.05, iy = h * 0.6, iw = w * 0.42, ih = h * 0.14; ctx.fillStyle = 'rgba(5,8,12,.72)'; ctx.fillRect(ix, iy, iw, ih); ctx.strokeStyle = 'rgba(255,255,255,.15)'; ctx.strokeRect(ix + 0.5, iy + 0.5, iw - 1, ih - 1);
+  const prof = T.alt; const mx = Math.max(...prof); ctx.beginPath(); prof.forEach((a, i) => { const x = ix + 4 + (i / (prof.length - 1)) * (iw - 8), y = iy + ih - 5 - (a / mx) * (ih - 14); i ? ctx.lineTo(x, y) : ctx.moveTo(x, y); }); ctx.strokeStyle = '#FF6B61'; ctx.lineWidth = 1.6; ctx.stroke();
+  label(ctx, 'ALT ↓ FL370 → FL' + Math.round(prof[prof.length - 1] / 100), ix + 5, iy + 8, Math.max(7, w / 50), 'rgba(255,255,255,.8)');
+};
+
+// lightning density over a basin (number card backdrop)
+PT.strikes = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const mv = mapView(o.lat ?? 26.5, o.lon ?? -89, o.span ?? 22, w, h);
+  mapBase(ctx, mv, { lights: 0.7, land: '#10161e', sea: '#04070b', coast: '#2c3a4c' }); const R = rng(o.seed || 77);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  const cells = [[25.6, -88.2, 1.4], [27.4, -91.5, 1.0], [24.4, -84.9, 0.9], [28.6, -86.4, 0.7], [23.2, -92.8, 1.1]];
+  for (const [la, lo, s] of cells) for (let i = 0; i < 260 * s; i++) { const x = mv.X(lo + R.gauss() * s), y = mv.Y(la + R.gauss() * s * 0.7); const age = R(); ctx.fillStyle = age < 0.15 ? 'rgba(255,255,255,.95)' : age < 0.5 ? 'rgba(255,230,90,.75)' : 'rgba(255,140,40,.45)'; ctx.fillRect(x, y, age < 0.15 ? 2.2 : 1.6, age < 0.15 ? 2.2 : 1.6); }
+  for (const [la, lo] of cells) glow(ctx, mv.X(lo), mv.Y(la), w / 5, 'rgba(255,200,80,A)', 0.18);
+  ctx.restore();
+};
+
+// GNSS interference: hex bins of degraded integrity, tracks with gaps
+PT.gnss = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const mv = mapView(o.lat ?? 56.8, o.lon ?? 21.5, o.span ?? 17, w, h);
+  mapBase(ctx, mv, { lights: 0.8, land: '#121821', sea: '#05080c', coast: '#33425a' }); const R = rng(o.seed || 5);
+  const hot = [[55.0, 20.5, 1.6], [59.3, 24.2, 1.2], [57.2, 19.0, 0.8]]; const hs = w / 16;
+  ctx.save();
+  for (let row = 0; row * hs * 0.87 < h + hs; row++) for (let col = 0; col * hs < w + hs; col++) {
+    const x = col * hs + (row % 2 ? hs / 2 : 0), y = row * hs * 0.87; const la = mv.lat(y), lo = mv.lon(x);
+    let k = 0; for (const [a, b, s] of hot) k = Math.max(k, Math.exp(-(((la - a) / s) ** 2 + ((lo - b) / (s * 1.8)) ** 2)));
+    if (k < 0.12) continue; ctx.beginPath(); for (let i = 0; i < 6; i++) { const an = Math.PI / 6 + (i * Math.PI) / 3; ctx.lineTo(x + Math.cos(an) * hs * 0.5, y + Math.sin(an) * hs * 0.5); } ctx.closePath();
+    ctx.fillStyle = `rgba(255,${Math.round(150 - k * 110)},${Math.round(60 - k * 40)},${0.12 + k * 0.5})`; ctx.fill(); ctx.strokeStyle = `rgba(255,140,90,${k * 0.5})`; ctx.stroke();
+  }
+  // airliner tracks: dashed where position integrity drops
+  ctx.lineWidth = 1.2;
+  for (let i = 0; i < 26; i++) { const y0 = R() * h, y1 = R() * h; let prevBad = null; for (let s = 0; s < 40; s++) { const t0 = s / 40, t1 = (s + 1) / 40; const x0 = t0 * w, x1 = t1 * w, ya = lerp(y0, y1, t0), yb = lerp(y0, y1, t1); const la = mv.lat(ya), lo = mv.lon(x0); let k = 0; for (const [a, b, sd] of hot) k = Math.max(k, Math.exp(-(((la - a) / sd) ** 2 + ((lo - b) / (sd * 1.8)) ** 2))); const bad = k > 0.4; ctx.strokeStyle = bad ? 'rgba(255,120,90,.0)' : 'rgba(150,205,255,.55)'; if (!bad) { ctx.beginPath(); ctx.moveTo(x0, ya); ctx.lineTo(x1, yb); ctx.stroke(); } if (bad && s % 2 === 0) { ctx.fillStyle = 'rgba(255,170,140,.7)'; ctx.fillRect(x0, ya + (R() - 0.5) * 6, 1.5, 1.5); } } }
+  ctx.restore();
+  label(ctx, 'NIC/NACp ≤ 4', w * 0.05, h * PT.topY, Math.max(8, w / 40), 'rgba(255,255,255,.85)');
+};
+
+// helicopter school: the circuit flown again and again over the field
+PT.heli = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const N = noiseGen(11);
+  field(ctx, w, h, 2, (u, v, out) => { const n = N.fbm(u * 7, v * 7, 4), f = N(u * 22, v * 22); const g = f > 0.6 ? 1 : 0; out[0] = lerp(58, 92, n) + g * 18; out[1] = lerp(72, 98, n) + g * 22; out[2] = lerp(42, 60, n); });
+  // tree lines & roads
+  ctx.save(); ctx.fillStyle = 'rgba(25,40,22,.55)'; const R = rng(3); for (let i = 0; i < 40; i++) { ctx.beginPath(); ctx.ellipse(R() * w, R() * h, w * 0.06 * R(), h * 0.012, R() * 3, 0, TAU); ctx.fill(); } ctx.restore();
+  ctx.save(); ctx.translate(w * 0.5, h * 0.5); ctx.rotate(0.06);
+  ctx.fillStyle = '#6d6f70'; ctx.fillRect(-w * 0.36, -h * 0.025, w * 0.72, h * 0.05); ctx.save(); ctx.rotate(1.1); ctx.fillStyle = '#6a6c6d'; ctx.fillRect(-w * 0.3, -h * 0.02, w * 0.6, h * 0.04); ctx.restore();
+  ctx.strokeStyle = 'rgba(255,255,255,.7)'; ctx.setLineDash([6, 6]); ctx.beginPath(); ctx.moveTo(-w * 0.34, 0); ctx.lineTo(w * 0.34, 0); ctx.stroke(); ctx.setLineDash([]);
+  for (let i = 0; i < 12; i++) { ctx.fillStyle = '#7d7f80'; ctx.fillRect(-w * 0.3 + i * w * 0.05, h * 0.08, w * 0.035, w * 0.035); }
+  // circuit laps (oldest faint)
+  const n = o.laps ?? 14; const cw = w * 0.62, ch = h * 0.42;
+  for (let i = 0; i < n; i++) { const j = i / n; const off = (hash01(i + 1) - 0.5) * w * 0.03; ctx.strokeStyle = `rgba(155,240,150,${0.12 + j * 0.65})`; ctx.lineWidth = i === n - 1 ? 2.4 : 1.1; const r = w * 0.06; const x = -cw / 2 + off, y = -ch / 2 - h * 0.02 + off; ctx.beginPath(); ctx.roundRect(x, y, cw, ch, r); ctx.stroke(); }
+  // helicopter
+  const hx = cw / 2 - w * 0.02, hy = -ch * 0.1; ctx.fillStyle = '#E8FFE4'; ctx.beginPath(); ctx.arc(hx, hy, w / 60, 0, TAU); ctx.fill(); ctx.strokeStyle = 'rgba(232,255,228,.8)'; ctx.lineWidth = 1; ctx.beginPath(); ctx.arc(hx, hy, w / 22, 0, TAU); ctx.stroke(); ctx.beginPath(); ctx.moveTo(hx, hy); ctx.lineTo(hx, hy + w / 14); ctx.stroke();
+  ctx.restore();
+  const fs = Math.max(7, w / 44); for (const [t, x, y] of [['UPWIND', 0.5, 0.25], ['DOWNWIND', 0.5, 0.79], ['BASE', 0.12, 0.52], ['CROSSWIND', 0.88, 0.48]]) label(ctx, t, x * w, y * h, fs, 'rgba(225,255,220,.75)', 'center');
+  vignette(ctx, w, h, 0.35);
+};
+
+/* =====================================================================================
+   GROUND
+   ===================================================================================== */
+// shake map: intensity bands over the coast, epicentre, stations
+PT.shake = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const Q = GE.BIGQ; const mv = mapView(Q.lat + 0.6, Q.lon - 1.6, o.span ?? 6.5, w, h);
+  mapBase(ctx, mv, { relief: 1.1, land: '#161d26', sea: '#05080c', coast: '#5a6e88', lights: 0.6 });
+  const fw = Math.round(w / 2); const wm = cropData('water', mv, fw, Math.round(h / 2)); const strike = 0.35;
+  const mmi = (la, lo) => { const dx = (lo - Q.lon) * Math.cos(Q.lat * D2R), dy = la - Q.lat; const a = dx * Math.cos(strike) + dy * Math.sin(strike), b = -dx * Math.sin(strike) + dy * Math.cos(strike); const d = Math.hypot(a / 1.7, b) * 111; return clamp(8.2 - 2.1 * Math.log10(1 + d / 9) * 1.55, 1, 9); };
+  field(ctx, w, h, 2, (u, v, out, x, y) => { const la = mv.lat(v * h), lo = mv.lon(u * w); const I = mmi(la, lo); const band = Math.floor(I); const t = clamp((band - 1) / 7, 0, 1); const j = Math.round(t * 255) * 3; const sea = wm[(y * fw + x) * 4] / 255 > 0.5; out[0] = LUT.mmi[j]; out[1] = LUT.mmi[j + 1]; out[2] = LUT.mmi[j + 2]; out[3] = I < 4 ? 0 : (sea ? 50 : 120) + (I - 4) * 26; }, true);
+  // contour lines
+  ctx.save(); ctx.lineWidth = 1; ctx.strokeStyle = 'rgba(255,255,255,.35)';
+  for (const I of [4, 5, 6, 7]) { const d = 9 * (Math.pow(10, (8.2 - I) / (2.1 * 1.55)) - 1) / 111; ctx.beginPath(); for (let k = 0; k <= 72; k++) { const an = (k / 72) * TAU; const a = Math.cos(an) * d * 1.7, b = Math.sin(an) * d; const dx = a * Math.cos(strike) - b * Math.sin(strike), dy = a * Math.sin(strike) + b * Math.cos(strike); const x = mv.X(Q.lon + dx / Math.cos(Q.lat * D2R)), y = mv.Y(Q.lat + dy); k ? ctx.lineTo(x, y) : ctx.moveTo(x, y); } ctx.stroke(); }
+  ctx.restore();
+  // rupture
+  ctx.save(); ctx.strokeStyle = '#fff'; ctx.lineWidth = 2; const e = 0.45; ctx.beginPath(); ctx.moveTo(mv.X(Q.lon - Math.cos(strike) * e), mv.Y(Q.lat - Math.sin(strike) * e)); ctx.lineTo(mv.X(Q.lon + Math.cos(strike) * e), mv.Y(Q.lat + Math.sin(strike) * e)); ctx.stroke(); ctx.restore();
+  // stations
+  const R = rng(14); for (let i = 0; i < 46; i++) { const la = Q.lat + R.gauss() * 1.3 + 0.5, lo = Q.lon - 1.2 + R.gauss() * 1.2; const m = cropData('water', mv, fw, Math.round(h / 2)); const x = mv.X(lo), y = mv.Y(la); if (x < 0 || y < 0 || x >= w || y >= h) continue; if (m[(Math.floor(y / 2) * fw + Math.floor(x / 2)) * 4] > 128) continue; const I = mmi(la, lo) + R.gauss() * 0.4; const j = Math.round(clamp((I - 1) / 7, 0, 1) * 255) * 3; ctx.fillStyle = `rgb(${LUT.mmi[j]},${LUT.mmi[j + 1]},${LUT.mmi[j + 2]})`; ctx.strokeStyle = 'rgba(0,0,0,.7)'; const s = w / 70; ctx.beginPath(); ctx.moveTo(x, y - s); ctx.lineTo(x + s * 0.9, y + s * 0.6); ctx.lineTo(x - s * 0.9, y + s * 0.6); ctx.closePath(); ctx.fill(); ctx.stroke(); }
+  // epicentre star
+  const ex = mv.X(Q.lon), ey = mv.Y(Q.lat); ctx.save(); ctx.translate(ex, ey); ctx.fillStyle = '#FF3B30'; ctx.strokeStyle = '#fff'; ctx.lineWidth = 1.5; ctx.beginPath(); for (let i = 0; i < 10; i++) { const r = i % 2 ? w / 50 : w / 22; const a = -Math.PI / 2 + (i * Math.PI) / 5; ctx.lineTo(Math.cos(a) * r, Math.sin(a) * r); } ctx.closePath(); ctx.fill(); ctx.stroke(); ctx.restore();
+  for (const [t, la, lo] of [['SENDAI', 38.27, 140.87], ['FUKUSHIMA', 37.75, 140.47], ['MITO', 36.37, 140.47], ['TOKYO', 35.68, 139.69]]) { const x = mv.X(lo), y = mv.Y(la); ctx.fillStyle = '#fff'; ctx.fillRect(x - 1.5, y - 1.5, 3, 3); label(ctx, t, x - 5, y, Math.max(7, w / 48), 'rgba(235,240,248,.85)', 'right'); }
+  const lx = w * 0.05, ly = h * PT.botY; for (let i = 2; i <= 8; i++) { const j = Math.round(((i - 1) / 7) * 255) * 3; ctx.fillStyle = `rgb(${LUT.mmi[j]},${LUT.mmi[j + 1]},${LUT.mmi[j + 2]})`; ctx.fillRect(lx + (i - 2) * w * 0.05, ly, w * 0.05, Math.max(4, h / 90)); label(ctx, ['', 'I', 'II', 'III', 'IV', 'V', 'VI', 'VII', 'VIII'][i], lx + (i - 2) * w * 0.05 + w * 0.025, ly - 7, Math.max(6, w / 60), 'rgba(255,255,255,.7)', 'center'); }
+  label(ctx, 'MMI · INSTRUMENTAL INTENSITY', w * 0.05, h * PT.topY, Math.max(8, w / 42), 'rgba(255,255,255,.85)');
+};
+
+// crowd density inside and around a stadium, top-down, with an egress crush point
+PT.stadium = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 66); const N = noiseGen(66);
+  ctx.fillStyle = '#0b0e12'; ctx.fillRect(0, 0, w, h);
+  ctx.save(); ctx.fillStyle = '#12161c'; for (let i = 0; i < 70; i++) { const x = R() * w, y = R() * h; if (Math.hypot((x - w / 2) / w, (y - h / 2) / h) < 0.36) continue; ctx.fillRect(x, y, w * (0.04 + R() * 0.07), h * (0.03 + R() * 0.05)); } ctx.restore();
+  const cx = w / 2, cy = h * 0.48, RX = w * 0.36, RY = h * 0.3;
+  ctx.fillStyle = '#1b2028'; ctx.beginPath(); ctx.ellipse(cx, cy, RX * 1.08, RY * 1.08, 0, 0, TAU); ctx.fill();
+  // intensity buffer of people
+  const k = 2, fw = Math.round(w / k), fh = Math.round(h / k); const I = new Float32Array(fw * fh);
+  const splat = (x, y, s, a) => { const r = Math.ceil(s * 2.5), x0 = Math.round(x / k), y0 = Math.round(y / k); for (let j = -r; j <= r; j++) for (let i = -r; i <= r; i++) { const X = x0 + i, Y = y0 + j; if (X < 0 || Y < 0 || X >= fw || Y >= fh) continue; I[Y * fw + X] += a * Math.exp(-(i * i + j * j) / (s * s)); } };
+  for (let n = 0; n < 2600; n++) { const a = R() * TAU, t = 0.55 + R() * 0.45; splat(cx + Math.cos(a) * RX * t, cy + Math.sin(a) * RY * t, 1.6, 0.35 + 0.5 * N(Math.cos(a) * 3, Math.sin(a) * 3)); }
+  const gates = [[-0.25, 'A'], [1.2, 'B'], [Math.PI * 0.62, 'C'], [Math.PI * 1.25, 'D']];
+  for (const [ga, gl] of gates) { const gx = cx + Math.cos(ga) * RX * 1.08, gy = cy + Math.sin(ga) * RY * 1.08; const crush = gl === 'C'; for (let n = 0; n < (crush ? 900 : 260); n++) { const d = Math.pow(R(), crush ? 1.8 : 1) * w * (crush ? 0.2 : 0.3); const sp = R.gauss() * (crush ? 0.18 : 0.12); splat(gx + Math.cos(ga + sp) * d, gy + Math.sin(ga + sp) * d, 1.8, crush ? 0.6 : 0.3); } }
+  const c2 = mk(fw, fh), cx2 = c2.getContext('2d'); const id = cx2.createImageData(fw, fh);
+  for (let i = 0; i < fw * fh; i++) { const v = clamp(I[i] / 3.2, 0, 1); const j = Math.round(v * 255) * 3; id.data[i * 4] = LUT.inferno[j]; id.data[i * 4 + 1] = LUT.inferno[j + 1]; id.data[i * 4 + 2] = LUT.inferno[j + 2]; id.data[i * 4 + 3] = v < 0.04 ? 0 : clamp(v * 900, 0, 235); }
+  cx2.putImageData(id, 0, 0); ctx.save(); ctx.imageSmoothingQuality = 'high'; ctx.drawImage(c2, 0, 0, w, h); ctx.restore();
+  // pitch
+  ctx.save(); ctx.fillStyle = '#16301e'; ctx.fillRect(cx - RX * 0.42, cy - RY * 0.42, RX * 0.84, RY * 0.84); ctx.strokeStyle = 'rgba(220,255,220,.35)'; ctx.lineWidth = 1; ctx.strokeRect(cx - RX * 0.42, cy - RY * 0.42, RX * 0.84, RY * 0.84); ctx.beginPath(); ctx.moveTo(cx, cy - RY * 0.42); ctx.lineTo(cx, cy + RY * 0.42); ctx.stroke(); ctx.beginPath(); ctx.arc(cx, cy, RY * 0.12, 0, TAU); ctx.stroke(); ctx.restore();
+  for (const [ga, gl] of gates) { const gx = cx + Math.cos(ga) * RX * 1.16, gy = cy + Math.sin(ga) * RY * 1.16; label(ctx, 'GATE ' + gl, gx, gy, Math.max(7, w / 46), gl === 'C' ? '#fff' : 'rgba(230,236,245,.6)', 'center'); }
+  const ga = gates[2][0]; const hx = cx + Math.cos(ga) * RX * 1.3, hy = cy + Math.sin(ga) * RY * 1.3; ctx.save(); ctx.strokeStyle = '#FF3B30'; ctx.lineWidth = 2; ctx.beginPath(); ctx.arc(hx, hy, w / 13, 0, TAU); ctx.stroke(); ctx.restore();
+  label(ctx, '4.6 P/M²', hx, hy + w / 9, Math.max(9, w / 30), '#FF6B61', 'center');
+  label(ctx, 'CROWD DENSITY · P/M²', w * 0.05, h * PT.topY, Math.max(8, w / 42), 'rgba(255,255,255,.85)');
+};
+
+/* ---------- CCTV-style scenes (animated: static base cached, dynamic layer per frame) ---------- */
+const SCN = (PT.scenes = {});
+function cctvOSD(ctx, w, h, t, o) {
+  const fs = Math.max(8, Math.round(w / 34)); const y0 = h * (o.osdY ?? PT.osdY), y1 = h * (o.osdB ?? PT.osdB);
+  osd(ctx, o.cam || 'CAM 0412', w * 0.045, y0, fs); osd(ctx, PT.stamp(o.at ?? Date.now()), w * 0.955, y0, fs, 'right');
+  if (o.place) osd(ctx, o.place, w * 0.045, y1 - fs, fs * 0.9);
+  if (o.rec !== false && Math.floor(t * 1.2) % 2 === 0) { ctx.fillStyle = '#FF3B30'; ctx.beginPath(); ctx.arc(w * 0.955 - fs * 0.3, y1 - fs * 0.5, fs * 0.32, 0, TAU); ctx.fill(); osd(ctx, 'REC', w * 0.955 - fs * 0.9, y1 - fs, fs * 0.9, 'right'); }
+}
+PT.osdY = 0.115; PT.osdB = 0.87; PT.topY = 0.125; PT.botY = 0.86;
+PT.cctvOSD = cctvOSD;
+
+// harbour at night: gantry cranes, a lit ship, fog, reflections, rain before a typhoon
+SCN.harbour = {
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const R = rng(o.seed || 8); const N = noiseGen(8); const hz = h * 0.56;
+    const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#0b0d12'); sky.addColorStop(0.7, '#2a2522'); sky.addColorStop(1, '#5a4430'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz);
+    // far shore: city lights band
+    ctx.fillStyle = '#121010'; ctx.fillRect(0, hz - h * 0.035, w, h * 0.04);
+    for (let i = 0; i < 260; i++) { const x = R() * w, y = hz - R() * h * 0.05; ctx.fillStyle = `rgba(255,${170 + R() * 70},${90 + R() * 80},${0.4 + R() * 0.6})`; ctx.fillRect(x, y, 1.3, 1.3); }
+    for (let i = 0; i < 9; i++) { const x = R() * w, bw = w * (0.02 + R() * 0.03), bh = h * (0.05 + R() * 0.12); ctx.fillStyle = '#0d0c0d'; ctx.fillRect(x, hz - bh, bw, bh); for (let k = 0; k < 18; k++) { if (R() < 0.5) continue; ctx.fillStyle = `rgba(255,220,160,${0.3 + R() * 0.5})`; ctx.fillRect(x + R() * bw, hz - R() * bh, 1.4, 1.4); } }
+    // gantry cranes
+    for (let i = 0; i < 4; i++) {
+      const x = w * (0.08 + i * 0.2) + R() * w * 0.04, s = h * (0.34 - i * 0.03), top = hz - s; ctx.strokeStyle = '#08080a'; ctx.fillStyle = '#08080a'; ctx.lineWidth = Math.max(2, w / 160);
+      ctx.beginPath(); ctx.moveTo(x, hz + h * 0.04); ctx.lineTo(x + w * 0.012, top); ctx.moveTo(x + w * 0.07, hz + h * 0.04); ctx.lineTo(x + w * 0.058, top); ctx.stroke();
+      ctx.fillRect(x - w * 0.09, top - h * 0.012, w * 0.26, h * 0.016); ctx.fillRect(x + w * 0.01, top - h * 0.06, w * 0.05, h * 0.05);
+      ctx.lineWidth = 1; for (let k = 0; k < 8; k++) { ctx.beginPath(); ctx.moveTo(x + w * 0.012 * (k / 8) + 1, hz + h * 0.04 - (k * s) / 8); ctx.lineTo(x + w * 0.07 - w * 0.012 * ((k + 1) / 8), hz + h * 0.04 - ((k + 1) * s) / 8); ctx.stroke(); }
+      for (let k = 0; k < 6; k++) { ctx.fillStyle = 'rgba(255,236,200,.85)'; ctx.fillRect(x - w * 0.08 + k * w * 0.045, top - h * 0.002, 2, 2); }
+    }
+    // container ship
+    const sy = hz + h * 0.02; ctx.fillStyle = '#0d0f12'; ctx.beginPath(); ctx.moveTo(w * 0.12, sy); ctx.lineTo(w * 0.92, sy); ctx.lineTo(w * 0.88, sy + h * 0.07); ctx.lineTo(w * 0.15, sy + h * 0.07); ctx.closePath(); ctx.fill();
+    const cols = ['#3b2420', '#1f2d3b', '#2b3326', '#3a3324', '#2a2a30', '#3a1f2a'];
+    for (let i = 0; i < 46; i++) for (let j = 0; j < 4; j++) { if (R() < 0.12) continue; ctx.fillStyle = cols[R.int(cols.length)]; ctx.fillRect(w * 0.18 + i * w * 0.0145, sy - (j + 1) * h * 0.014, w * 0.013, h * 0.012); }
+    ctx.fillStyle = '#16181c'; ctx.fillRect(w * 0.8, sy - h * 0.1, w * 0.07, h * 0.1); for (let k = 0; k < 14; k++) { ctx.fillStyle = 'rgba(255,230,180,.85)'; ctx.fillRect(w * 0.805 + (k % 7) * w * 0.009, sy - h * 0.09 + Math.floor(k / 7) * h * 0.02, 2, 2); }
+    // water
+    const wg = ctx.createLinearGradient(0, hz, 0, h); wg.addColorStop(0, '#15120f'); wg.addColorStop(1, '#050506'); ctx.fillStyle = wg; ctx.fillRect(0, sy + h * 0.07, w, h);
+    // quay & lamps in the foreground
+    ctx.fillStyle = '#0a0a0b'; ctx.beginPath(); ctx.moveTo(0, h * 0.86); ctx.lineTo(w, h * 0.8); ctx.lineTo(w, h); ctx.lineTo(0, h); ctx.fill();
+    for (let i = 0; i < 4; i++) { const x = w * (0.1 + i * 0.28), y = h * (0.86 - i * 0.015); ctx.fillStyle = '#060606'; ctx.fillRect(x, y - h * 0.16, 2, h * 0.16); }
+    // fog
+    for (let y = 0; y < h; y += 4) { const f = Math.exp(-(((y - hz) / (h * 0.12)) ** 2)) * 0.18; ctx.fillStyle = `rgba(150,130,110,${f})`; ctx.fillRect(0, y, w, 4); }
+    c.lights = []; for (let i = 0; i < 4; i++) c.lights.push([w * (0.1 + i * 0.28) + 1, h * (0.86 - i * 0.015) - h * 0.16]);
+    c.hz = hz; c.sy = sy + h * 0.07; return c;
+  },
+  frame(ctx, w, h, t, o, B) {
+    ctx.drawImage(B, 0, 0); const N = this._n || (this._n = noiseGen(4)); const R = rng(Math.floor(t * 8));
+    ctx.save(); ctx.globalCompositeOperation = 'lighter';
+    // reflections shimmer
+    for (let y = B.sy; y < h * 0.86; y += 2) { const f = (y - B.sy) / (h * 0.86 - B.sy); for (const [lx, a] of [[0.83, 0.35], [0.3, 0.12], [0.55, 0.1], [0.12, 0.08]]) { const j = (N(y * 0.15, t * 2 + lx * 9) - 0.5) * 16 * (0.5 + f); ctx.fillStyle = `rgba(255,170,90,${a * (1 - f * 0.7)})`; ctx.fillRect(lx * w + j - 3 - f * 8, y, 6 + f * 16, 1.3); } }
+    for (const [x, y] of B.lights) glow(ctx, x, y, w * 0.06, 'rgba(255,170,80,A)', 0.55);
+    for (let i = 0; i < 4; i++) { const on = Math.sin(t * 3 + i * 1.7) > 0; if (!on) continue; glow(ctx, w * (0.1 + i * 0.2) + w * 0.035, B.hz - h * (0.34 - i * 0.03) - h * 0.065, w * 0.025, 'rgba(255,40,30,A)', 0.9); }
+    ctx.restore();
+    // light rain
+    ctx.save(); ctx.strokeStyle = 'rgba(200,200,210,.18)'; ctx.lineWidth = 1; ctx.beginPath(); for (let i = 0; i < 90; i++) { const x = (R() * w + t * 60) % w, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - 3, y + h * 0.03); } ctx.stroke(); ctx.restore();
+    scan(ctx, w, h, 0.06); vignette(ctx, w, h, 0.5); grain(ctx, w, h, 0.12);
+    cctvOSD(ctx, w, h, t, o);
+  },
+};
+
+// scramble crossing at night in the rain: umbrellas from a high camera, neon on wet asphalt
+SCN.crossing = {
+  // high camera over a scramble: ground plane in perspective, crowds waiting and crossing in the rain
+  map(w, h) { const top = h * 0.25, zF = 2.3, zN = 1; return (u, v) => { const z = lerp(zF, zN, v); const y = top + (h - top) * ((1 / z - 1 / zF) / (1 / zN - 1 / zF)); return [w / 2 + ((u - 0.5) * w * 1.3) / z, y, 1 / z]; }; },
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const R = rng(o.seed || 31); const M = this.map(w, h); const top = h * 0.25;
+    // facades, video screens and signs (abstract, no marks)
+    const fg = ctx.createLinearGradient(0, 0, 0, top); fg.addColorStop(0, '#060609'); fg.addColorStop(1, '#141218'); ctx.fillStyle = fg; ctx.fillRect(0, 0, w, top + 2);
+    for (let i = 0; i < 7; i++) { const x = (i / 7) * w + R() * 10, bw = w / 7 - 4; ctx.fillStyle = `rgb(${12 + R() * 10},${12 + R() * 8},${16 + R() * 10})`; ctx.fillRect(x, R() * top * 0.2, bw, top); for (let k = 0; k < 40; k++) { if (R() < 0.5) continue; ctx.fillStyle = `rgba(255,${210 + R() * 40},${160 + R() * 70},${0.25 + R() * 0.4})`; ctx.fillRect(x + R() * bw, R() * top, 2, 1.5); } }
+    const neon = ['255,70,130', '70,200,255', '255,190,70', '170,110,255', '90,255,190'];
+    const screens = []; for (let i = 0; i < 4; i++) { const x = w * (0.05 + i * 0.25) + R() * 10, y = top * (0.14 + R() * 0.3), sw = w * (0.09 + R() * 0.05), sh = top * (0.22 + R() * 0.16); screens.push([x, y, sw, sh, neon[R.int(5)], neon[R.int(5)]]); }
+    for (const [x, y, sw, sh, a, b] of screens) { ctx.fillStyle = '#050507'; ctx.fillRect(x - 3, y - 3, sw + 6, sh + 6); const g = ctx.createLinearGradient(x, y, x + sw, y + sh); g.addColorStop(0, `rgba(${a},.75)`); g.addColorStop(0.6, `rgba(${b},.55)`); g.addColorStop(1, `rgba(${a},.35)`); ctx.fillStyle = g; ctx.fillRect(x, y, sw, sh); ctx.fillStyle = 'rgba(255,255,255,.35)'; for (let k = 0; k < 3; k++) ctx.fillRect(x + sw * 0.1, y + sh * (0.55 + k * 0.12), sw * (0.3 + R() * 0.5), Math.max(1, sh * 0.05)); ctx.fillStyle = 'rgba(0,0,0,.25)'; for (let yy = y; yy < y + sh; yy += 2) ctx.fillRect(x, yy, sw, 1); ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, x + sw / 2, y + sh / 2, sw * 0.8, `rgba(${a},A)`, 0.18); ctx.restore(); }
+    for (let i = 0; i < 9; i++) { const x = R() * w, y = R() * top * 0.7; ctx.fillStyle = `rgba(${neon[R.int(5)]},.6)`; ctx.fillRect(x, y, w * 0.008, top * (0.15 + R() * 0.25)); }
+    // asphalt
+    ctx.fillStyle = '#121117'; ctx.beginPath(); const q = [M(0, 0), M(1, 0), M(1, 1), M(0, 1)]; ctx.moveTo(-w, top); ctx.lineTo(w * 2, top); ctx.lineTo(w * 2, h); ctx.lineTo(-w, h); ctx.fill();
+    ctx.save(); ctx.globalCompositeOperation = 'lighter';
+    for (const [x, y, sw, sh, a] of screens) { const g = ctx.createLinearGradient(0, top, 0, h); g.addColorStop(0, `rgba(${a},.30)`); g.addColorStop(0.6, `rgba(${a},.05)`); g.addColorStop(1, `rgba(${a},0)`); ctx.fillStyle = g; for (let k = 0; k < 6; k++) ctx.fillRect(x + sw * (0.1 + k * 0.15) + R.gauss() * 3, top, sw * 0.08, h - top); }
+    ctx.restore();
+    // crosswalk stripes as quads on the ground plane
+    const zebra = (u1, v1, u2, v2, n, wd) => { const du = u2 - u1, dv = v2 - v1, L = Math.hypot(du, dv); const nu = -dv / L * wd, nv = du / L * wd; ctx.fillStyle = 'rgba(205,208,218,.26)'; for (let i = 0; i < n; i++) { const t0 = (i + 0.15) / n, t1 = (i + 0.62) / n; const a = M(u1 + du * t0 + nu, v1 + dv * t0 + nv), b = M(u1 + du * t1 + nu, v1 + dv * t1 + nv), cc = M(u1 + du * t1 - nu, v1 + dv * t1 - nv), d = M(u1 + du * t0 - nu, v1 + dv * t0 - nv); poly(ctx, [a, b, cc, d], true); ctx.fill(); } };
+    zebra(0.1, 0.14, 0.9, 0.14, 26, 0.06); zebra(0.08, 0.9, 0.92, 0.9, 26, 0.07); zebra(0.08, 0.2, 0.08, 0.84, 20, 0.055); zebra(0.92, 0.2, 0.92, 0.84, 20, 0.055); zebra(0.17, 0.22, 0.83, 0.82, 30, 0.028); zebra(0.83, 0.22, 0.17, 0.82, 30, 0.028);
+    // kerbs/corner pavements
+    ctx.fillStyle = '#1d1c22'; for (const [u0, v0] of [[-0.3, -0.2], [1.0, -0.2], [-0.3, 1.0], [1.0, 1.0]]) { poly(ctx, [M(u0, v0), M(u0 + 0.3, v0), M(u0 + 0.3, v0 + 0.2), M(u0, v0 + 0.2)], true); ctx.fill(); }
+    // vehicles waiting, lights on
+    for (const [u, v, d] of [[-0.05, 0.4, 1], [-0.05, 0.55, 1], [-0.05, 0.7, 1], [1.05, 0.35, -1], [1.05, 0.5, -1], [0.35, -0.05, 0], [0.55, 1.08, 0]]) { const [x, y, s] = M(u, v); ctx.fillStyle = '#18181d'; ctx.fillRect(x - 22 * s, y - 9 * s, 44 * s, 18 * s); ctx.save(); ctx.globalCompositeOperation = 'lighter'; if (d >= 0) { glow(ctx, x + 22 * s, y - 5 * s, 26 * s, 'rgba(255,248,225,A)', 0.8); glow(ctx, x + 22 * s, y + 5 * s, 26 * s, 'rgba(255,248,225,A)', 0.8); } else { glow(ctx, x + 22 * s, y, 18 * s, 'rgba(255,40,40,A)', 0.7); } ctx.restore(); }
+    // people
+    const P = []; const corners = [[0.06, 0.08], [0.94, 0.08], [0.06, 0.94], [0.94, 0.94]]; const cols = ['226,60,72', '34,44,64', '236,236,242', '56,134,228', '248,188,44', '26,26,32', '118,196,124', '240,120,170', '40,40,46', '190,190,200'];
+    for (let i = 0; i < 520; i++) { const wait = i < 170; const ci = i % 4; const a = corners[ci], b = wait ? a : corners[[3, 2, 1, 0, 1, 0, 3, 2][(i >> 2) % 8] ?? 3 - ci]; const umb = R() < 0.72; P.push({ a, b, wait, off: R(), sp: 0.035 + R() * 0.03, jx: R.gauss() * (wait ? 0.035 : 0.03), jy: R.gauss() * (wait ? 0.03 : 0.022), umb, col: cols[R.int(cols.length)], s: 0.8 + R() * 0.45 }); }
+    c.P = P; c.M = M; return c;
+  },
+  frame(ctx, w, h, t, o, B) {
+    ctx.drawImage(B, 0, 0); const M = B.M; const list = [];
+    for (const p of B.P) { const u = p.wait ? 0 : (p.off + t * p.sp) % 1; const [x, y, s] = M(lerp(p.a[0], p.b[0], u) + p.jx, lerp(p.a[1], p.b[1], u) + p.jy); list.push([y, x, s * (w / 46) * p.s, p]); }
+    list.sort((a, b) => a[0] - b[0]);
+    for (const [y, x, s, p] of list) { if (p.umb) { ctx.fillStyle = `rgba(${p.col},.95)`; ctx.beginPath(); ctx.ellipse(x, y, s * 1.1, s * 0.82, 0, 0, TAU); ctx.fill(); ctx.fillStyle = 'rgba(255,255,255,.16)'; ctx.beginPath(); ctx.ellipse(x - s * 0.25, y - s * 0.22, s * 0.5, s * 0.32, 0, 0, TAU); ctx.fill(); } else { ctx.fillStyle = '#17161b'; ctx.beginPath(); ctx.ellipse(x, y + s * 0.2, s * 0.55, s * 0.4, 0, 0, TAU); ctx.fill(); ctx.fillStyle = '#2b2622'; ctx.beginPath(); ctx.arc(x, y - s * 0.1, s * 0.33, 0, TAU); ctx.fill(); } }
+    ctx.save(); ctx.strokeStyle = 'rgba(210,215,230,.15)'; ctx.lineWidth = 1; const R = rng(Math.floor(t * 10)); ctx.beginPath(); for (let i = 0; i < 160; i++) { const x = R() * w, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - 2, y + h * 0.025); } ctx.stroke(); ctx.restore();
+    vignette(ctx, w, h, 0.45); scan(ctx, w, h, 0.05); grain(ctx, w, h, 0.1);
+    if (!o.noOSD) cctvOSD(ctx, w, h, t, o);
+  },
+};
+
+// waterfront in a storm at night: looking along the wall, swells breaking over it, sodium lamps on a
+// flooded road, a town behind; handheld when a person films it
+SCN.seawall = {
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const R = rng(o.seed || 51); const N = noiseGen(o.seed || 51); const hz = h * 0.4;
+    const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#06070a'); sky.addColorStop(1, o.skyline ? '#2a2129' : '#191a20'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz + 2);
+    field(ctx, w, hz, 3, (u, v, out) => { const n = N.fbm(u * 2.5 + v, v * 4, 5); out[0] = 34 + n * 40; out[1] = 32 + n * 38; out[2] = 38 + n * 40; out[3] = 150 * smooth(0.35, 0.8, n); });
+    // town / skyline on the right half, beyond the road
+    const town = (x0, x1, tall) => { for (let i = 0; i < (tall ? 26 : 34); i++) { const x = lerp(x0, x1, R()), bw = w * (tall ? 0.02 + R() * 0.035 : 0.025 + R() * 0.04), bh = h * (tall ? 0.04 + Math.pow(R(), 2) * 0.24 : 0.02 + R() * 0.05); ctx.fillStyle = '#0b0a0d'; ctx.fillRect(x, hz - bh, bw, bh + 2); const n = Math.floor(bw * bh * 0.012); for (let k = 0; k < n; k++) { if (R() < 0.5) continue; ctx.fillStyle = `rgba(255,${190 + R() * 60},${120 + R() * 90},${0.3 + R() * 0.6})`; ctx.fillRect(x + R() * bw, hz - R() * bh, 1.4, 1.4); } } };
+    town(w * 0.5, w * 1.0, !!o.skyline);
+    ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, w * 0.8, hz, w * 0.5, 'rgba(255,140,60,A)', o.skyline ? 0.22 : 0.12); ctx.restore();
+    // sea on the left: dark swells with streaked foam, perspective-compressed toward the horizon
+    field(ctx, w, h, 2, (u, v, out) => { const y = v * h; if (y < hz) { out[3] = 0; return; } const d = (y - hz) / (h - hz); const z = 1 / (0.05 + d); const n = N.fbm(u * 3 * z * 0.25 + 3, d * 9 + z * 0.15, 5); const sw = Math.sin(z * 1.6 + n * 4); const crest = smooth(0.7, 0.98, sw) * smooth(0.45, 0.7, n); const foam = smooth(0.68, 0.82, N(u * 30 * z * 0.1, d * 60)) * 0.35 * smooth(0.5, 0.75, n);
+      out[0] = 10 + n * 22 + (crest + foam) * 170; out[1] = 13 + n * 25 + (crest + foam) * 172; out[2] = 18 + n * 28 + (crest + foam) * 178; out[3] = 255; });
+    // the wall: a parapet running from bottom-left toward the horizon; road + puddles on its right
+    const vp = [w * 0.56, hz + h * 0.005]; const L0 = [w * -0.02, h * 1.0], L1 = [w * 0.22, h * 1.0];
+    ctx.fillStyle = '#1e1d1f'; poly(ctx, [L0, vp, [vp[0] + 2, vp[1]], L1], true); ctx.fill(); // wall top
+    const road = [[w * 0.22, h], [vp[0] + 2, vp[1]], [w * 0.9, vp[1] + h * 0.02], [w * 1.2, h]]; const rg = ctx.createLinearGradient(0, hz, 0, h); rg.addColorStop(0, '#141316'); rg.addColorStop(1, '#0a0a0b'); ctx.fillStyle = rg; poly(ctx, road, true); ctx.fill();
+    ctx.strokeStyle = 'rgba(200,190,170,.18)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(L1[0], L1[1]); ctx.lineTo(vp[0] + 2, vp[1]); ctx.stroke();
+    // lamps along the road edge
+    const lamps = []; for (let i = 0; i < 7; i++) { const f = Math.pow(i / 7, 0.8); const bx = lerp(w * 0.5, vp[0] + w * 0.02, f), by = lerp(h * 1.0, vp[1] + h * 0.004, f); const lh = lerp(h * 0.5, h * 0.02, f); ctx.fillStyle = '#050506'; ctx.fillRect(bx, by - lh, Math.max(1.2, 6 * (1 - f)), lh); ctx.fillRect(bx - lh * 0.12, by - lh, lh * 0.14, Math.max(1, 4 * (1 - f))); lamps.push([bx - lh * 0.1, by - lh + 3, 1 - f, by]); }
+    if (o.palm) { ctx.save(); ctx.translate(w * 0.9, h * 0.98); ctx.strokeStyle = '#040404'; ctx.lineWidth = w / 45; ctx.beginPath(); ctx.moveTo(0, 0); ctx.quadraticCurveTo(-w * 0.02, -h * 0.3, -w * 0.12, -h * 0.5); ctx.stroke(); ctx.lineWidth = w / 160; for (let k = 0; k < 9; k++) { const a = -2.6 + k * 0.28; ctx.beginPath(); ctx.moveTo(-w * 0.12, -h * 0.5); ctx.quadraticCurveTo(-w * 0.12 + Math.cos(a) * w * 0.08, -h * 0.5 + Math.sin(a) * h * 0.04, -w * 0.12 + Math.cos(a) * w * 0.17 - w * 0.05, -h * 0.5 + Math.sin(a) * h * 0.06 + h * 0.06); ctx.stroke(); } ctx.restore(); }
+    c.lamps = lamps; c.hz = hz; c.vp = vp; return c;
+  },
+  frame(ctx, w, h, t, o, B) {
+    const shake = o.handheld ? [Math.sin(t * 7.1) * w * 0.004 + Math.sin(t * 2.3) * w * 0.006, Math.cos(t * 6.3) * h * 0.003] : [0, 0];
+    ctx.save(); ctx.translate(shake[0], shake[1]); ctx.drawImage(B, -4, -4, w + 8, h + 8);
+    ctx.save(); ctx.globalCompositeOperation = 'lighter';
+    for (const [x, y, f, gy] of B.lamps) { glow(ctx, x, y, w * 0.14 * (0.3 + f), 'rgba(255,150,50,A)', 0.55 + 0.1 * Math.sin(t * 13 + x)); const g = ctx.createLinearGradient(0, gy - h * 0.01, 0, gy + h * 0.16 * f); g.addColorStop(0, 'rgba(255,150,60,.0)'); g.addColorStop(0.2, 'rgba(255,150,60,.3)'); g.addColorStop(1, 'rgba(255,150,60,0)'); ctx.fillStyle = g; ctx.fillRect(x - w * 0.012 * (0.5 + f), gy - h * 0.01, w * 0.024 * (0.5 + f) + 1.5, h * 0.17 * f); }
+    // breaking swells: spray sheets rise off the wall and blow right with the wind
+    const R0 = rng(7); for (let b = 0; b < 3; b++) { const per = 3.6 + b * 1.3; const tt = t + b * 1.7; const ph = (tt % per) / per; if (ph > 0.6) continue; const k = Math.sin((ph / 0.6) * Math.PI); const f = [0.18, 0.42, 0.68][b]; const bx = lerp(w * 0.08, B.vp[0], f), by = lerp(h * 0.98, B.vp[1], f); const sz = (1 - f * 0.85) * h * 0.55; const R = rng(b * 97 + Math.floor(tt / per));
+      for (let i = 0; i < 90; i++) { const up = Math.pow(R(), 0.7) * sz * k, side = (R() - 0.35) * sz * 0.35 + up * 0.6 * ph; const x = bx + side, y = by - up; const r = (0.002 + R() * 0.007) * w * (1 - f * 0.6) * (0.6 + k); ctx.fillStyle = `rgba(210,218,230,${(0.04 + R() * 0.1) * k})`; ctx.beginPath(); ctx.arc(x, y, r, 0, TAU); ctx.fill(); }
+      ctx.strokeStyle = `rgba(220,226,236,${0.08 * k})`; ctx.lineWidth = Math.max(1, w / 400); ctx.beginPath(); for (let i = 0; i < 40; i++) { const up = R() * sz * k; const x = bx + (R() - 0.3) * sz * 0.3, y = by - up * 0.3; ctx.moveTo(x, y); ctx.lineTo(x + sz * 0.12 * ph + R() * 6, y - up * 0.7); } ctx.stroke();
+      const g = ctx.createRadialGradient(bx + sz * 0.25 * ph, by - sz * 0.35 * k, 0, bx + sz * 0.25 * ph, by - sz * 0.35 * k, sz * 0.55); g.addColorStop(0, `rgba(190,198,212,${0.13 * k})`); g.addColorStop(1, 'rgba(190,198,212,0)'); ctx.fillStyle = g; ctx.fillRect(bx - sz, by - sz * 1.2, sz * 2.2, sz * 1.4); }
+    ctx.restore();
+    // rain, wind-driven, brighter near the lamps
+    const R = rng(Math.floor(t * 24)); ctx.lineWidth = 1; ctx.strokeStyle = 'rgba(205,212,228,.26)'; ctx.beginPath(); for (let i = 0; i < 320; i++) { const x = R() * w * 1.25, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - w * 0.035, y + h * 0.05); } ctx.stroke();
+    ctx.strokeStyle = 'rgba(255,190,120,.35)'; ctx.beginPath(); for (const [x, y, f] of B.lamps) for (let i = 0; i < 10 * f; i++) { const xx = x + (R() - 0.5) * w * 0.2 * f, yy = y + (R() - 0.3) * h * 0.2 * f; ctx.moveTo(xx, yy); ctx.lineTo(xx - w * 0.02, yy + h * 0.03); } ctx.stroke();
+    ctx.restore();
+    vignette(ctx, w, h, 0.55); grain(ctx, w, h, 0.12);
+    if (!o.noOSD) cctvOSD(ctx, w, h, t, o);
+  },
+};
+
+// a quiet volcano webcam by day: ash column over the bay
+SCN.volcano = {
+  base(w, h, o) {
+    const c = mk(w, h), ctx = c.getContext('2d'); const N = noiseGen(12); const R = rng(12); const hz = h * 0.66;
+    const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#6f8fb0'); sky.addColorStop(1, '#c9cfd2'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, hz);
+    // ash plume
+    const vx = w * 0.46, vy = hz - h * 0.3;
+    field(ctx, w, h, 2, (u, v, out) => { const x = u * w - vx, y = v * h - vy; if (y > 4) { out[3] = 0; return; } const up = -y; const drift = up * 0.55; const wd = 10 + up * 0.32; const n = N.fbm((x - drift) / 40, up / 40, 5); const d = Math.exp(-(((x - drift) / wd) ** 2) * (1.2 - n)) * smooth(0, 20, up) * (0.4 + 0.9 * n) * Math.exp(-up / (h * 1.2)); const a = clamp(d * 1.3, 0, 0.95); const sh = 0.6 + (x - drift) / wd * 0.15; out[0] = (120 + n * 70) * sh; out[1] = (108 + n * 62) * sh; out[2] = (98 + n * 58) * sh; out[3] = a * 255; });
+    // cone
+    const prof = (x) => { const d = Math.abs(x - vx) / w; return vy + (d < 0.035 ? (0.035 - d) * h * 0.25 : 0) + Math.pow(d, 1.35) * h * 0.95 + N(x / 22, 0) * 5; };
+    field(ctx, w, h, 1.5, (u, v, out) => { const x = u * w, y = v * h; const top = prof(x); if (y < top || y > hz + 2) { out[3] = 0; return; } const d = (x - vx) / w; const n = N.fbm(u * 14, v * 6, 4); const gul = Math.pow(Math.abs(Math.sin(d * 60 + n * 3)), 6); const shade = 0.75 + d * 1.1 - gul * 0.25; const veg = smooth(0.08, 0.22, (y - top) / h) * smooth(0.4, 0.7, n); out[0] = (78 + n * 30) * shade - veg * 20; out[1] = (72 + n * 26) * shade + veg * 6; out[2] = (66 + n * 22) * shade - veg * 10; out[3] = 255; });
+    // bay
+    const wg = ctx.createLinearGradient(0, hz, 0, h); wg.addColorStop(0, '#7f9aa8'); wg.addColorStop(1, '#3d5664'); ctx.fillStyle = wg; ctx.fillRect(0, hz, w, h - hz);
+    for (let y = hz; y < h; y += 2) { ctx.fillStyle = `rgba(255,255,255,${0.04 + R() * 0.05})`; ctx.fillRect(R() * w, y, w * 0.2 * R(), 1); }
+    // town on the near shore
+    ctx.fillStyle = '#2f3438'; ctx.fillRect(0, h * 0.86, w, h * 0.14); for (let i = 0; i < 60; i++) { const x = R() * w, bw = w * (0.02 + R() * 0.04), bh = h * (0.02 + R() * 0.06); ctx.fillStyle = ['#d8d4cc', '#b9b4aa', '#8e8a84', '#6c6a68'][R.int(4)]; ctx.fillRect(x, h * 0.88 - bh, bw, bh); }
+    return c;
+  },
+  frame(ctx, w, h, t, o, B) { ctx.drawImage(B, 0, 0); vignette(ctx, w, h, 0.25); grain(ctx, w, h, 0.07); if (!o.noOSD) cctvOSD(ctx, w, h, t, o); },
+};
+
+/* =====================================================================================
+   INSIDE — what a person saw
+   ===================================================================================== */
+PT.aurora = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 61); const N = noiseGen(61); const hz = h * 0.66;
+  const sky = ctx.createLinearGradient(0, 0, 0, hz); sky.addColorStop(0, '#02030a'); sky.addColorStop(1, '#0b1a22'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, h);
+  for (let i = 0; i < 500; i++) { ctx.fillStyle = `rgba(255,255,255,${R() * 0.8})`; ctx.fillRect(R() * w, R() * hz, 1, 1); }
+  // curtains (per-pixel: base line, height and ray striation per column)
+  const curtains = [[0.42, 0.06, 1.3, [170, 80, 255]], [0.55, 0.04, 4.2, [200, 90, 255]]];
+  field(ctx, w, h, 3, (u, v, out) => { let r = 0, g = 0, b = 0; const y = v * h; for (const [yb, amp, sd, top] of curtains) { const base = h * yb + Math.sin(u * 5 + sd) * amp * h + N(u * 6, sd) * amp * h * 1.4; const ht = h * (0.18 + 0.28 * N.fbm(u * 9 + sd, sd, 3)); const f = (base - y) / ht; if (f < -0.03 || f > 1) continue; const ray = 0.35 + 0.65 * Math.pow(N(u * 70, sd * 3), 2); const low = f < 0 ? smooth(-0.03, 0, f) : 1; const gk = Math.exp(-f * 3.2) * low * ray, pk = smooth(0.25, 0.9, f) * (1 - f) * ray * 0.6; r += gk * 60 + pk * top[0]; g += gk * 255 + pk * top[1] * 0.3; b += gk * 140 + pk * top[2]; } out[0] = r * 0.7; out[1] = g * 0.7; out[2] = b * 0.7; out[3] = 255; }, true, 'lighter');
+  // mountains + fjord reflection
+  ctx.fillStyle = '#05070a'; ctx.beginPath(); ctx.moveTo(0, hz); for (let x = 0; x <= w; x += 3) ctx.lineTo(x, hz - h * 0.05 - N.ridge(x / w * 3, 2, 4) * h * 0.16); ctx.lineTo(w, hz); ctx.fill();
+  const img = ctx.getImageData(0, 0, w, Math.floor(hz)); const ref = mk(w, Math.floor(hz)); ref.getContext('2d').putImageData(img, 0, 0);
+  ctx.save(); ctx.translate(0, hz * 2); ctx.scale(1, -1); ctx.globalAlpha = 0.45; for (let y = 0; y < hz; y += 3) { const j = Math.sin(y * 0.4) * 2; ctx.drawImage(ref, 0, y, w, 3, j, y, w, 3); } ctx.restore();
+  ctx.fillStyle = 'rgba(2,4,8,.35)'; ctx.fillRect(0, hz, w, h - hz);
+  ctx.fillStyle = '#020305'; ctx.fillRect(0, h * 0.9, w, h * 0.1); for (let i = 0; i < 26; i++) { const x = R() * w, th = h * (0.06 + R() * 0.1); ctx.beginPath(); ctx.moveTo(x, h * 0.9 - th); ctx.lineTo(x - th * 0.22, h * 0.91); ctx.lineTo(x + th * 0.22, h * 0.91); ctx.fill(); }
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, w * 0.7, h * 0.885, w * 0.05, 'rgba(255,190,110,A)', 0.8); ctx.restore();
+  vignette(ctx, w, h, 0.45); grain(ctx, w, h, 0.12);
+};
+
+// a hillside on fire, from the road
+PT.firewit = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 71); const N = noiseGen(71);
+  const sky = ctx.createLinearGradient(0, 0, 0, h * 0.7); sky.addColorStop(0, '#07060a'); sky.addColorStop(0.7, '#3a1a10'); sky.addColorStop(1, '#8a3a12'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, h);
+  // smoke lit from below
+  field(ctx, w, h * 0.7, 3, (u, v, out) => { const n = N.fbm(u * 3 + 0.5 * v, v * 4, 5); const lit = smooth(0.2, 0.95, v); out[0] = 40 + n * 90 * lit + 60 * lit; out[1] = 25 + n * 45 * lit; out[2] = 20 + n * 25 * lit; out[3] = 255 * smooth(0.35, 0.75, n) * 0.85; });
+  const ridge = (x) => h * 0.52 - N.fbm(x / w * 2.4, 3, 4) * h * 0.22 + (x / w) * h * 0.06;
+  ctx.fillStyle = '#060404'; ctx.beginPath(); ctx.moveTo(0, h); for (let x = 0; x <= w; x += 3) ctx.lineTo(x, ridge(x)); ctx.lineTo(w, h); ctx.fill();
+  // flames along the ridge
+  ctx.save(); ctx.globalCompositeOperation = 'lighter';
+  for (let x = 0; x < w; x += 2) { const y = ridge(x); const k = smooth(0.25, 0.6, N(x / 40, 7)); if (k < 0.05) continue; const fh = h * (0.02 + 0.07 * N(x / 9, 2)) * k; const g = ctx.createLinearGradient(0, y, 0, y - fh); g.addColorStop(0, `rgba(255,220,120,${0.9 * k})`); g.addColorStop(0.4, `rgba(255,120,30,${0.7 * k})`); g.addColorStop(1, 'rgba(200,40,10,0)'); ctx.fillStyle = g; ctx.fillRect(x, y - fh, 2.4, fh + 2); }
+  for (let x = 0; x < w; x += w / 14) { const y = ridge(x); glow(ctx, x, y, w * 0.12, 'rgba(255,100,20,A)', 0.25 * smooth(0.25, 0.6, N(x / 40, 7))); }
+  for (let i = 0; i < 120; i++) { const x = R() * w, y = R() * h * 0.55; ctx.fillStyle = `rgba(255,${150 + R() * 80},60,${R() * 0.8})`; ctx.fillRect(x, y, 1.6, 1.6); }
+  ctx.restore();
+  // road & tail lights
+  ctx.fillStyle = '#0b0b0c'; ctx.beginPath(); ctx.moveTo(0, h); ctx.lineTo(w * 0.42, h * 0.74); ctx.lineTo(w * 0.52, h * 0.74); ctx.lineTo(w, h); ctx.fill();
+  ctx.strokeStyle = 'rgba(255,220,120,.4)'; ctx.setLineDash([8, 10]); ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(w * 0.62, h); ctx.lineTo(w * 0.475, h * 0.745); ctx.stroke(); ctx.setLineDash([]);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; for (const [x, y, s] of [[0.36, 0.86, 1], [0.44, 0.8, 0.6], [0.47, 0.77, 0.4]]) { glow(ctx, x * w, y * h, w * 0.04 * s, 'rgba(255,30,30,A)', 0.8); glow(ctx, x * w + w * 0.06 * s, y * h, w * 0.04 * s, 'rgba(255,30,30,A)', 0.8); } ctx.restore();
+  vignette(ctx, w, h, 0.5); grain(ctx, w, h, 0.13);
+};
+
+// inside the cabin of a diverting airliner: masks down, emergency floor lighting, a calm crew
+PT.cabin = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 81); const vx = w * 0.52, vy = h * 0.42;
+  const bg = ctx.createRadialGradient(vx, vy, 0, vx, vy, h); bg.addColorStop(0, '#5a5040'); bg.addColorStop(0.35, '#2a2620'); bg.addColorStop(1, '#0c0b0a'); ctx.fillStyle = bg; ctx.fillRect(0, 0, w, h);
+  const P = (x, y, z) => [vx + (x - vx) * z, vy + (y - vy) * z];
+  // ceiling & bins
+  ctx.fillStyle = '#1e1c1a'; poly(ctx, [[0, 0], [w, 0], P(w, 0, 0.12), P(0, 0, 0.12)], true); ctx.fill();
+  for (const side of [0, 1]) { const x0 = side ? w : 0; ctx.fillStyle = '#2c2a27'; poly(ctx, [[x0, h * 0.05], P(x0, h * 0.05, 0.12), P(x0, h * 0.3, 0.12), [x0, h * 0.3]], true); ctx.fill();
+    ctx.strokeStyle = 'rgba(255,236,200,.5)'; ctx.lineWidth = 2; ctx.beginPath(); ctx.moveTo(x0, h * 0.3); const e = P(x0, h * 0.3, 0.12); ctx.lineTo(e[0], e[1]); ctx.stroke(); }
+  // windows (dark night outside, faint blue)
+  for (let i = 0; i < 9; i++) { const z = 1 / (1 + i * 0.55); for (const side of [0, 1]) { const x0 = side ? w : 0; const [x, y] = P(x0, h * 0.36, z); const ww = w * 0.05 * z, wh = h * 0.08 * z; ctx.fillStyle = '#0b1424'; ctx.beginPath(); ctx.ellipse(x + (side ? -ww : ww), y, ww * 0.5, wh * 0.5, 0, 0, TAU); ctx.fill(); } }
+  // seat rows receding
+  for (let i = 9; i >= 0; i--) { const z = 1 / (1 + i * 0.55); for (const side of [0, 1]) { for (let k = 0; k < 3; k++) { const sx = side ? lerp(w * 0.62, w * 1.05, k / 2.4) : lerp(w * 0.42, -w * 0.05, k / 2.4); const [x, y] = P(sx, h * 0.6, z); const sw = w * 0.13 * z, sh = h * 0.3 * z; ctx.fillStyle = `rgb(${18 + i * 2},${24 + i * 2},${44 + i * 2})`; ctx.beginPath(); ctx.roundRect(x - sw / 2, y - sh * 0.55, sw * 0.92, sh, sw * 0.18); ctx.fill(); ctx.fillStyle = `rgba(210,205,190,${0.5 - i * 0.03})`; ctx.fillRect(x - sw * 0.38, y - sh * 0.52, sw * 0.7, sh * 0.12); if (R() < 0.75) { ctx.fillStyle = `rgba(${40 + R() * 40},${30 + R() * 30},${25 + R() * 20},.95)`; ctx.beginPath(); ctx.arc(x - sw * 0.05, y - sh * 0.62, sw * 0.2, 0, TAU); ctx.fill(); } } } }
+  // oxygen masks hanging on their tubes
+  for (let i = 0; i < 26; i++) { const z = 1 / (1 + R() * 5); const side = R() < 0.5; const sx = side ? lerp(w * 0.62, w * 1.0, R()) : lerp(w * 0.42, 0, R()); const [x, y0] = P(sx, h * 0.3, z); const L = h * (0.12 + R() * 0.16) * z; const sway = (R() - 0.5) * 10 * z; ctx.strokeStyle = 'rgba(240,240,230,.7)'; ctx.lineWidth = Math.max(0.6, 1.4 * z); ctx.beginPath(); ctx.moveTo(x, y0); ctx.quadraticCurveTo(x + sway, y0 + L * 0.6, x + sway * 0.6, y0 + L); ctx.stroke(); ctx.fillStyle = '#F4C21A'; ctx.beginPath(); ctx.ellipse(x + sway * 0.6, y0 + L + 5 * z, 7 * z * (w / 400), 9 * z * (w / 400), 0, 0, TAU); ctx.fill(); }
+  // aisle with emergency floor path lighting
+  ctx.fillStyle = '#161412'; poly(ctx, [[w * 0.36, h], [w * 0.68, h], P(w * 0.56, h, 0.1), P(w * 0.48, h, 0.1)], true); ctx.fill();
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; for (let i = 0; i < 18; i++) { const z = 1 / (1 + i * 0.4); for (const xx of [w * 0.38, w * 0.66]) { const [x, y] = P(xx, h * 0.99, z); glow(ctx, x, y, 10 * z * (w / 300), 'rgba(255,170,70,A)', 0.9); } } glow(ctx, vx, vy - h * 0.05, w * 0.3, 'rgba(255,220,170,A)', 0.25); ctx.restore();
+  // a crew member down the aisle
+  const [cx, cy] = P(w * 0.52, h * 0.66, 0.42); ctx.fillStyle = '#0d0c10'; ctx.beginPath(); ctx.roundRect(cx - w * 0.03, cy - h * 0.16, w * 0.06, h * 0.17, 6); ctx.fill(); ctx.beginPath(); ctx.arc(cx, cy - h * 0.18, w * 0.022, 0, TAU); ctx.fill();
+  // motion blur feel + grain
+  ctx.save(); ctx.globalAlpha = 0.18; ctx.drawImage(cv, 3, 1); ctx.restore();
+  vignette(ctx, w, h, 0.6); grain(ctx, w, h, 0.16);
+};
+
+// a city block after the power went out: one building on generator light
+PT.blackout = function (cv, o = {}) {
+  const ctx = cv.getContext('2d'), w = cv.width, h = cv.height; const R = rng(o.seed || 91);
+  const sky = ctx.createLinearGradient(0, 0, 0, h); sky.addColorStop(0, '#05060a'); sky.addColorStop(1, '#10121a'); ctx.fillStyle = sky; ctx.fillRect(0, 0, w, h);
+  for (let i = 0; i < 7; i++) { const x = i * w / 6 - 10, bw = w / 6 + 10, bh = h * (0.25 + R() * 0.3); ctx.fillStyle = '#08090c'; ctx.fillRect(x, h * 0.72 - bh, bw, bh); }
+  const hx = w * 0.56, hy = h * 0.38; ctx.fillStyle = '#121418'; ctx.fillRect(hx - w * 0.16, hy, w * 0.32, h * 0.34);
+  for (let r = 0; r < 7; r++) for (let c = 0; c < 10; c++) { if (R() < 0.45) continue; ctx.fillStyle = `rgba(255,${225 + R() * 30},${180 + R() * 50},${0.45 + R() * 0.5})`; ctx.fillRect(hx - w * 0.145 + c * w * 0.03, hy + h * 0.025 + r * h * 0.042, w * 0.016, h * 0.022); }
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; glow(ctx, hx, hy + h * 0.15, w * 0.4, 'rgba(255,230,190,A)', 0.18); glow(ctx, w * 0.2, h * 0.86, w * 0.1, 'rgba(255,40,40,A)', 0.6); ctx.restore();
+  const rg = ctx.createLinearGradient(0, h * 0.72, 0, h); rg.addColorStop(0, '#0b0c10'); rg.addColorStop(1, '#030304'); ctx.fillStyle = rg; ctx.fillRect(0, h * 0.72, w, h * 0.28);
+  ctx.save(); ctx.globalCompositeOperation = 'lighter'; ctx.globalAlpha = 0.25; for (let y = h * 0.74; y < h; y += 2) { ctx.fillStyle = 'rgba(255,220,170,.5)'; ctx.fillRect(hx - w * 0.08 + Math.sin(y) * 4, y, w * 0.16, 1); } ctx.restore();
+  ctx.strokeStyle = 'rgba(200,210,230,.2)'; ctx.lineWidth = 1; ctx.beginPath(); for (let i = 0; i < 160; i++) { const x = R() * w, y = R() * h; ctx.moveTo(x, y); ctx.lineTo(x - 4, y + 14); } ctx.stroke();
+  vignette(ctx, w, h, 0.55); grain(ctx, w, h, 0.15);
+};
+
+/* ---------- registry: id → draw(canvas, opts); scenes are drawn at t ---------- */
+PT.draw = function (id, cv, o = {}) {
+  if (SCN[id]) { const sc = SCN[id]; const key = id + '|' + cv.width + 'x' + cv.height + '|' + (o.seed || 0) + '|' + (o.skyline ? 1 : 0) + (o.palm ? 1 : 0); PT._bases = PT._bases || new Map(); let B = PT._bases.get(key); if (!B) { B = sc.base(cv.width, cv.height, o); PT._bases.set(key, B); } sc.frame(cv.getContext('2d'), cv.width, cv.height, o.t ?? performance.now() / 1000, o, B); return true; }
+  const f = PT[id]; if (typeof f !== 'function') return false; f(cv, o); return true;
+};
+PT.animated = (id) => !!SCN[id];
diff --git a/mobile/vision/src/js/50-situations.js b/mobile/vision/src/js/50-situations.js
index a1d5086e5..3bbb3b24c 100644
--- a/mobile/vision/src/js/50-situations.js
+++ b/mobile/vision/src/js/50-situations.js
@@ -37,7 +37,8 @@ function dayReplay(lat, lon, localHour = 15.5) {
   while (t > NOW) t -= 86400000; return { at: t, start: t - 3 * 3600000, end: t + 3 * 3600000, replay: true };
 }
 SIT.dayReplay = dayReplay;
-const LAUNCH_T0 = NOW + (2 * 3600 + 14 * 60 + 33) * 1000;
+const LAUNCH_T0 = NOW - (34 * 60 + 12) * 1000;
+GE.LAUNCH_T0 = LAUNCH_T0;
 const KOSHI_T = GE.scenes.FLOOD.startMs;
 const AURORA_T = (() => { const d = new Date(NOW); d.setUTCHours(21, 30, 0, 0); if (d.getTime() < NOW) d.setUTCDate(d.getUTCDate() + 1); return d.getTime(); })();
 
@@ -123,11 +124,11 @@ add({
 });
 add({
   id: 'launch', short: 'Launch · SLC-40', fam: 'orbit', kind: 'launch', section: 'now', live: true, aspect: 1.5, ageS: 300, watchers: 33800,
-  title: 'Rideshare launch from SLC-40 — countdown', place: 'Cape Canaveral, Florida', lat: 28.5618, lon: -80.5772,
+  title: 'Twilight launch from SLC-40 — plume seen along 600 km of coast', place: 'Cape Canaveral, Florida', lat: 28.5618, lon: -80.5772,
   camera: { lat: 28.5585, lon: -80.5825, range: 0.00045, heading: 0.85, tilt: 1.28 }, labels3d: [[28.5618, -80.5772, 'SLC-40 · vehicle on pad', 0.11]], thumbCam: { lat: 28.25, lon: -80.95, range: 0.028, heading: 0.75, tilt: 1.0 }, layers: ['launches', 'flights', 'ais', 'tracks'], source: 'Range schedule (illustrative)',
-  metric: () => [`<span class="num">T−${fmt.dur((LAUNCH_T0 - Date.now()) / 1000)}</span>`, 'Rideshare to SSO · trajectory NE'],
-  metrics: () => [{ v: fmt.dur((LAUNCH_T0 - Date.now()) / 1000), u: '', l: 'Countdown', s: 'Range · 5 min' }, { v: 92, u: '%', l: 'Weather go', s: 'Forecast · 1 h' }, { v: 14, u: '', l: 'Vessels in hazard area', s: 'AIS · 40 s' }],
-  brief: { lede: 'Vehicle is vertical on the pad. The hazard area offshore is still being cleared — 14 vessels remain inside. Trajectory heads northeast along the coast.', series: [{ label: 'Vessels in hazard area', unit: '', data: [41, 39, 36, 33, 31, 28, 24, 21, 19, 17, 15, 14], src: 'AIS · 15 min · 40 s', fmt: (v) => v }], sources: [['Range schedule (illustrative)', '5 min', 'live'], ['AIS', '40 s', 'live']] },
+  metric: () => [`<span class="num">T+${fmt.dur((Date.now() - LAUNCH_T0) / 1000)}</span>`, 'Rideshare to SSO · 2nd stage coasting'],
+  metrics: () => [{ v: fmt.dur((Date.now() - LAUNCH_T0) / 1000), u: '', l: 'Since liftoff', s: 'Range · live' }, { v: 212, u: 'km', l: '2nd stage altitude', s: 'Tracking · 10 s' }, { v: 418, u: '', l: 'Sky captures', s: 'Signed · 4 min' }],
+  brief: { lede: 'The vehicle lifted off just after sunset. Its exhaust climbed into sunlight above the dark ground and spread into a glowing "jellyfish" seen from Georgia to the Keys. The second stage is coasting to its burn; the pad is being safed.', series: [{ label: 'Sky captures per minute', unit: '', data: [0, 2, 14, 61, 120, 96, 70, 44, 30, 22, 15, 11], src: 'Signed bundles · 1 min', fmt: (v) => v }], sources: [['Range schedule (illustrative)', '5 min', 'live'], ['Tracking camera (illustrative)', '10 s', 'live'], ['Signed sky captures', '4 min', 'live']] },
 });
 add({
   id: 'koshi', short: 'Bhote Koshi · 4D', fam: 'haz', kind: 'recon', section: 'recon', live: false, aspect: 1.33, ageS: 53 * 86400, watchers: 12800, thread: 'koshi', d4: true,
@@ -211,6 +212,21 @@ add({
   brief: { lede: 'Two traffic separation lanes, one of the densest anchorages anywhere.', series: [{ label: 'Transits per hour', unit: '', data: walk(24, 80, 4, 0, 61).map(Math.round), src: 'AIS · hourly', fmt: (v) => v }], sources: [['AIS', '40 s', 'live']] },
 });
 
+/* round two: situations behind the new feed cards (lite: camera, layers, brief) */
+const lite = (o) => add({ live: true, aspect: 1.25, section: 'now', watchers: 3000, metric: () => [o.m0 || '', o.m1 || ''], metrics: () => o.ms.map(([v, u, l, sx]) => ({ v, u, l, s: sx })), brief: { lede: o.lede, series: o.series || [], sources: o.sources || [] }, ...o });
+lite({ id: 'dfw', short: 'Squall line · DFW', fam: 'wx', kind: 'storm', title: 'Bowing squall line crossing Dallas–Fort Worth', place: 'Dallas–Fort Worth, Texas', lat: 32.82, lon: -97.0, camera: { lat: 32.62, lon: -97.12, range: 0.05, heading: 0.3, tilt: 0.9 }, layers: ['radar', 'lightning', 'flights', 'traffic'], source: 'Radar mosaic', watchers: 26100, ageS: 90,
+  ms: [[62, 'dBZ', 'Peak reflectivity', 'Radar · 2 min'], [72, 'km/h', 'Line motion', 'Derived'], [1, '', 'Tornado warning', 'Warning feed · 4 min']], lede: 'A bowing line is racing east at 72 km/h. The apex is producing 100 km/h gusts and a brief tornado warning covers Arlington. Departures at DFW are on a ground stop.', series: [{ label: 'Peak dBZ', unit: '', data: [38, 41, 47, 52, 55, 58, 61, 62], src: 'Radar mosaic · 5 min', fmt: (v) => v }], sources: [['Radar mosaic (illustrative)', '2 min', 'live'], ['Lightning network', '30 s', 'live']] });
+lite({ id: 'gulf', short: 'Lightning · Gulf', fam: 'wx', kind: 'lightning', title: '4,812 lightning strikes in the last hour over the Gulf', place: 'Gulf of Mexico', lat: 26.5, lon: -89, camera: { lat: 24.5, lon: -89.5, range: 0.3, heading: 0, tilt: 0.5 }, layers: ['lightning', 'clouds', 'flights', 'ais'], source: 'Lightning network', watchers: 4100, ageS: 60,
+  ms: [['4,812', '', 'Strikes / h', 'Network · 1 min'], [5, '', 'Active cells', 'Derived'], [31, '', 'Flights deviating', 'ADS-B · 2 min']], lede: 'Five clusters of deep convection are firing over warm Gulf water. Airliners are deviating around the two strongest cells.', sources: [['Lightning network (illustrative)', '1 min', 'live']] });
+lite({ id: 'shibuya', short: 'Shibuya crossing', fam: 'eyes', kind: 'eye', title: 'Shibuya crossing in the rain — public camera', place: 'Shibuya, Tokyo', lat: 35.6595, lon: 139.7005, camera: { lat: 35.6575, lon: 139.6985, range: 0.0009, heading: 0.6, tilt: 1.1 }, layers: ['cctv', 'transit', 'traffic', 'venues'], source: 'Public camera', watchers: 9400, ageS: 3,
+  ms: [['~2,400', '', 'People per cycle', 'Camera count · 1 min'], [12, 'mm/h', 'Rain', 'Gauge · 10 min'], [46, 's', 'Signal cycle', 'Observed']], lede: 'A public street camera over the scramble. Counts are estimated on-device; no faces are kept.', sources: [['Public street camera (illustrative)', 'live', 'live']] });
+lite({ id: 'derby', short: 'Derby egress', fam: 'ground', kind: 'crowd', title: 'Derby egress: crowd density building at Gate C', place: 'Avellaneda, Buenos Aires', lat: -34.6705, lon: -58.3685, camera: { lat: -34.6735, lon: -58.3715, range: 0.0012, heading: 0.4, tilt: 1.0 }, layers: ['venues', 'transit', 'traffic', 'cctv'], source: 'Crowd sensing (illustrative)', watchers: 11800, ageS: 40,
+  ms: [[4.6, 'p/m²', 'Peak density', 'Derived · 30 s'], ['41k', '', 'Leaving', 'Estimate'], [3, '', 'Gates open', 'Venue feed']], lede: 'Fans are leaving after the final whistle. Density outside Gate C has passed 4 people per square metre while Gates A and D are flowing freely. Stewards are being redirected.', series: [{ label: 'Density at Gate C', unit: 'p/m²', data: [1.1, 1.4, 2.0, 2.8, 3.5, 4.1, 4.6], src: 'Derived · 1 min', fmt: (v) => v.toFixed(1) }], sources: [['Crowd sensing (illustrative)', '30 s', 'live'], ['Signed captures', '3 min', 'live']] });
+lite({ id: 'sakurajima', short: 'Sakurajima cam', fam: 'haz', kind: 'volcano', title: 'Sakurajima ash column to 3.2 km — webcam', place: 'Kagoshima Bay, Japan', lat: 31.58, lon: 130.66, camera: { lat: 31.52, lon: 130.6, range: 0.012, heading: 0.5, tilt: 1.15 }, layers: ['volcanoes', 'flights', 'wind', 'cctv'], source: 'Volcano webcam', watchers: 5300, ageS: 120,
+  ms: [[3.2, 'km', 'Ash column', 'Webcam · 2 min'], ['ESE', '', 'Drift', 'Wind model'], [0, '', 'Flights affected', 'ADS-B']], lede: 'A routine but tall explosion. Ash is drifting away from the city; the airport is open.', sources: [['Volcano webcam (illustrative)', '2 min', 'live'], ['Wind model', '1 h', 'live']] });
+lite({ id: 'lakefront', short: 'Lake Michigan gale', fam: 'wx', kind: 'gale', title: 'Gale on Lake Michigan — waves over the lakefront trail', place: 'Chicago lakefront', lat: 41.866, lon: -87.607, camera: { lat: 41.62, lon: -87.42, range: 0.035, heading: -0.35, tilt: 1.0 }, layers: ['cctv', 'signed', 'traffic'], source: 'Buoy + signed captures', watchers: 1900, ageS: 300, section: 'near',
+  ms: [[3.4, 'm', 'Wave height', 'Buoy · 10 min'], [74, 'km/h', 'Gusts', 'Station · 5 min'], [2, '', 'Trail closures', 'City feed']], lede: 'North-northeast gales are piling waves onto the lakefront. The trail is closed between two harbours.', sources: [['Lake buoy (illustrative)', '10 min', 'live'], ['Signed captures', 'live', 'live']] });
+
 for (const s of S) if (s.time && s.time.replay) { s.live = false; s.replayLabel = 'Today ' + new Date(s.time.at).toLocaleTimeString('en-US', { hour: 'numeric', minute: '2-digit', timeZone: 'UTC' }) + ' UTC'; }
 SIT.list = S;
 SIT.byId = Object.fromEntries(S.map((s) => [s.id, s]));
@@ -220,6 +236,7 @@ SIT.sections = [
 // dynamic cameras
 SIT.cameraFor = function (s) {
   if (s.id === 'starlink') { const g = GE.world.sun.gmst; const p = GE.satAt(GE.SATS.find((x) => x.kind === 5), GE.world.t, g); const [la, lo] = geo.ll(p); return { lat: la - 6, lon: lo - 8, range: 0.32, heading: 0.6, tilt: 0.85 }; }
+  if (s.id === 'squawk' && GE.feed && GE.feed._sq) return s.camera;
   if (s.id === 'squawk') { const f = GE.FLIGHTS[GE.world.squawks[0]]; const p = GE.flightAt(f, GE.world.t) || { lat: 50, lon: -30 }; return { lat: p.lat - 4, lon: p.lon - 3, range: 0.3, heading: 0.3, tilt: 0.75 }; }
   if (s.id === 'iss') { const p = GE.satAt(GE.ISS, GE.world.t, GE.world.sun.gmst); const [la, lo] = geo.ll(p); return { lat: la - 9, lon: lo - 4, range: 0.48, heading: 0.35, tilt: 0.78 }; }
   return s.camera;
diff --git a/mobile/vision/src/js/54-rooms.js b/mobile/vision/src/js/54-rooms.js
new file mode 100644
index 000000000..1b18f29b2
--- /dev/null
+++ b/mobile/vision/src/js/54-rooms.js
@@ -0,0 +1,140 @@
+/* Rooms — every situation has one. Structured posts (Witness / Context / Question / Correction /
+   Prediction) anchored in place and time, badges earned from evidence, community notes shown only when
+   raters who usually disagree both find them helpful, and a Known / Disputed / Unknown synthesis whose
+   every line cites a post or an observation. All people, posts and claims are fictional. */
+const RM = (GE.rooms = { byId: {} });
+const MIN_ = 60000, HR2 = 3600000;
+RM.KINDS = {
+  witness: { name: 'Witness', icon: 'eye', tone: 'gold', hint: 'I saw or recorded this' },
+  context: { name: 'Context', icon: 'layers', tone: 'sky', hint: 'Background, a map, a source' },
+  question: { name: 'Question', icon: 'bubble', tone: 'white', hint: 'Floats to the top until answered' },
+  correction: { name: 'Correction', icon: 'flag', tone: 'amber', hint: 'Something here is wrong' },
+  prediction: { name: 'Prediction', icon: 'clock', tone: 'orbit', hint: 'What happens next — scored later' },
+};
+const P0 = GE.PEOPLE;
+const kmBetween = (a, b, c, d) => geo.dist(a, b, c, d) * EARTH_KM;
+RM.kmBetween = kmBetween;
+
+/* ---------- room content ---------- */
+const CY = GE.CYCLONE.at(0);
+const ROOMS = {
+  cyclone: {
+    watching: 3204, rate: 4,
+    src: { O1: 'Geostationary IR mosaic · 01:40Z', O2: 'Advisory + 14 ensemble tracks · 3 h', O3: 'AIS vessel positions · 40 s', S1: 'Sealed live stream, 6 segments · @nadia_basco' },
+    posts: [
+      { id: 'cy1', kind: 'witness', by: 'nadia', ago: 4, live: true, text: 'Waves are coming over the seawall by the port every 30–40 seconds. The road behind it is ankle-deep. The wall itself is intact from what I can see — I\'m 200 m up the slope.', place: { lat: 20.4485, lon: 121.9705, label: 'Basco seawall' }, att: { paint: 'seawall', o: { palm: true, handheld: true, noOSD: true, seed: 52 }, tier: 'sealed-live', segs: 6, distKm: 0.2 }, reacts: { eye: 1240, heart: 212, alert: 48 }, replies: 31 },
+      { id: 'cy2', kind: 'question', by: 'rafa', ago: 6, text: 'Is the Magapit bridge into Aparri still open? Nobody here knows and the power is out.', place: { lat: 18.12, lon: 121.65, label: 'Magapit bridge' }, reacts: { eye: 96 }, replies: 2 },
+      { id: 'cy3', kind: 'context', by: 'lin', ago: 11, text: 'An eyewall replacement looks likely in the next 12 h. Expect the peak wind number to drop while the wind field gets wider. For Batanes that is not good news, so don\'t read a lower number as "weakening".', cites: ['O1', 'O2'], reacts: { heart: 340, eye: 520 }, replies: 18 },
+      { id: 'cy4', kind: 'witness', by: 'repost', ago: 9, text: 'VIDEO: Basco port pier has COLLAPSED!! Share before it\'s deleted', att: { paint: 'harbour', o: { seed: 19, cam: 'CAM 03', place: 'PORT' }, tier: 'unverified', distKm: null }, reacts: { alert: 860 }, replies: 77,
+        note: { text: 'This clip is from a 2019 storm at a different port. Reverse-image search finds 3 earlier copies. The pier is visible and intact in tonight\'s sealed live stream from Basco [P1].', helpfulA: 0.81, helpfulB: 0.74, ratersA: 118, ratersB: 94, cites: ['P1'] } },
+      { id: 'cy5', kind: 'prediction', by: 'joon', ago: 14, text: 'Kaohsiung will close the port to outbound traffic by 06:00 local. 11 ships have already left the anchorage and are heading south of the track.', place: { lat: 22.61, lon: 120.27, label: 'Kaohsiung pier 70' }, att: { paint: 'harbour', o: { seed: 8, cam: 'HBR-07', place: 'KAOHSIUNG PIER 70' }, tier: 'eye', distKm: null }, cites: ['O3'], reacts: { eye: 210, heart: 41 }, replies: 6, resolves: '06:00 local' },
+      { id: 'cy6', kind: 'witness', by: 'rafa', ago: 22, text: 'Power out across Aparri centro since 01:10. The hospital is on generators. Rain is sideways.', place: { lat: 18.357, lon: 121.637, label: 'Aparri centro' }, att: { paint: 'blackout', o: { seed: 91 }, tier: 'sealed', distKm: 0.4 }, reacts: { heart: 190, eye: 300 }, replies: 9 },
+      { id: 'cy7', kind: 'correction', by: 'ais', ago: 18, text: 'Correction to an earlier post: there are 2 ships holding off Batanes, not 6. The other 4 are at anchor in the lee of Sabtang and are fine.', cites: ['O3'], place: { lat: 20.34, lon: 121.85, label: 'Sabtang lee' }, reacts: { heart: 88 }, replies: 3 },
+    ],
+    synth: {
+      known: [['Waves are overtopping the Basco seawall near the port; the wall itself is intact as of a few minutes ago.', ['P1', 'S1']], ['Eyewall cloud tops are colder than −80 °C with frequent lightning.', ['O1']], ['Aparri centro has lost power; the hospital is on generators.', ['P6']]],
+      disputed: [['A viral "collapsed pier" video — a community note shows it predates this storm.', ['P4', 'N1']], ['Whether Halcyon is weakening: peak wind estimates dip while the wind field broadens.', ['P3', 'O2']]],
+      unknown: [['Whether the Magapit bridge into Aparri is open — asked 6 min ago, no evidence yet.', ['P2']], ['Landfall point: guidance still spreads ±150 km at 36 h.', ['O2']]],
+    },
+  },
+  quake: {
+    watching: 1880, rate: 2,
+    src: { O1: 'Seismic catalog · revised 12 min ago', O2: 'Tide gauges · 3 min', O3: 'Rail status boards · 9 min' },
+    posts: [
+      { id: 'qk1', kind: 'question', by: 'aiko', ago: 48, text: 'Are trains running north of Sendai yet? Stuck at the station with my kids.', place: { lat: 38.26, lon: 140.88, label: 'Sendai station' }, answered: 'qk2', reacts: { eye: 140 }, replies: 5 },
+      { id: 'qk2', kind: 'context', by: 'tetsu', ago: 41, text: 'Northbound service resumed at 02:41 after track inspection. Expect 20–30 min delays through Fukushima.', cites: ['O3'], reacts: { heart: 220 }, replies: 4 },
+      { id: 'qk3', kind: 'witness', by: 'aiko', ago: 300, text: 'Long rolling shake, maybe 40 seconds. Shelves came down in the store and everyone came out onto the street. Nobody hurt here.', place: { lat: 38.262, lon: 140.871, label: 'Aoba-ku' }, att: { paint: 'crossing', o: { seed: 33, cam: 'PHONE', rec: false }, tier: 'sealed', distKm: 162 }, reacts: { heart: 410, eye: 700 }, replies: 22 },
+      { id: 'qk4', kind: 'correction', by: 'geo', ago: 280, text: 'The depth is 32 km in the revised solution, not the 10 km in early reposts. That matters for how far the shaking reached.', cites: ['O1'], reacts: { heart: 160 }, replies: 7 },
+      { id: 'qk5', kind: 'witness', by: 'repost', ago: 310, text: 'TSUNAMI 3 METERS hitting the coast right now!!!', reacts: { alert: 1900 }, replies: 140,
+        note: { text: 'Tide gauges along the coast recorded at most 20 cm [O2]. No tsunami warning was issued. The video attached to the original claim is from 2011.', helpfulA: 0.88, helpfulB: 0.79, ratersA: 302, ratersB: 241, cites: ['O2'] } },
+      { id: 'qk6', kind: 'prediction', by: 'geo', ago: 200, text: 'Chance of an M5+ aftershock in the next 72 h is about 1 in 4 for a sequence like this. Not a reason to panic, a reason to secure shelves.', cites: ['O1'], reacts: { heart: 98 }, replies: 11, resolves: 'in 72 h' },
+    ],
+    synth: {
+      known: [['An M 6.4 thrust event at 32 km depth off the Honshu coast.', ['O1', 'P4']], ['Tide gauges recorded at most 20 cm; no tsunami.', ['O2', 'N1']], ['Northbound trains resumed at 02:41 with delays.', ['P2', 'O3']]],
+      disputed: [['Early reposts claimed a 3 m tsunami — rated false by raters across perspectives.', ['P5', 'N1']]],
+      unknown: [['Damage inland of Fukushima — the only sealed capture so far is from Sendai.', ['P3']], ['Whether a larger aftershock follows (≈ 1 in 4 within 72 h).', ['P6']]],
+    },
+  },
+  squawk: {
+    watching: 2410, rate: 3,
+    src: { O1: 'ADS-B · 1 Hz', O2: 'Diversion airport board · 2 min' },
+    posts: [
+      { id: 'sq1', kind: 'witness', by: 'seat', ago: 7, text: 'On board. Masks dropped about 20 minutes ago. Crew are calm, we\'re descending and they said we\'re landing soon. Everyone is OK.', att: { paint: 'cabin', o: { seed: 81 }, tier: 'sealed', distKm: 0 }, reacts: { heart: 1820, eye: 2100 }, replies: 64 },
+      { id: 'sq2', kind: 'context', by: 'tomas', ago: 12, text: 'Squawk 7700, a turn toward the nearest long runway and a steady ~2,400 ft/min descent to FL100 is what a pressurisation problem looks like. It is a well-practised procedure.', cites: ['O1'], reacts: { heart: 960 }, replies: 21 },
+      { id: 'sq3', kind: 'question', by: 'sky', ago: 5, text: 'Does anyone know which runway they\'ll use? Wind there is strong from the east.', reacts: { eye: 44 }, replies: 1 },
+      { id: 'sq4', kind: 'prediction', by: 'tomas', ago: 9, text: 'They\'ll be on the ground in about 34 minutes.', cites: ['O1', 'O2'], reacts: { heart: 120 }, replies: 2, resolves: 'at landing' },
+    ],
+    synth: {
+      known: [['The aircraft squawked 7700, turned toward the diversion airport and is descending.', ['O1']], ['A passenger on board reports masks deployed and the crew calm.', ['P1']]],
+      disputed: [],
+      unknown: [['The cause — the descent profile fits a pressurisation problem, unconfirmed.', ['P2']], ['Landing runway and time (est. ~34 min).', ['P3', 'P4']]],
+    },
+  },
+  fires: {
+    watching: 1460, rate: 2,
+    src: { O1: 'VIIRS 375 m hotspots · 38 min', O2: 'Wind model · 1 h' },
+    posts: [
+      { id: 'fi1', kind: 'witness', by: 'ines', ago: 26, text: 'The ridge above the N2 is burning along about two kilometres. Ash is falling on the road. Traffic is still moving south.', place: { lat: 40.13, lon: -8.05, label: 'N2 at the ridge' }, att: { paint: 'firewit', o: { seed: 71 }, tier: 'sealed', distKm: 1.8 }, reacts: { heart: 260, eye: 900 }, replies: 18 },
+      { id: 'fi2', kind: 'context', by: 'bomb', ago: 20, text: 'Front is moving west at about 1.2 km/h. The N2 will close between the two junctions within the hour. Please don\'t stop on the road to film.', cites: ['O1', 'O2'], reacts: { heart: 700 }, replies: 12 },
+      { id: 'fi3', kind: 'question', by: 'ines', ago: 8, text: 'Is the IC8 open toward Coimbra?', reacts: { eye: 60 }, replies: 0 },
+    ],
+    synth: { known: [['A fire front about 2 km long is burning above the N2, moving west ~1.2 km/h.', ['P1', 'P2', 'O1']]], disputed: [], unknown: [['Whether the IC8 toward Coimbra is open.', ['P3']]] },
+  },
+};
+// light rooms for the rest: a context post from the brief + an open question
+function liteRoom(s) {
+  const by = ['kora', 'sky', 'geo', 'ais', 'hydro'][s.id.length % 5];
+  return { watching: Math.round((s.watchers || 2000) * 0.06) + 40, rate: 1, src: Object.fromEntries((s.brief?.sources || []).slice(0, 3).map(([n, a], i) => ['O' + (i + 1), `${n} · ${a}`])),
+    posts: [{ id: s.id + '-1', kind: 'context', by, ago: 12, text: s.brief?.lede || s.title, cites: ['O1'], reacts: { heart: 40, eye: 120 }, replies: 3 }, { id: s.id + '-2', kind: 'question', by: 'kora', ago: 5, text: 'Anyone close enough to send a sealed capture?', reacts: { eye: 20 }, replies: 0 }],
+    synth: { known: [[s.brief?.lede?.split('. ')[0] + '.', ['O1', 'P1']]], disputed: [], unknown: [['No witness captures yet.', ['P2']]] } };
+}
+
+/* ---------- derived: badges, evidence score, ordering ---------- */
+RM.badges = function (room, p) {
+  const s = GE.SIT.byId[room.sit]; const who = P0[p.by] || {}; const out = [];
+  const sealed = p.att && /^sealed/.test(p.att.tier);
+  if (sealed && p.att.distKm != null && p.att.distKm <= 5) out.push(['there', `Was there · ${p.att.distKm < 1 ? Math.round(p.att.distKm * 1000) + ' m' : p.att.distKm.toFixed(1) + ' km'}`]);
+  if (sealed) out.push(['sealed', p.att.tier === 'sealed-live' ? 'Sealed live' : 'Sealed']);
+  if (who.home && s && kmBetween(who.home[0], who.home[1], p.place?.lat ?? s.lat, p.place?.lon ?? s.lon) < 120) out.push(['local', 'Local']);
+  if (who.domain) out.push(['domain', who.domain]);
+  if (p.att && p.att.tier === 'unverified') out.push(['unv', 'Unverified upload']);
+  if (p.by === 'you' && GE.ME && s && kmBetween(GE.ME.lat, GE.ME.lon, s.lat, s.lon) < 120 && !out.some((b) => b[0] === 'local')) out.push(['local', 'Local']);
+  return out;
+};
+RM.score = function (room, p) { let sc = 0; for (const [k] of RM.badges(room, p)) sc += { there: 4, sealed: 3, domain: 2, local: 1, unv: -2 }[k] || 0; if (p.att?.tier === 'eye') sc += 1; if (p.note) sc -= 3; return sc; };
+RM.ordered = function (room, mode = 'evidence') {
+  const ps = room.posts.slice();
+  const openQ = (p) => p.kind === 'question' && !p.answered;
+  if (mode === 'latest') return ps.sort((a, b) => b.at - a.at);
+  if (mode === 'questions') return ps.filter((p) => p.kind === 'question').sort((a, b) => (openQ(b) - openQ(a)) || b.at - a.at);
+  return ps.sort((a, b) => (openQ(b) - openQ(a)) || RM.score(room, b) - RM.score(room, a) || b.at - a.at);
+};
+RM.pid = (room, p) => 'P' + (room.posts.indexOf(p) + 1);
+RM.byPid = (room, pid) => room.posts[+pid.slice(1) - 1];
+
+/* ---------- ledger per room (real SHA-256 chain) ---------- */
+RM.append = async function (room, type, actor, payload) {
+  const L = room.ledger; const prev = L.length ? L[L.length - 1].hash : '0'.repeat(64);
+  const e = { i: L.length, ts: Date.now(), type, actor, payload }; e.digest = await sha256(canon(payload)); e.prev = prev; e.hash = await sha256(canon({ i: e.i, ts: e.ts, type: e.type, actor: e.actor, digest: e.digest, prev })); L.push(e); return e;
+};
+
+/* ---------- build ---------- */
+RM.get = function (sitId) {
+  if (RM.byId[sitId]) return RM.byId[sitId];
+  const s = GE.SIT.byId[sitId]; if (!s) return null;
+  const R0 = ROOMS[sitId] || liteRoom(s);
+  const room = { sit: sitId, ...R0, ledger: [], posts: R0.posts.map((p) => ({ ...p, at: NOW - (p.ago || 1) * MIN_ })) };
+  for (const p of room.posts) if (p.att && p.att.paint === 'seawall' && p.live) p.att.o.cam = '@' + P0[p.by].h;
+  RM.byId[sitId] = room;
+  (async () => { for (const p of room.posts) await RM.append(room, 'post.' + p.kind, P0[p.by]?.h || p.by, { id: p.id, text: p.text, att: p.att ? { tier: p.att.tier } : null, place: p.place || null }); })();
+  return room;
+};
+RM.count = (sitId) => { const r = ROOMS[sitId]; return r ? r.posts.length : 2; };
+RM.watching = (sitId) => (RM.byId[sitId]?.watching) ?? ROOMS[sitId]?.watching ?? Math.round((GE.SIT.byId[sitId]?.watchers || 2000) * 0.06) + 40;
+RM.sealedCount = (sitId) => { const r = RM.byId[sitId] || ROOMS[sitId]; return r ? r.posts.filter((p) => p.att && /^sealed/.test(p.att.tier)).length : 0; };
+RM.topClaim = function (sitId) {
+  const r = ROOMS[sitId]; if (!r) return null;
+  const open = r.posts.find((p) => p.kind === 'question' && !p.answered);
+  const k = r.synth.known[0], d = r.synth.disputed[0];
+  return { q: open?.text, known: k?.[0], disputed: d?.[0], sealed: r.posts.filter((p) => p.att && /^sealed/.test(p.att.tier)).length };
+};
diff --git a/mobile/vision/src/js/55-feed.js b/mobile/vision/src/js/55-feed.js
new file mode 100644
index 000000000..ab7f9cff6
--- /dev/null
+++ b/mobile/vision/src/js/55-feed.js
@@ -0,0 +1,115 @@
+/* Feed model — mixed archetypes across the four altitude bands, ordered for diversity.
+   Bands answer "where is the sensor": Orbit, Sky, Ground, and Inside (a person). */
+const FD = (GE.feed = {});
+GE.BANDS = {
+  orbit: { name: 'Orbit', c: '#B79CFF', alt: '400–36,000 km', sensor: 'satellites · ISS · launches' },
+  sky: { name: 'Sky', c: '#8CD4FF', alt: '0–15 km', sensor: 'aircraft · radar · lightning' },
+  ground: { name: 'Ground', c: '#FFA53D', alt: '0 m', sensor: 'cameras · seismometers · crowds' },
+  inside: { name: 'Inside', c: '#F2CF7A', alt: 'you', sensor: 'witnesses · broadcasts · rooms' },
+};
+GE.ARCH = { sensor: 'Sensor', eye: 'Eye', track: 'Track', number: 'Number', witness: 'Witness', room: 'Room' };
+const MIN3 = 60000;
+FD.fmtDist = (km) => (km < 1 ? Math.round(km * 1000) + ' m' : km < 100 ? km.toFixed(km < 10 ? 1 : 0) + ' km' : fmt.n(Math.round(km)) + ' km');
+FD.distFromMe = (lat, lon) => geo.dist(GE.ME.lat, GE.ME.lon, lat, lon) * EARTH_KM;
+const llz = (lat, lon) => `${Math.abs(lat).toFixed(2)}${lat >= 0 ? 'N' : 'S'} ${Math.abs(lon).toFixed(2)}${lon >= 0 ? 'E' : 'W'}`;
+const hmsZ = () => { const d = new Date(); return `${String(d.getUTCHours()).padStart(2, '0')}:${String(d.getUTCMinutes()).padStart(2, '0')}:${String(d.getUTCSeconds()).padStart(2, '0')}Z`; };
+FD.hmsZ = hmsZ; FD.llz = llz;
+
+/* the diverting flight, computed from the synthetic traffic so card, room and globe agree */
+FD.squawkTrack = function () {
+  if (FD._sq) return FD._sq;
+  const f = GE.FLIGHTS[GE.world.squawks[0]]; const pts = [];
+  for (let k = -90; k <= 0; k += 3) { const p = GE.flightAt(f, GE.world.t + k * 60); if (p) pts.push([p.lat, p.lon]); }
+  let ok = pts.length > 12;
+  if (!ok) { pts.length = 0; for (let k = 0; k <= 30; k++) pts.push(k < 18 ? [55 + k * 0.12, -10 - k * 0.9] : [57.1 + (k - 18) * 0.25, -26.2 - (k - 18) * 0.35]); }
+  const cur = pts[pts.length - 1]; let div = null, bd = 1e9;
+  for (const a of GE.AP) { if (a.w < 8) continue; const d = geo.dist(cur[0], cur[1], a.lat, a.lon); if (d < bd && d > 0.02) { bd = d; div = a; } }
+  if (!ok) div = GE.apByIata.RKV || div;
+  // bend the last third toward the diversion field
+  const k0 = Math.floor(pts.length * 0.62); const bend = pts.slice(0, k0 + 1); const a = pts[k0];
+  for (let i = 1; i <= pts.length - 1 - k0; i++) { const t = (i / (pts.length - 1 - k0)) * 0.45; bend.push([lerp(a[0], div.lat, t), lerp(a[1], div.lon, t)]); }
+  const alt = [37000, 37000, 36000, 31000, 27000, 24000];
+  FD._sq = { pts: bend, sqAt: k0, div: { lat: div.lat, lon: div.lon, iata: div.iata, city: div.city }, alt, cur: bend[bend.length - 1] };
+  // put the same track on the globe: white before the declaration, red after, the aircraft at its head
+  const W = GE.world; const C2 = FD._sq.cur; const alt3 = (i) => 10.5 - Math.max(0, i - k0) * 0.25;
+  W.extraLines.push({ pts: bend.slice(0, k0 + 1).map(([la, lo], i) => geo.vec(la, lo, alt3(i))), col: [0.85, 0.9, 1, 0.55] }, { pts: bend.slice(k0).map(([la, lo], i) => geo.vec(la, lo, alt3(i + k0))), col: [1, 0.25, 0.2, 0.95] }, { pts: [geo.vec(C2[0], C2[1], 7), geo.vec(div.lat, div.lon, 0)], col: [1, 0.45, 0.4, 0.5], dashed: 1 });
+  (W.extraSprites = W.extraSprites || []).push({ v: geo.vec(C2[0], C2[1], 7), col: [1, 0.23, 0.19, 1], size: 30 });
+  const s = GE.SIT.byId.squawk; if (s) { s.lat = C2[0]; s.lon = C2[1]; s.camera = { lat: C2[0] - 4, lon: C2[1] - 3, range: 0.14, heading: 0.35, tilt: 0.85 }; }
+  return FD._sq;
+};
+
+/* ---------- items ---------- */
+FD.items = function () {
+  if (FD._items) return FD._items;
+  const C = GE.CYCLONE.at(0); const sq = FD.squawkTrack(); const iss = GE.SIT.issPass(Date.now());
+  const it = [
+    { id: 'basco', arch: 'witness', band: 'inside', sit: 'cyclone', post: 'cy1', wide: true, prio: 100, live: true, by: 'nadia', paint: 'seawall', po: { palm: true, handheld: true, noOSD: true, seed: 52 }, aspect: 0.62,
+      title: 'Waves over the Basco seawall — live from the port', place: 'Basco, Batanes', lat: 20.4485, lon: 121.9705, ago: 14, cam: { lat: 18.6, lon: 123.4, range: 0.18, heading: -0.55, tilt: 0.62 },
+      tele: () => `WITNESS · SEALED LIVE · ±4 M · ${fmt.n(Math.round(RM.kmBetween(20.4485, 121.9705, C.lat, C.lon)))} KM FROM EYE` },
+    { id: 'ir', arch: 'sensor', band: 'orbit', sit: 'cyclone', prio: 95, paint: 'ir', aspect: 1.25, title: 'Typhoon Halcyon: −83 °C cloud tops and lightning in the eyewall', place: 'Philippine Sea', lat: C.lat, lon: C.lon, ago: 2,
+      tele: () => `ORBIT · GEO IR · 35,786 KM · ${llz(C.lat, C.lon)}` },
+    { id: 'cabin', arch: 'witness', band: 'inside', sit: 'squawk', post: 'sq1', prio: 92, by: 'seat', paint: 'cabin', aspect: 1.3, title: '“Masks dropped. Crew calm. We’re descending.” — on board the 7700', place: 'Over the North Atlantic', lat: sq.cur[0], lon: sq.cur[1], ago: 7,
+      tele: () => 'WITNESS · SEALED · ON BOARD · FL240' },
+    { id: 'harbour', arch: 'eye', band: 'ground', sit: 'cyclone', post: 'cy5', prio: 90, live: true, paint: 'harbour', po: { seed: 8, cam: 'HBR-07', place: 'KAOHSIUNG · PIER 70' }, aspect: 1.0, title: 'Kaohsiung harbour cam: ships leave ahead of Halcyon', place: 'Kaohsiung, Taiwan', lat: 22.61, lon: 120.27, ago: 0, cam: { lat: 21.2, lon: 121.6, range: 0.2, heading: -0.7, tilt: 0.6 },
+      tele: () => `GROUND · CAM HBR-07 · ${llz(22.61, 120.27)} · ${hmsZ()}` },
+    { id: 'squawk', arch: 'track', band: 'sky', sit: 'squawk', prio: 89, live: true, paint: 'track', po: { track: sq }, aspect: 1.15, title: `Squawk 7700 — diverting to ${sq.div.iata} ${sq.div.city ? '(' + sq.div.city + ')' : ''}`, place: 'Over the North Atlantic', lat: sq.cur[0], lon: sq.cur[1], ago: 3,
+      readout: 'SQ 7700 · FL240 ↓', tele: () => 'SKY · ADS-B · 2,400 FPM ↓ · 412 KT', cta: ['airplane', 'Follow the track'] },
+    { id: 'room-cy', arch: 'room', band: 'inside', sit: 'cyclone', prio: 88, wide: true, title: 'Typhoon Halcyon', place: 'Batanes · Babuyan · Luzon Strait', lat: 20.45, lon: 121.97, ago: 1, ev: [['seawall', { palm: true, noOSD: true, seed: 52 }], ['harbour', { seed: 8, cam: 'HBR-07' }], ['blackout', { seed: 91 }], ['ir', {}]] },
+    { id: 'radar', arch: 'sensor', band: 'sky', sit: 'dfw', prio: 86, paint: 'radar', aspect: 1.2, title: 'Bowing squall line crossing Dallas–Fort Worth — tornado warning', place: 'Dallas–Fort Worth', lat: 32.82, lon: -97.0, ago: 2,
+      tele: () => 'SKY · RADAR 0.5° · 62 DBZ · 72 KM/H E' },
+    { id: 'crossing', arch: 'eye', band: 'ground', sit: 'shibuya', prio: 84, live: true, paint: 'crossing', po: { seed: 31, cam: 'CAM 0412', place: 'SHIBUYA SCRAMBLE' }, aspect: 1.25, title: 'Shibuya crossing in the rain: ~2,400 people every cycle', place: 'Shibuya, Tokyo', lat: 35.6595, lon: 139.7005, ago: 0,
+      tele: () => `GROUND · CAM 0412 · ${llz(35.6595, 139.7005)} · ${hmsZ()}` },
+    { id: 'shake', arch: 'sensor', band: 'ground', sit: 'quake', prio: 83, paint: 'shake', aspect: 1.15, title: 'M 6.4 off Honshu: strongest shaking on the Fukushima coast', place: 'Off eastern Honshu', lat: GE.BIGQ.lat, lon: GE.BIGQ.lon, ago: 324,
+      tele: () => 'GROUND · 46 STATIONS · MMI VI · 32 KM DEEP' },
+    { id: 'firesat', arch: 'sensor', band: 'orbit', sit: 'fires', prio: 80, paint: 'firesat', aspect: 1.1, title: 'Central Portugal: a 60 km smoke plume drifts toward the coast', place: 'Pampilhosa da Serra', lat: 40.05, lon: -7.95, ago: 38,
+      tele: () => 'ORBIT · 375 M · FRP 840 MW · WIND ESE 31' },
+    { id: 'isscam', arch: 'eye', band: 'orbit', sit: 'iss', prio: 79, live: true, paint: 'isscam', aspect: 1.3, title: 'From the station’s external camera: the Nile at night', place: '418 km over Egypt', lat: 27.1, lon: 31.2, ago: 0,
+      tele: () => 'ORBIT · ISS · 418 KM · 7.66 KM/S · 27.1N 31.2E' },
+    { id: 'firewit', arch: 'witness', band: 'inside', sit: 'fires', post: 'fi1', prio: 78, by: 'ines', paint: 'firewit', aspect: 1.25, title: 'The ridge above the N2 is burning — 1.8 km from the front', place: 'N2, central Portugal', lat: 40.13, lon: -8.05, ago: 26,
+      tele: () => 'WITNESS · SEALED · ±6 M · 1.8 KM FROM FRONT' },
+    { id: 'lightning', arch: 'number', band: 'sky', sit: 'gulf', prio: 76, paint: 'strikes', aspect: 1.05, title: 'Lightning over the Gulf of Mexico', place: 'Gulf of Mexico', lat: 26.5, lon: -89, ago: 1,
+      big: '4,812', unit: 'strikes', label: 'in the last hour over the Gulf', spark: [1200, 1500, 1900, 2600, 3100, 3800, 4300, 4812], tele: () => 'SKY · LIGHTNING NETWORK · 5 CELLS' },
+    { id: 'stadium', arch: 'sensor', band: 'ground', sit: 'derby', prio: 75, live: true, paint: 'stadium', aspect: 1.1, title: 'Derby egress: 4.6 people/m² building at Gate C', place: 'Avellaneda, Buenos Aires', lat: -34.6705, lon: -58.3685, ago: 1,
+      tele: () => 'GROUND · CROWD SENSING · GATE C · 4.6 P/M²' },
+    { id: 'aurora', arch: 'witness', band: 'inside', sit: 'aurora', prio: 74, by: 'ola', paint: 'aurora', aspect: 1.2, title: 'Corona overhead in Tromsø, sealed 18 minutes ago', place: 'Tromsø, Norway', lat: 69.65, lon: 18.96, ago: 18,
+      tele: () => 'WITNESS · SEALED · ±5 M · KP 6' },
+    { id: 'skychart', arch: 'track', band: 'orbit', sit: 'iss', prio: 72, paint: 'skychart', po: { at: iss.start, max: Math.round(iss.max) }, aspect: 1.0, title: `The ISS crosses your sky at ${fmt.hm(iss.maxAt)} UTC`, place: `Over ${GE.ME.name}`, lat: GE.ME.lat, lon: GE.ME.lon, ago: 0,
+      readout: `MAX ${Math.round(iss.max)}° · ${Math.round((iss.end - iss.start) / 60000)} MIN`, tele: () => 'ORBIT · ISS PASS · TLE · COMPUTED', cta: ['bell', 'Remind me'] },
+    { id: 'plume', arch: 'track', band: 'orbit', sit: 'launch', prio: 71, paint: 'plume', aspect: 1.3, title: 'Twilight launch: the plume was seen along 600 km of coast', place: 'Cape Canaveral', lat: 28.5618, lon: -80.5772, ago: 34,
+      readout: () => `T+${fmt.dur((Date.now() - GE.LAUNCH_T0) / 1000)}`, tele: () => 'ORBIT · TRACKING CAM · 2ND STAGE 212 KM' },
+    { id: 'room-qk', arch: 'room', band: 'inside', sit: 'quake', prio: 70, title: 'M 6.4 off Honshu', place: 'Fukushima · Miyagi · Ibaraki', lat: GE.BIGQ.lat, lon: GE.BIGQ.lon, ago: 3, ev: [['shake', {}], ['crossing', { seed: 33, cam: 'PHONE', rec: false }]] },
+    { id: 'gnss', arch: 'number', band: 'sky', sit: 'gnss', prio: 68, paint: 'gnss', aspect: 1.05, title: 'GPS interference over the Baltic', place: 'Baltic Sea', lat: 56.8, lon: 21.5, ago: 10,
+      big: '340', unit: 'aircraft', label: 'lost GPS integrity in the last hour', spark: [120, 160, 150, 210, 260, 240, 300, 340], tele: () => 'SKY · ADS-B NIC/NACp · 10 MIN' },
+    { id: 'heli', arch: 'track', band: 'sky', sit: 'novosel', prio: 66, live: true, paint: 'heli', po: { laps: 14 }, aspect: 1.1, title: 'HAWK 21 is flying its 14th circuit at Fort Novosel', place: 'Cairns Army Airfield, Alabama', lat: 31.276, lon: -85.713, ago: 0, ride: true,
+      readout: 'CIRCUIT 14 · 500 FT', tele: () => 'SKY · ADS-B/MLAT · 72 KT · 500 FT AGL', cta: ['helicopter', 'Ride along'] },
+    { id: 'koshi', arch: 'room', band: 'inside', sit: 'koshi', recon: 'koshi', prio: 64, wide: true, paint: 'globe', aspect: 0.56, title: 'Bhote Koshi outburst flood — 4D reconstruction', place: 'Rasuwa, Nepal · 26 Aug 2026', lat: 28.215, lon: 85.36, ago: 120 },
+    { id: 'sar', arch: 'sensor', band: 'orbit', sit: 'suez', prio: 62, paint: 'sar', aspect: 1.15, title: 'Radar satellite pass: 48 ships waiting off Suez', place: 'Gulf of Suez', lat: 29.86, lon: 32.55, ago: 47,
+      tele: () => 'ORBIT · SAR C-BAND · 10 M · DESC PASS' },
+    { id: 'volcano', arch: 'eye', band: 'ground', sit: 'sakurajima', prio: 60, live: true, paint: 'volcano', po: { cam: 'VOLCANO CAM 2', place: 'KAGOSHIMA BAY' }, aspect: 1.05, title: 'Sakurajima: ash column to 3.2 km, drifting away from the city', place: 'Kagoshima, Japan', lat: 31.58, lon: 130.66, ago: 2,
+      tele: () => `GROUND · VOLCANO CAM 2 · ${llz(31.58, 130.66)}` },
+    { id: 'blackout', arch: 'witness', band: 'inside', sit: 'cyclone', post: 'cy6', prio: 58, by: 'rafa', paint: 'blackout', aspect: 1.15, title: 'Aparri is dark — the hospital is running on generators', place: 'Aparri, Cagayan', lat: 18.357, lon: 121.637, ago: 22,
+      tele: () => 'WITNESS · SEALED · ±8 M · LOCAL' },
+  ];
+  for (const x of it) { x.at = NOW - x.ago * MIN3; x.dist = FD.distFromMe(x.lat, x.lon); }
+  return (FD._items = it);
+};
+FD.user = []; // your own posts land here (newest first)
+
+/* diversity-aware ordering: never two of the same archetype or band side by side when avoidable */
+FD.order = function (items) {
+  const rest = items.slice().sort((a, b) => b.prio - a.prio); const out = [];
+  while (rest.length) {
+    const prev = out[out.length - 1], prev2 = out[out.length - 2];
+    const fits = (x, strict) => !prev || ((x.arch !== prev.arch || !strict) && x.band !== prev.band && (!strict || !prev2 || x.arch !== prev2.arch));
+    let i = rest.findIndex((x) => fits(x, true)); if (i < 0) i = rest.findIndex((x) => fits(x, false)); if (i < 0) i = 0;
+    out.push(rest.splice(i, 1)[0]);
+  }
+  return out;
+};
+FD.list = function (band = 'all') {
+  const all = [...FD.user, ...FD.items()];
+  const f = band === 'all' ? all : band === 'near' ? all.filter((x) => x.dist < 2500) : all.filter((x) => x.band === band);
+  const user = f.filter((x) => x.mine); const ordered = FD.order(f.filter((x) => !x.mine));
+  return [...user, ...ordered];
+};
+FD.counts = function () { const c = { all: 0, orbit: 0, sky: 0, ground: 0, inside: 0 }; for (const x of [...FD.user, ...FD.items()]) { c.all++; c[x.band]++; } return c; };
diff --git a/mobile/vision/src/js/60-shell.js b/mobile/vision/src/js/60-shell.js
index 4d0d4ffae..62fb835ce 100644
--- a/mobile/vision/src/js/60-shell.js
+++ b/mobile/vision/src/js/60-shell.js
@@ -67,11 +67,17 @@ APP.updateChrome = function () {
 
 /* ---------- accessory ---------- */
 APP.renderAccessory = function () {
-  const s = GE.SIT.byId[APP.following]; if (!s) return;
-  const html = `<span class="dot pulse"></span><span class="txt"><div class="ttl">${esc(GE.CYCLONE.name)}</div><div class="sub num">${esc(s.accessory ? s.accessory() : '')}</div></span><svg class="spk" width="54" height="22" viewBox="0 0 54 22">${sparkPath(GE.CYCLONE.track.slice(0, 7).map((x) => x[3]), 54, 22, '#FF6A3D')}</svg><span class="ab"><svg class="ic sm"><use href="#i-chevu"/></svg></span>`;
-  $('#acc').innerHTML = html;
-  $('#accMini').innerHTML = `<span class="dot pulse"></span><span class="txt"><div class="ttl">${esc(GE.CYCLONE.name)}</div><div class="sub num">${esc(s.accessory ? s.accessory() : '')}</div></span>`;
+  // the tab-bar accessory follows a person, not a number: the live witness you follow (or you, when live)
+  const me = GE.capture?.live; let ttl, sub, open;
+  if (me && me.on) { ttl = `You’re live · ${fmt.dur((Date.now() - me.t0) / 1000).slice(3)}`; sub = `Sealed live · ${me.segs.length} segments · ${fmt.n(me.viewers)} watching`; open = () => APP.setTab('capture'); }
+  else { const r = GE.rooms.byId.cyclone; const n = r ? r.watching : 3204; ttl = '@nadia_basco · Basco seawall'; sub = `Sealed live · Typhoon Halcyon room · ${fmt.n(n)} watching`; open = () => { const it = GE.feed.items().find((x) => x.id === 'basco'); GE.now._item = it; GE.sheet.open('cyclone', { post: 'cy1' }); }; }
+  APP._accOpen = open;
+  const html = `<span class="accdot"><span class="dot pulse"></span></span><span class="txt"><div class="ttl">${esc(ttl)}</div><div class="sub num">${esc(sub)}</div></span><canvas class="accv" width="120" height="68"></canvas><span class="ab"><svg class="ic sm"><use href="#i-chevu"/></svg></span>`;
+  const a = $('#acc'); if (a._k !== ttl + sub) { a.innerHTML = html; a._k = ttl + sub; }
+  const m = $('#accMini'); if (m._k !== ttl + sub) { m.innerHTML = `<span class="dot pulse"></span><span class="txt"><div class="ttl">${esc(ttl)}</div><div class="sub num">${esc(sub)}</div></span>`; m._k = ttl + sub; }
 };
+APP.accFrame = function () { const cv = $('#acc .accv'); if (!cv || $('#accHost').classList.contains('hidden')) return; const me = GE.capture?.live; if (me && me.on) GE.paint.draw('seawall', cv, { skyline: true, noOSD: true, seed: 53, t: performance.now() / 1000 }); else GE.paint.draw('seawall', cv, { palm: true, noOSD: true, seed: 52, t: performance.now() / 1000 }); };
+setInterval(() => { try { APP.accFrame(); } catch {} }, 200);
 function sparkPath(data, w, h, col, sw = 1.6) {
   const mn = Math.min(...data), mx = Math.max(...data), n = data.length;
   const pts = data.map((v, i) => [(i / (n - 1)) * (w - 4) + 2, h - 3 - ((v - mn) / (mx - mn || 1)) * (h - 6)]);
@@ -92,6 +98,8 @@ APP.updateLabels = function (view) {
     const short = s.short || s.title.split(/ [—–-] /)[0].slice(0, 28);
     want.push({ k: 's:' + s.id, lat: s.lat, lon: s.lon, alt: 0.2, pr: s.watchers, html: `<i style="--c:${GE.FAM[s.fam].color}"></i>${esc(short)}`, w: short.length * 6.6 + 32, cls: 'glass', onclick: () => GE.sheet.open(s.id, { fromGlobe: true }) });
   }
+  const showEyes = (APP.tab === 'globe' || APP.isWide()) && !APP.intro && APP.mode !== 'ride' && APP.mode !== 'workspace';
+  if (showEyes) for (const e of GE.EYES || []) { if (view.range > 0.9 && e.kind !== 'you') continue; const t = e.label + (e.live ? ' · LIVE' : ''); want.push({ k: 'e:' + e.id + (e.live ? 'L' : ''), lat: e.lat, lon: e.lon, alt: 0.05, pr: e.kind === 'you' ? 2e9 : 6e4, html: `<i class="ei k-${e.kind}"><svg class="ic xs"><use href="#i-${e.kind === 'cctv' ? 'video' : 'eye'}"/></svg></i>${esc(t)}`, w: t.length * 6.4 + 40, cls: 'glass eyelbl k-' + e.kind, onclick: () => { if (e.id === 'you' && GE.live.on) { APP.setTab('capture'); return; } if (e.sit) { const it = GE.feed.items().find((x) => x.post && x.post === e.post); GE.now._item = it || null; GE.sheet.open(e.sit, { post: e.post }); } } }); }
   if (GE.world.sel && GE.world.sel.v && APP.mode !== 'ride') want.push({ k: 'sel', v: GE.world.sel.v, pr: 1e9, html: `<b>${esc(GE.world.sel.title)}</b>`, w: 90, cls: 'plain tag' });
   for (const [k, l] of GE.extraLabels || []) want.push({ k, pr: 1e8, w: 120, ...l });
   want.sort((a, b) => b.pr - a.pr);
@@ -126,7 +134,7 @@ GE.extraLabels = new Map();
 /* ---------- wiring ---------- */
 APP.initShell = function () {
   $$('.tab').forEach((b) => b.addEventListener('click', () => APP.setTab(b.dataset.tab)));
-  const openFollowed = () => GE.sheet.open(APP.following);
+  const openFollowed = () => (APP._accOpen ? APP._accOpen() : GE.sheet.open(APP.following));
   $('#acc').addEventListener('click', openFollowed); $('#accMini').addEventListener('click', openFollowed);
   $('#btnSearch').addEventListener('click', () => GE.gui.openSearch());
   // minimize tab bar on scroll (feed-like views)
diff --git a/mobile/vision/src/js/61-now.js b/mobile/vision/src/js/61-now.js
index 86ebf1bf3..d92752a9b 100644
--- a/mobile/vision/src/js/61-now.js
+++ b/mobile/vision/src/js/61-now.js
@@ -57,74 +57,140 @@ TH.fallback = function (s, canvas) {
 };
 
 /* ---------- feed ---------- */
+const BAND_ORDER = ['all', 'orbit', 'sky', 'ground', 'inside'];
+NOWV.band = store.get('band', 'all');
 const famIcon = (f) => GE.FAM[f].icon;
-function cardHTML(s) {
-  const c = GE.FAM[s.fam].color;
-  const [m, ml] = s.metric();
-  const badge = s.d4 ? `<span class="badge d4">4D</span><span class="badge replay">Thread</span>` : s.live ? `<span class="badge live"><span class="dot pulse"></span>Live</span>` : `<span class="badge replay">${s.replayLabel ? 'Replay · ' + s.replayLabel.replace('Today ', '') : 'Replay'}</span>`;
-  const right = s.thread ? `<span class="stack">${['tamang', 'hydro', 'kora', 'geo'].map((k) => `<span class="avatar sm" style="--h:${GE.PEOPLE[k].hue}">${GE.PEOPLE[k].h[0].toUpperCase()}</span>`).join('')}</span>` : `<span class="r">${ic('eye', 'xs')}<span class="num">${fmt.k(s.watchers)}</span></span>`;
-  return `<div class="thumb" style="aspect-ratio:${1}/${s.aspect}"><canvas width="360" height="${Math.round(360 * s.aspect)}"></canvas>
-    <div class="tl">${badge}</div><div class="tr" style="--c:${c}">${ic(famIcon(s.fam), 'sm')}</div>
-    <div class="bl"><div class="metric num" data-m>${m}</div><div class="mlabel num" data-ml>${ml}</div></div></div>
-    <div class="meta"><div class="ttl">${esc(s.title)}</div><div class="src"><span class="l"><span style="width:6px;height:6px;border-radius:50%;background:${c};flex:none"></span><span data-age>${esc(s.source)} · ${fmt.ago(Date.now() - s.updatedAt)}</span></span>${right}</div>
-    ${s.ride ? `<button class="cta" data-ride>${ic('helicopter', 'sm')}Jump into the chopper</button>` : ''}</div>`;
+const avatarHTML = (k, cls = 'sm') => { const p = GE.PEOPLE[k] || { h: k, hue: 205 }; return `<span class="avatar ${cls}" style="--h:${p.hue}">${esc((p.h || '?')[0].toUpperCase())}</span>`; };
+GE.avatarHTML = avatarHTML;
+const bandTag = (b) => `<span class="bt">${GE.BANDS[b].name.toUpperCase()}</span>`;
+function cvSize(x) { const W0 = x.wide ? 800 : 400; return [W0, Math.round(W0 * x.aspect)]; }
+function whereHTML(x) { const ago = x.live && x.ago < 1 ? 'LIVE NOW' : x.live ? `LIVE · ${fmt.ago(Date.now() - x.at).replace(' ago', '').toUpperCase()}` : fmt.ago(Date.now() - x.at).toUpperCase(); return `<div class="where"><div class="pl">${esc(x.place)}</div><div class="d mono">${x.dist < 60 ? 'NEAR YOU · ' : ''}${GE.feed.fmtDist(x.dist).toUpperCase()} AWAY · ${ago}</div></div>`; }
+function socHTML(x) {
+  const r = GE.rooms; const n = r.watching(x.sit); const posts = r.count(x.sit); const sealed = r.sealedCount(x.sit);
+  const ppl = (GE.rooms.byId[x.sit]?.posts || []).slice(0, 3).map((p) => p.by);
+  const stack = (ppl.length ? ppl : ['kora', 'sky', 'geo']).map((k) => avatarHTML(k)).join('');
+  return `<div class="soc">${x.wide ? `<span class="stack">${stack}</span>` : ''}<span>${ic('threads', 'xs')}<b class="num">${fmt.k(n)}</b> in room</span>${sealed ? `<span class="sl">${ic('seal', 'xs')}<b class="num">${sealed}</b> sealed</span>` : `<span><b class="num">${posts}</b> posts</span>`}</div>`;
+}
+function frameHTML(x, inner = '') {
+  const [w, h] = cvSize(x);
+  return `<div class="fr" style="aspect-ratio:${1}/${x.aspect}"><canvas width="${w}" height="${h}"></canvas><i class="bk a"></i><i class="bk b"></i><i class="bk c"></i><i class="bk d"></i>
+    <div class="ftop">${bandTag(x.band)}<span class="at">${GE.ARCH[x.arch].toUpperCase()}</span>${x.live ? '<span class="lv"><i></i>LIVE</span>' : ''}${x.mine ? '<span class="mine">YOU</span>' : ''}</div>
+    ${inner}${x.tele ? `<div class="tele" data-tele>${esc(x.tele())}</div>` : ''}</div>`;
+}
+function cardHTML(x) {
+  const B = GE.BANDS[x.band];
+  if (x.arch === 'room' && !x.recon) return roomCardHTML(x);
+  let inner = '';
+  if (x.arch === 'number') inner = `<div class="numov"><div class="big num">${x.big}<small>${esc(x.unit)}</small></div><div class="nl">${esc(x.label)}</div><svg class="nsp" viewBox="0 0 160 34" preserveAspectRatio="none">${GE.sparkPath(x.spark, 160, 34, B.c, 2)}</svg></div>`;
+  if (x.readout) inner += `<div class="readout num" data-ro>${esc(typeof x.readout === 'function' ? x.readout() : x.readout)}</div>`;
+  if (x.arch === 'witness') inner += `<svg class="fseal"><use href="#i-seal"/></svg>`;
+  if (x.recon) inner += `<div class="r4d"><span class="badge d4">4D</span><span class="badge">Reconstruction</span></div>`;
+  const who = x.by ? (() => { const p = GE.PEOPLE[x.by]; const room = GE.rooms.get(x.sit); const post = room?.posts.find((q) => q.id === x.post); const bd = post ? GE.rooms.badges(room, post).slice(0, 2) : []; return `<div class="who">${avatarHTML(x.by)}<b>@${esc(p.h)}</b>${bd.map(([k, l]) => `<span class="bdg ${k}">${esc(l)}</span>`).join('')}</div>`; })() : '';
+  const cta = x.cta ? `<button class="cta" data-cta>${ic(x.cta[0], 'sm')}${esc(x.cta[1])}</button>` : '';
+  const recon = x.recon ? `<div class="soc"><span><b class="num">23</b> observations</span><span><b class="num">9</b> hypotheses</span><span class="sl">${ic('link', 'xs')}ledger verified</span></div>` : socHTML(x);
+  return `${frameHTML(x, inner)}<div class="fm">${who}<div class="ttl">${esc(x.title)}</div>${whereHTML(x)}${recon}${cta}</div>`;
+}
+function roomCardHTML(x) {
+  const room = GE.rooms.get(x.sit); const syn = room.synth; const open = room.posts.find((p) => p.kind === 'question' && !p.answered);
+  const ppl = [...new Set(room.posts.map((p) => p.by))].slice(0, 5);
+  const line = (cls, lab, t, c) => t ? `<div class="cl ${cls}"><b>${lab}</b><span>${esc(t)}</span>${c ? `<span class="cites">${c.map((z) => `<i>${z}</i>`).join('')}</span>` : ''}</div>` : '';
+  const ev = (x.ev || []).map((e, i) => `<canvas class="evc" data-ev="${i}" width="200" height="150"></canvas>`).join('');
+  const sealed = room.posts.filter((p) => p.att && /^sealed/.test(p.att.tier)).length; const notes = room.posts.filter((p) => p.note).length;
+  return `<div class="rhead"><span class="rtag">${ic('threads', 'xs')}ROOM</span>${bandTag('inside')}<span class="lvw"><span class="dot pulse"></span><b class="num" data-watch>${fmt.n(room.watching)}</b> watching</span><span class="stack">${ppl.map((k) => avatarHTML(k)).join('')}</span></div>
+    <h3>${esc(x.title)}</h3>${whereHTML(x)}
+    <div class="claims">${line('known', 'KNOWN', syn.known[0]?.[0], syn.known[0]?.[1])}${line('disputed', 'DISPUTED', syn.disputed[0]?.[0], syn.disputed[0]?.[1])}${open ? line('open', 'ASKED', '“' + open.text + '”', null) : line('unknown', 'UNKNOWN', syn.unknown[0]?.[0], syn.unknown[0]?.[1])}</div>
+    ${ev ? `<div class="evs">${ev}</div>` : ''}
+    <div class="rfoot"><span><b class="num">${room.posts.length}</b> posts · <b class="num">${sealed}</b> sealed${notes ? ` · <b class="num">${notes}</b> note` : ''}</span><span class="join">Join the room ${ic('chevr', 'xs')}</span></div>`;
 }
 NOWV.render = function () {
-  const v = $('#v-now');
-  const now = new Date();
-  const kick = now.toLocaleDateString('en-GB', { weekday: 'long', day: 'numeric', month: 'long', timeZone: 'UTC' });
-  v.innerHTML = `<div class="navbar">Now</div>
+  const v = $('#v-now'); const now = new Date();
+  const kick = now.toLocaleDateString('en-GB', { weekday: 'short', day: 'numeric', month: 'short', timeZone: 'UTC' }).toUpperCase();
+  v.innerHTML = `<div class="navbar"><span class="wm">GOD’S EYE</span></div>
   <div class="now-hero">
-    <div class="lt"><div class="kicker"><span class="dot pulse"></span><span>${kick}</span>·<span class="num" id="nowClock">${fmt.hm(Date.now())} UTC</span></div>
-      <div class="row"><h1>Now</h1><button class="avatar md" style="--h:205" aria-label="You" id="nowMe">Y</button></div></div>
-    <div class="livebar"><span><b class="num" id="cSit">${GE.SIT.list.length}</b> situations</span><span><b class="num" id="cAir">–</b> aircraft</span><span><b class="num" id="cShip">–</b> vessels</span><span><b class="num" id="cSat">${fmt.n(GE.SATS.length)}</b> satellites</span></div>
+    <div class="hud"><span class="wm">GOD’S&nbsp;EYE</span><i class="hb a"></i><i class="hb b"></i><i class="hb c"></i><i class="hb d"></i><i class="xh"></i><div class="hud-t mono" id="heroTele"></div></div>
+    <div class="lt"><div class="kicker mono"><span class="dot pulse"></span><span>LIVE · ${kick} · <span class="num" id="nowClock">${GE.feed.hmsZ()}</span></span></div>
+      <div class="row"><h1>Right now, at every altitude.</h1><button class="avatar md" style="--h:205" aria-label="You" id="nowMe">Y</button></div>
+      <div class="counts mono"><span><b class="num" id="cAir">–</b> aircraft</span><span><b class="num" id="cShip">–</b> vessels</span><span><b class="num">${fmt.n(GE.SATS.length)}</b> satellites</span><span><b class="num">408</b> cameras</span><span class="w"><b class="num" id="cWit">14</b> witnesses live</span></div></div>
   </div>
-  <div class="now-body"><div class="chips" id="nowChips">
-    ${[['all', 'For you'], ['now', 'Happening now'], ['near', 'Near you'], ['recon', 'Reconstructions'], ['always', 'Always on']].map(([k, l]) => `<button class="chip ${NOWV.filter === k ? 'on' : ''}" data-f="${k}">${l}</button>`).join('')}
-  </div><div id="nowSecs"></div></div>`;
+  <div class="now-body"><div class="bandrail" id="bandRail" role="tablist" aria-label="Altitude"></div><div id="feed"></div><div class="feed-end mono">${ic('sparkles', 'xs')} CONCEPT · ILLUSTRATIVE DATA · PEOPLE AND POSTS ARE FICTIONAL</div></div>`;
   $('#nowMe').addEventListener('click', () => APP.setTab('you'));
-  $$('#nowChips .chip').forEach((b) => b.addEventListener('click', () => { NOWV.filter = b.dataset.f; $$('#nowChips .chip').forEach((x) => x.classList.toggle('on', x === b)); NOWV.renderSections(); haptic(4); }));
-  NOWV.renderSections();
+  NOWV.renderRail(); NOWV.renderFeed();
 };
-NOWV.renderSections = function () {
-  const host = $('#nowSecs'); host.innerHTML = '';
-  for (const sec of GE.SIT.sections) {
-    if (NOWV.filter !== 'all' && NOWV.filter !== sec.id) continue;
-    const items = GE.SIT.list.filter((s) => s.section === sec.id);
-    const hd = h('div', { class: 'sec-h' }, h('h2', null, sec.title), h('span', null, sec.sub));
-    const grid = h('div', { class: 'masonry' }); const cols = [h('div', { class: 'col' }), h('div', { class: 'col' })]; grid.append(...cols);
-    const hs = [0, 0];
-    for (const s of items) {
-      const el = h('article', { class: 'card', 'data-id': s.id, tabindex: 0, role: 'button', 'aria-label': s.title }); el.innerHTML = cardHTML(s);
-      const ci = hs[0] <= hs[1] ? 0 : 1; cols[ci].append(el); hs[ci] += s.aspect + 0.62;
-      el.addEventListener('click', (e) => { if (e.target.closest('[data-ride]')) { e.stopPropagation(); NOWV.open(s, el, { ride: true }); return; } NOWV.open(s, el); });
-      el.addEventListener('keydown', (e) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); NOWV.open(s, el); } });
-      const cv = el.querySelector('canvas');
-      const cached = TH.done.get(s.id);
-      if (cached) cv.getContext('2d').drawImage(cached, 0, 0);
-      else { TH.fallback(s, cv); TH.enqueue(() => { const c2 = document.createElement('canvas'); c2.width = cv.width; c2.height = cv.height; TH.renderSituation(s, c2); TH.done.set(s.id, c2); $$(`.card[data-id="${s.id}"] canvas, .tcard[data-id="${s.id}"] canvas`).forEach((x) => { const xc = x.getContext('2d'); xc.drawImage(c2, 0, 0, x.width, x.height); }); }); }
-    }
-    host.append(hd, grid);
+NOWV.renderRail = function () {
+  const c = GE.feed.counts();
+  $('#bandRail').innerHTML = BAND_ORDER.map((b) => { const B = GE.BANDS[b]; return `<button class="bcell ${NOWV.band === b ? 'on' : ''}" data-b="${b}" role="tab" aria-selected="${NOWV.band === b}" style="--c:${B ? B.c : '#E8EEF8'}"><i></i><b>${b === 'all' ? 'ALL' : B.name.toUpperCase()}</b><span class="num">${c[b]}</span><em>${b === 'all' ? 'orbit → you' : esc(B.alt)}</em></button>`; }).join('<span class="rarr"></span>');
+  $$('#bandRail .bcell').forEach((el) => el.addEventListener('click', () => { NOWV.band = el.dataset.b; store.set('band', NOWV.band); NOWV.renderRail(); NOWV.renderFeed(); haptic(5); const v = $('#v-now'); const r = $('#bandRail'); if (v.scrollTop > r.offsetTop) v.scrollTo({ top: r.offsetTop - 4, behavior: 'smooth' }); }));
+};
+NOWV.cardEl = function (x) {
+  const el = h('article', { class: `card fc a-${x.arch} b-${x.band}${x.wide ? ' wide' : ''}${x.arch === 'room' && !x.recon ? ' room' : ''}${x.mine ? ' mine' : ''}`, 'data-fid': x.id, 'data-id': x.sit, tabindex: 0, role: 'button', 'aria-label': x.title, style: `--c:${GE.BANDS[x.band].c}` });
+  el.innerHTML = cardHTML(x);
+  const go = (e) => { if (e && e.target.closest('[data-cta]')) { e.stopPropagation(); if (x.ride) { NOWV.open(GE.SIT.byId[x.sit], el, { ride: true }); return; } if (x.cta[0] === 'bell') { APP.toast(`${ic('bell', 'sm')} Reminder set · 5 min before the pass`); return; } } NOWV.openItem(x, el); };
+  el.addEventListener('click', go); el.addEventListener('keydown', (e) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); go(); } });
+  // paint
+  const cv = el.querySelector('.fr canvas');
+  if (cv) NOWV.paint(x, cv);
+  el.querySelectorAll('canvas.evc').forEach((c) => { const [id, o] = x.ev[+c.dataset.ev]; TH.enqueue(() => GE.paint.draw(id, c, { ...o, t: 2 + +c.dataset.ev })); });
+  return el;
+};
+NOWV.paint = function (x, cv) {
+  if (x.img) { const im = new Image(); im.onload = () => { const cx = cv.getContext('2d'); const s = Math.max(cv.width / im.width, cv.height / im.height); cx.drawImage(im, (cv.width - im.width * s) / 2, (cv.height - im.height * s) / 2, im.width * s, im.height * s); }; im.src = x.img; return; }
+  if (x.paint === 'globe') { const s = GE.SIT.byId[x.sit]; const cached = TH.done.get(s.id); if (cached) cv.getContext('2d').drawImage(cached, 0, 0, cv.width, cv.height); else { TH.fallback(s, cv); TH.enqueue(() => { const c2 = document.createElement('canvas'); c2.width = cv.width; c2.height = cv.height; TH.renderSituation(s, c2); TH.done.set(s.id, c2); $$(`[data-id="${s.id}"] .fr canvas`).forEach((z) => z.getContext('2d').drawImage(c2, 0, 0, z.width, z.height)); }); } return; }
+  const key = x.id + '|' + cv.width; const done = NOWV.painted.get(key);
+  const cx = cv.getContext('2d'); cx.fillStyle = '#06080c'; cx.fillRect(0, 0, cv.width, cv.height);
+  if (GE.paint.animated(x.paint)) { NOWV.anim.set(cv, x); TH.enqueue(() => GE.paint.draw(x.paint, cv, { ...x.po, t: performance.now() / 1000 })); return; }
+  if (done) { cx.drawImage(done, 0, 0); return; }
+  TH.enqueue(() => { if (!GE.paint.draw(x.paint, cv, { ...x.po })) return; const c2 = GE.paint.mk(cv.width, cv.height); c2.getContext('2d').drawImage(cv, 0, 0); NOWV.painted.set(key, c2); });
+};
+NOWV.painted = new Map(); NOWV.anim = new Map(); NOWV.vis = new Set();
+NOWV.renderFeed = function () {
+  const host = $('#feed'); if (!host) return; host.innerHTML = ''; NOWV.anim.clear();
+  const list = GE.feed.list(NOWV.band);
+  if (NOWV.band !== 'all') { const B = GE.BANDS[NOWV.band]; host.append(h('div', { class: 'band-h', style: `--c:${B.c}`, html: `<b>${B.name}</b><span>${esc(B.alt)} · ${esc(B.sensor)}</span>` })); }
+  let grid = null, cols = null, hs = [0, 0];
+  const flush = () => { grid = null; };
+  for (const x of list) {
+    const el = NOWV.cardEl(x);
+    if (x.wide) { flush(); host.append(el); continue; }
+    if (!grid) { grid = h('div', { class: 'masonry' }); cols = [h('div', { class: 'col' }), h('div', { class: 'col' })]; grid.append(...cols); host.append(grid); hs = [0, 0]; }
+    const ci = hs[0] <= hs[1] ? 0 : 1; cols[ci].append(el); hs[ci] += (x.aspect || 0.9) + (x.arch === 'number' ? 0.5 : 0.62) + (x.by ? 0.16 : 0) + (x.cta ? 0.2 : 0);
   }
+  NOWV.observe();
+};
+NOWV.observe = function () {
+  if (!('IntersectionObserver' in window)) { NOWV.anim.forEach((x, cv) => NOWV.vis.add(cv)); return; }
+  NOWV.io && NOWV.io.disconnect(); NOWV.vis.clear();
+  NOWV.io = new IntersectionObserver((es) => { for (const e of es) { const cv = e.target; if (e.isIntersecting) NOWV.vis.add(cv); else NOWV.vis.delete(cv); } }, { root: $('#v-now'), rootMargin: '80px' });
+  NOWV.anim.forEach((x, cv) => NOWV.io.observe(cv));
+};
+// animated eyes: CCTV and live scenes redraw at ~8 fps while visible
+NOWV.animate = function () {
+  if (APP.tab !== 'now' || APP.mode || APP.intro) return; const t = performance.now() / 1000;
+  for (const cv of NOWV.vis) { const x = NOWV.anim.get(cv); if (!x) continue; GE.paint.draw(x.paint, cv, { ...x.po, t }); }
+};
+setInterval(() => { try { NOWV.animate(); } catch (e) { console.warn(e); } }, 125);
+NOWV.openItem = function (x, el) {
+  if (x.recon) { APP.setTab('threads'); GE.threads.openWs(x.recon); return; }
+  const s = GE.SIT.byId[x.sit]; NOWV._item = x;
+  if (x.arch === 'room') { GE.sheet.open(x.sit, { post: x.post }); return; }
+  NOWV.open(s, el, { cam: x.cam, post: x.post, seg: x.arch === 'number' || (x.arch === 'sensor' && !x.post) ? 'room' : 'room' });
 };
 NOWV.tick = function () {
   const W = GE.world;
   const c = W.counts; const air = (c.flights || 0) + (c.military || 0) + (c.ga || 0) + GE.HELI_CIRCUITS.length;
   const a = $('#cAir'); if (a) a.textContent = fmt.n(air);
   const sh = $('#cShip'); if (sh) sh.textContent = fmt.n(GE.SHIPS.length);
-  const ck = $('#nowClock'); if (ck) ck.textContent = fmt.hm(Date.now()) + ' UTC';
-  for (const el of $$('.card[data-id]')) {
-    const s = GE.SIT.byId[el.dataset.id]; if (!s) continue;
-    const [m, ml] = s.metric(); const me = el.querySelector('[data-m]'), mle = el.querySelector('[data-ml]');
-    if (me && me.innerHTML !== m) { me.innerHTML = m; } if (mle && mle.innerHTML !== ml) mle.innerHTML = ml;
-    const ag = el.querySelector('[data-age]'); if (ag) ag.textContent = `${s.source} · ${fmt.ago(Date.now() - s.updatedAt)}`;
-  }
+  const ck = $('#nowClock'); if (ck) ck.textContent = GE.feed.hmsZ();
+  const ht = $('#heroTele'); if (ht && GE.mainView) { const v = GE.mainView; const [la, lo, alt] = geo.ll(v.eye); ht.textContent = `ORBIT · ALT ${fmt.n(Math.round(alt))} KM · NADIR ${GE.feed.llz(la, lo)} · TERMINATOR ${W.sun.lat >= 0 ? 'N' : 'S'} · ${GE.feed.hmsZ()}`; }
+  if (APP.tab !== 'now') return;
+  const items = new Map([...GE.feed.user, ...GE.feed.items()].map((x) => [x.id, x]));
+  for (const el of $$('#feed .fc[data-fid]')) { const x = items.get(el.dataset.fid); if (!x) continue; const t = el.querySelector('[data-tele]'); if (t && x.tele) { const s2 = x.tele(); if (t.textContent !== s2) t.textContent = s2; } const ro = el.querySelector('[data-ro]'); if (ro && typeof x.readout === 'function') ro.textContent = x.readout(); const w = el.querySelector('[data-watch]'); if (w) { const r = GE.rooms.byId[x.sit]; if (r) w.textContent = fmt.n(r.watching); } }
 };
+GE.rooms.drift = setInterval(() => { for (const r of Object.values(GE.rooms.byId)) r.watching += Math.round((Math.random() - 0.42) * r.rate * 3); }, 2000);
 
 /* ---------- hero morph: card → live globe ---------- */
 NOWV.open = function (s, cardEl, o = {}) {
   const wide = APP.isWide();
-  const thumb = cardEl?.querySelector('.thumb canvas');
+  const thumb = cardEl?.querySelector('.fr canvas') || cardEl?.querySelector('.evc');
   if (wide || !thumb || prefersReduced()) { GE.sheet.open(s.id, { ...o, fade: !wide }); return; }
   const r = thumb.getBoundingClientRect(); const app = $('#app').getBoundingClientRect();
   const M = $('#morph'); M.innerHTML = ''; const cv = document.createElement('canvas'); cv.width = thumb.width; cv.height = thumb.height; cv.getContext('2d').drawImage(thumb, 0, 0); M.append(cv);
@@ -144,9 +210,9 @@ NOWV.open = function (s, cardEl, o = {}) {
   }));
 };
 NOWV.foldBack = function (id) {
-  const cardEl = $(`#v-now .card[data-id="${id}"]`); const M = $('#morph');
+  const cardEl = (NOWV._morphCard && document.body.contains(NOWV._morphCard) && NOWV._morphCard.dataset.id === id) ? NOWV._morphCard : $(`#v-now .card[data-id="${id}"]`); const M = $('#morph');
   if (!cardEl || prefersReduced() || APP.isWide()) return false;
-  const thumb = cardEl.querySelector('.thumb canvas'); const app = $('#app').getBoundingClientRect();
+  const thumb = cardEl.querySelector('.fr canvas') || cardEl.querySelector('.evc'); if (!thumb) return false; const app = $('#app').getBoundingClientRect();
   M.innerHTML = ''; const cv = document.createElement('canvas'); cv.width = thumb.width; cv.height = thumb.height; cv.getContext('2d').drawImage(thumb, 0, 0); M.append(cv);
   const tw = app.width, th = app.height * 0.57;
   Object.assign(M.style, { left: '0px', top: '0px', width: tw + 'px', height: th + 'px', transformOrigin: '0 0', transition: 'none', transform: 'none', borderRadius: '0px', opacity: '0' });
diff --git a/mobile/vision/src/js/62-sheet.js b/mobile/vision/src/js/62-sheet.js
index ec8b0d8a8..f2b7335dd 100644
--- a/mobile/vision/src/js/62-sheet.js
+++ b/mobile/vision/src/js/62-sheet.js
@@ -1,7 +1,7 @@
 /* Situation sheet: detents (peek / medium / large), drag with velocity snapping, the world always
    wins (touching the globe collapses to peek). Tufte-grade brief: direct-labelled sparklines with
    uncertainty, small multiples rendered from the globe, evidence strip, every number sourced + aged. */
-const SH = (GE.sheet = { id: null, detent: 'medium' });
+const SH = (GE.sheet = { id: null, detent: 'medium', seg: 'room' });
 const sheetEl = () => $('#sheet');
 SH.heights = function () {
   const H = $('#app').clientHeight; const sab = parseFloat(getComputedStyle(document.documentElement).getPropertyValue('--sab')) || 0;
@@ -19,7 +19,7 @@ SH.setDetent = function (d, animate = true) {
 SH.open = function (id, o = {}) {
   const s = GE.SIT.byId[id]; if (!s) return;
   const W = GE.world;
-  SH.id = id; SH.sit = s;
+  SH.fromTab = APP.mode === 'situation' ? SH.fromTab : APP.tab; SH.id = id; SH.sit = s; SH.opts = o; SH.seg = o.seg || 'room';
   if (APP.tab !== 'globe' && !APP.isWide()) { APP.tab = 'globe'; $('#app').dataset.tab = 'globe'; $$('.tab').forEach((b) => b.classList.toggle('on', b.dataset.tab === 'globe')); $$('.pane .view').forEach((v) => v.classList.remove('on')); APP.moveLens(); }
   APP.setMode('situation');
   // layers & time window
@@ -28,9 +28,9 @@ SH.open = function (id, o = {}) {
   bus.emit('layers', W.layers);
   if (s.time) { W.setWindow({ start: s.time.start ?? s.time.at - 6 * 3600000, end: s.time.end ?? s.time.at + 6 * 3600000 }); W.setTime(s.time.at); }
   W.auroraK = s.auroraK ?? 0.85;
-  GE.setExtras && GE.setExtras(s.id); GE.setLabels3d(s.thread ? GE.threads.data[s.thread].labels : s.labels3d);
+  GE.setExtras && GE.setExtras(s.id); GE.setLabels3d(s.thread ? GE.threads.data[s.thread].labels : s.labels3d); GE.roomUI.labels(s, o.post);
   // camera
-  const cam = GE.SIT.cameraFor(s);
+  const cam = o.cam || GE.SIT.cameraFor(s);
   const hs = SH.heights();
   const shiftY = APP.isWide() ? 0 : hs.medium / hs.H;
   SH.targetShift = shiftY;
@@ -48,13 +48,14 @@ SH.open = function (id, o = {}) {
 SH.close = function (silent, keepTime) {
   if (!SH.id) return; const id = SH.id; const W = GE.world;
   const el = sheetEl(); el.classList.remove('drag', 'wopen'); el.style.transform = APP.isWide() ? '' : 'translateY(100%)';
-  SH.id = null; W.focus = null; GE.setExtras && GE.setExtras(null); GE.setLabels3d(null);
+  SH.id = null; W.focus = null; GE.setExtras && GE.setExtras(null); GE.setLabels3d(null); GE.roomUI.composer(false);
   if (SH._savedLayers) { W.layers.forEach((l, i) => (l.on = SH._savedLayers[i])); SH._savedLayers = null; bus.emit('layers', W.layers); }
   if (!keepTime) { W.setWindow(null); W.setTime(null); } W.auroraK = 0.85;
   APP.setMode('');
   if (silent) return;
   const fromNow = !APP.isWide() && GE.now && $(`#v-now .card[data-id="${id}"]`);
-  if (fromNow) { APP.setTab('now', { force: true }); requestAnimationFrame(() => GE.now.foldBack(id)); }
+  if (SH.fromTab === 'threads' || SH.fromTab === 'you') APP.setTab(SH.fromTab, { force: true });
+  else if (fromNow) { APP.setTab('now', { force: true }); requestAnimationFrame(() => GE.now.foldBack(id)); }
   else { Cam.flyTo({ range: Math.max(Cam.range * 3, 0.6), shiftY: APP.isWide() ? 0 : 0.06, tilt: 0 }); }
 };
 
@@ -127,8 +128,26 @@ function barsSVG(items, w) {
   items.forEach(([k, v], i) => { const y = i * 22; s += `<text x="0" y="${y + 14}" font-size="12" fill="rgba(232,238,248,.75)" font-family="var(--font)">${k}</text><rect x="92" y="${y + 6}" width="${(w - 132) * v}" height="10" rx="3" fill="rgba(124,196,255,.55)"/><text x="${92 + (w - 132) * v + 6}" y="${y + 15}" font-size="11" fill="rgba(232,238,248,.55)" font-family="var(--font)">${Math.round(v * 100)}</text>`; });
   return `<svg viewBox="0 0 ${w} ${hgt}" width="${w}" height="${hgt}">${s}</svg>`;
 }
+const bandOfSit = (s) => (GE.now?._item?.sit === s.id ? GE.now._item.band : { orbit: 'orbit', sky: 'sky', wx: 'sky', eyes: 'ground' }[s.fam] || 'ground');
 SH.render = function (s) {
-  const c = GE.FAM[s.fam].color; const el = $('#sheetC');
+  const el = $('#sheetC'); const b = bandOfSit(s); const B = GE.BANDS[b]; const room = GE.rooms.get(s.id);
+  const live = s.live ? `<span class="badge live"><span class="dot pulse"></span>Live</span>` : s.d4 ? `<span class="badge d4">4D</span>` : `<span class="badge replay">Replay</span>`;
+  const ppl = [...new Set(room.posts.map((p) => p.by))].slice(0, 5);
+  el.innerHTML = `<div class="sh-hd"><div class="t"><div class="tags" style="--c:${B.c}"><span class="bt">${B.name.toUpperCase()}</span>${live}<span class="age num" data-sage>${fmt.ago(Date.now() - s.updatedAt)}</span></div>
+    <h2>${esc(s.title)}</h2><div class="pl">${esc(s.place)} · <span class="mono">${fmt.ll(s.lat, s.lon, 2)}</span> · <b>${GE.feed.fmtDist(GE.feed.distFromMe(s.lat, s.lon))}</b> from you</div></div></div>
+    <div class="presence-row"><span class="stack">${ppl.map((k) => GE.avatarHTML(k)).join('')}</span><span><b class="num" data-watch>${fmt.n(room.watching)}</b> watching</span><span class="rate">${room.rate} posts/min</span></div>
+    <div class="seg2" id="shSegs"><button data-seg="room" class="${SH.seg === 'room' ? 'on' : ''}">${ic('threads', 'xs')}Room <span class="num">${room.posts.length}</span></button><button data-seg="brief" class="${SH.seg === 'brief' ? 'on' : ''}">${ic('signal', 'xs')}Brief &amp; sources</button></div>
+    <div id="shSeg"></div>`;
+  el.querySelectorAll('[data-seg]').forEach((bt) => bt.addEventListener('click', () => { SH.seg = bt.dataset.seg; el.querySelectorAll('[data-seg]').forEach((x) => x.classList.toggle('on', x === bt)); SH.renderSeg(s); haptic(4); }));
+  SH.renderSeg(s);
+};
+SH.renderSeg = function (s) {
+  const host = $('#shSeg'); GE.roomUI.composer(SH.seg === 'room');
+  if (SH.seg === 'room') { GE.roomUI.render(host, s, { post: SH.opts?.post }); return; }
+  SH.renderBrief(s, host);
+};
+SH.renderBrief = function (s, el) {
+  const c = GE.FAM[s.fam].color;
   const ms = s.metrics();
   const live = s.live ? `<span class="badge live"><span class="dot pulse"></span>Live</span>` : s.d4 ? `<span class="badge d4">4D</span>` : `<span class="badge replay">Replay</span>`;
   const acts = [
@@ -139,8 +158,6 @@ SH.render = function (s) {
   ].join('');
   const b = s.brief || {};
   el.innerHTML = `
-  <div class="sh-hd"><div class="t"><div style="display:flex;gap:6px;align-items:center"><span class="badge fam" style="--c:${c}"><i></i>${GE.FAM[s.fam].name}</span>${live}<span style="font-size:12px;color:var(--text3)" class="num" data-sage>${fmt.ago(Date.now() - s.updatedAt)}</span></div>
-    <h2>${esc(s.title)}</h2><div class="pl">${esc(s.place)} · <span class="mono">${fmt.ll(s.lat, s.lon, 2)}</span></div></div></div>
   <div class="metrics" id="shMetrics">${ms.map((m) => `<div class="metric"><div class="v">${m.v}<small>${m.u}</small></div><div class="l">${m.l}</div><div class="s">${m.s}</div></div>`).join('')}</div>
   <div class="acts sh-acts">${acts}</div>
   <div class="brief">
diff --git a/mobile/vision/src/js/63-globe-ui.js b/mobile/vision/src/js/63-globe-ui.js
index c40754a3e..cc73b6066 100644
--- a/mobile/vision/src/js/63-globe-ui.js
+++ b/mobile/vision/src/js/63-globe-ui.js
@@ -136,7 +136,10 @@ GUI.drawRibbon = function () {
   el.classList.toggle('future', cur > 0.02 && !W.window);
   el.classList.toggle('breath', W.live && !prefersReduced());
   const nb = $('#rbNow'); nb.classList.toggle('live', W.live); nb.innerHTML = W.window ? `${ic('clock', 'xs')}EVENT` : W.live ? '<span class="dot pulse"></span>LIVE' : 'NOW';
-  const stt = $('#statusTxt'); if (stt) { stt.textContent = W.window ? 'Replay' : W.live ? 'Live' : cur > 0 ? 'Forecast' : 'Replay'; $('#statusTime').textContent = fmt.utc(simMs, false) + ' UTC'; $('#status .dot').style.background = W.live ? '' : cur > 0 ? 'var(--wx)' : 'var(--gold)'; }
+  const stt = $('#statusTxt'); if (stt) {
+    const alt = (GE.mainView ? geo.ll(GE.mainView.eye)[2] : Cam.range * EARTH_KM); const band = alt > 120 ? 'ORBIT' : alt > 0.8 ? 'SKY' : 'GROUND'; const bc = { ORBIT: 'var(--b-orbit)', SKY: 'var(--b-sky)', GROUND: 'var(--b-ground)' }[band];
+    if (GE.live && GE.live.on) { stt.innerHTML = `You’re live · <b class="num">${fmt.dur((Date.now() - GE.live.t0) / 1000).slice(3)}</b>`; $('#statusTime').textContent = 'return'; $('#status .dot').style.background = ''; }
+    else { stt.innerHTML = `${W.window ? 'Replay' : W.live ? 'Live' : cur > 0 ? 'Forecast' : 'Replay'} <span class="alt mono" style="color:${bc}">${band} · ${alt >= 10 ? fmt.n(Math.round(alt)) + ' KM' : alt >= 1 ? alt.toFixed(1) + ' KM' : fmt.n(Math.round(alt * 1000)) + ' M'}</span>`; $('#statusTime').textContent = fmt.utc(simMs, false) + ' UTC'; $('#status .dot').style.background = W.live ? '' : cur > 0 ? 'var(--wx)' : 'var(--gold)'; } }
 };
 GUI.pips = function () {
   const nowMs = Date.now(); const W = GE.world;
@@ -217,5 +220,5 @@ GUI.init = function () {
   $('#btnLens').addEventListener('click', () => { const ids = LENSES.map((l) => l[0]); const i = (ids.indexOf(GE.world.lens) + 1) % ids.length; GE.world.setLens(ids[i]); APP.toast(`${ic('sparkles', 'sm')} ${LENSES[i][1]} lens`); $('#btnLens').classList.toggle('on', ids[i] !== 'cinematic'); });
   $('#btnHome').addEventListener('click', () => { GUI.showPick(null); Cam.flyTo({ range: 2.6, tilt: 0, heading: 0, shiftY: APP.isWide() ? 0 : 0.06 }); });
   $('#btnCompass').addEventListener('click', () => Cam.flyTo({ heading: 0, tilt: 0 }, { duration: 0.8 }));
-  $('#status').addEventListener('click', () => GUI.snapNow());
+  $('#status').addEventListener('click', () => { if (GE.live && GE.live.on) { APP.setTab('capture'); return; } GUI.snapNow(); });
 };
diff --git a/mobile/vision/src/js/65-capture.js b/mobile/vision/src/js/65-capture.js
index 9a9ba8674..44eabfd6a 100644
--- a/mobile/vision/src/js/65-capture.js
+++ b/mobile/vision/src/js/65-capture.js
@@ -51,32 +51,42 @@ CAP.enter = function () {
   CAP.render();
   KEY.get();
 };
-CAP.exit = function () { if (!CAP.on) return; CAP.on = false; GE.renderOverride = null; Cam.setRig(null); Cam.rigBlend = 1; $('#sealOv').classList.remove('on'); };
+CAP.exit = function () { if (!CAP.on) return; CAP.on = false; CAP.cover = false; GE.renderOverride = null; Cam.setRig(null); Cam.rigBlend = 1; $('#sealOv').classList.remove('on'); };
+CAP.MODES = [['look', 'Look'], ['witness', 'Witness'], ['live', 'Live'], ['upload', 'Upload']];
+CAP.setMode = function (m) { if (CAP.mode === 'live' && m !== 'live' && CAP.live?.on) { APP.toast(`${ic('live', 'sm')} End the broadcast first`); return; } CAP.mode = m; if (CAP.on) CAP.render(); };
 CAP.render = function () {
-  const el = $('#v-capture'); const last = GE.captures[GE.captures.length - 1];
-  el.innerHTML = `<div class="cap-ui">
+  const el = $('#v-capture'); const last = GE.captures[GE.captures.length - 1]; const m = CAP.mode;
+  const rt = CAP.replyTo && GE.SIT.byId[CAP.replyTo.sit];
+  CAP.cover = m === 'live';
+  el.innerHTML = `<canvas class="livecv ${m === 'live' ? 'on' : ''}" id="liveCv"></canvas><div class="cap-ui m-${m}">
     <svg class="compass-tape" id="ctape"></svg>
     <div class="callouts" id="callouts"></div>
-    <div class="cap-top"><span class="st glass">${ic('location', 'xs')}<span>Simulated camera · ${SPOT.name}</span></span><span class="st glass" id="capMode">${CAP.mode === 'look' ? `${ic('eye', 'xs')}Look · AR` : `${ic('key', 'xs')}Witness · signing`}</span></div>
-    <div class="sensors glass ${CAP.mode === 'witness' ? 'on' : ''}" id="sensors"></div>
+    <div class="cap-top"><span class="st glass">${ic('location', 'xs')}<span>Simulated camera · ${SPOT.name}</span></span><span class="st glass" id="capMode">${{ look: `${ic('eye', 'xs')}Look · AR`, witness: `${ic('key', 'xs')}Witness · signing`, live: `${ic('live', 'xs')}Live · sealed every 10 s`, upload: `${ic('gallery', 'xs')}Upload · unverified` }[m]}</span></div>
+    ${rt ? `<div class="replyto glass">${ic('threads', 'xs')}<span>Replying in <b>${esc(rt.short || rt.title.split(' — ')[0])}</b></span><button id="rtX" aria-label="Cancel reply">${ic('x', 'xs')}</button></div>` : ''}
+    <div class="sensors glass ${m === 'witness' ? 'on' : ''}" id="sensors"></div>
+    <div id="modeHost"></div>
     <div class="cap-bottom">
-      <div class="zooms glass">${[0.5, 1, 3].map((z) => `<button data-z="${z}" class="${CAP.zoom === z ? 'on' : ''}">${z === 0.5 ? '.5' : z}×</button>`).join('')}</div>
-      <div class="dial" id="dial"><button data-m="look" class="${CAP.mode === 'look' ? 'on' : ''}">Look</button><button data-m="witness" class="${CAP.mode === 'witness' ? 'on' : ''}">Witness</button></div>
+      ${m === 'look' || m === 'witness' ? `<div class="zooms glass">${[0.5, 1, 3].map((z) => `<button data-z="${z}" class="${CAP.zoom === z ? 'on' : ''}">${z === 0.5 ? '.5' : z}×</button>`).join('')}</div>` : ''}
+      <div class="dial" id="dial">${CAP.MODES.map(([k, l]) => `<button data-m="${k}" class="${m === k ? 'on' : ''}">${l}</button>`).join('')}</div>
       <div class="shutrow"><button class="lastcap" id="lastcap" aria-label="Last capture" style="${last ? `background-image:url(${last.thumb})` : ''}">${last ? '<svg class="seal"><use href="#i-seal"/></svg>' : ''}</button>
-        <button class="shutter ${CAP.mode === 'look' ? 'look' : ''}" id="shutter" aria-label="${CAP.mode === 'look' ? 'Switch to Witness' : 'Capture and sign'}"><i></i></button>
-        <button class="circ glass" id="capFlip" aria-label="Layers in view">${ic('layers')}</button></div>
+        <button class="shutter s-${m} ${CAP.live?.on ? 'rec' : ''}" id="shutter" aria-label="${{ look: 'Switch to Witness', witness: 'Capture and sign', live: CAP.live?.on ? 'End broadcast' : 'Go live', upload: 'Choose a file' }[m]}"><i></i></button>
+        <button class="circ glass" id="capFlip" aria-label="${m === 'live' ? 'See yourself on the globe' : 'Layers in view'}">${ic(m === 'live' ? 'globe' : 'layers')}</button></div>
     </div></div>`;
   el.querySelectorAll('[data-z]').forEach((b) => b.addEventListener('click', () => { CAP.zoom = +b.dataset.z; CAP.syncZoom(); haptic(4); }));
-  el.querySelectorAll('[data-m]').forEach((b) => b.addEventListener('click', () => { CAP.mode = b.dataset.m; CAP.render(); haptic(6); }));
-  $('#shutter').addEventListener('click', () => { if (CAP.mode === 'look') { CAP.mode = 'witness'; CAP.render(); return; } CAP.shoot(); });
+  el.querySelectorAll('[data-m]').forEach((b) => b.addEventListener('click', () => { CAP.setMode(b.dataset.m); haptic(6); }));
+  $('#rtX')?.addEventListener('click', () => { CAP.replyTo = null; CAP.render(); });
+  $('#shutter').addEventListener('click', () => { if (m === 'look') { CAP.setMode('witness'); return; } if (m === 'witness') CAP.shoot(); if (m === 'live') (CAP.live?.on ? GE.live.stop() : GE.live.start()); if (m === 'upload') $('#upFile')?.click(); });
   $('#lastcap').addEventListener('click', () => { if (GE.captures.length) GE.you.inspect(GE.captures.length - 1); });
-  $('#capFlip').addEventListener('click', () => APP.toast(`${ic('layers', 'sm')} Showing Sky + Orbit in view`));
+  $('#capFlip').addEventListener('click', () => { if (m === 'live') GE.live.showOnGlobe(); else APP.toast(`${ic('layers', 'sm')} Showing Sky + Orbit in view`); });
+  if (m === 'live') GE.live.renderUI($('#modeHost'));
+  if (m === 'upload') GE.upload.renderUI($('#modeHost'));
 };
 CAP.syncZoom = () => $$('#v-capture [data-z]').forEach((x) => x.classList.toggle('on', +x.dataset.z === CAP.zoom));
 
 /* ---------- per-frame AR overlay ---------- */
 CAP.frame = function (view) {
   if (!CAP.on) return;
+  if (CAP.mode === 'live' || CAP.mode === 'upload') { GE.live.frame(); return; }
   const W = GE.world; const t = CAP.t + (performance.now() / 1000 - (CAP._t0 || (CAP._t0 = performance.now() / 1000)));
   const host = $('#callouts'); if (!host) return;
   // compass tape
@@ -158,8 +168,8 @@ CAP.ceremony = function (b, cv) {
     <div class="step" data-s="3"><span class="ck">${ic('check', 'xs')}</span><div><b>Bundle hash</b><div class="h" id="sh3">…</div></div></div>
     <div class="step" data-s="4"><span class="ck">${ic('check', 'xs')}</span><div><b>Signed</b> · ECDSA P-256, key generated on device, non-extractable<div class="h" id="sh4">…</div></div></div>
   </div>
-  <div class="btnrow" id="bbtns" style="opacity:.35;pointer-events:none"><button class="btn gold" id="bdrop">${ic('cube', 'sm')}Drop as hologram here</button></div>
-  <div class="btnrow" id="bbtns2" style="opacity:.35;pointer-events:none"><button class="btn" id="bver">${ic('check', 'sm')}Verify</button><button class="btn" id="bdone">Done</button></div>
+  <div class="btnrow" id="bbtns" style="opacity:.35;pointer-events:none"><button class="btn gold" id="bdrop">${ic('threads', 'sm')}Attach &amp; post</button></div>
+  <div class="btnrow" id="bbtns2" style="opacity:.35;pointer-events:none"><button class="btn" id="bver">${ic('check', 'sm')}Verify</button><button class="btn" id="bdone">Keep private</button></div>
   <p style="margin:0;font-size:11px;color:var(--text3);text-align:center">None of this proves truth. It raises the cost of lying.</p></div>`;
   const ph = $('#bph'); const c2 = document.createElement('canvas'); c2.width = 600; c2.height = 450; c2.getContext('2d').drawImage(cv, 0, 0, 600, 450); ph.prepend(c2);
   ov.classList.add('on');
@@ -173,7 +183,7 @@ CAP.ceremonyFill = async function (b) {
   $(`.step[data-s="4"]`).classList.add('on'); await stream('sh4', b.sig ? b.sig : 'WebCrypto unavailable here — bundle hashed but unsigned'); await step(4);
   $('#bigseal').classList.add('on'); haptic([10, 40, 20]);
   for (const id of ['bbtns', 'bbtns2']) { const e = $('#' + id); e.style.opacity = 1; e.style.pointerEvents = 'auto'; }
-  $('#bdrop').addEventListener('click', () => { GE.world.userHolos.push({ lat: b.lat, lon: b.lon, title: 'Your capture · ' + b.place, by: 'you', at: b.at }); b.dropped = true; $('#sealOv').classList.remove('on'); APP.toast(`${ic('cube', 'sm')} Hologram dropped · visible to people here`); CAP.render(); GE.you.render(); });
+  $('#bdrop').addEventListener('click', () => { $('#sealOv').classList.remove('on'); GE.attach.open({ kind: 'witness', tier: 'sealed', img: b.thumb, lat: b.lat, lon: b.lon, at: b.at, place: b.place, hash: b.hash, cap: b }); });
   $('#bver').addEventListener('click', () => { $('#sealOv').classList.remove('on'); GE.you.inspect(GE.captures.indexOf(b)); });
   $('#bdone').addEventListener('click', () => { $('#sealOv').classList.remove('on'); CAP.render(); GE.you.render(); });
 };
diff --git a/mobile/vision/src/js/66-threads.js b/mobile/vision/src/js/66-threads.js
index 3ba4a986c..8ffcd3528 100644
--- a/mobile/vision/src/js/66-threads.js
+++ b/mobile/vision/src/js/66-threads.js
@@ -156,12 +156,20 @@ THR.init = async function () {
 /* ---------- list ---------- */
 THR.render = function () {
   const v = $('#v-threads');
-  v.innerHTML = `<div class="tlist" id="tlist" style="background:var(--bg);min-height:100%"><div class="navbar">Threads</div><div class="lt"><div class="kicker">${ic('seal', 'xs')} Signed evidence · open ledgers</div><div class="row"><h1>Threads</h1><span class="concept" style="margin-bottom:8px">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
-  <div class="livebar" style="padding-bottom:14px"><span class="presence"><span class="stack">${['kora', 'hydro', 'tamang', 'geo', 'sky'].map((k) => `<span class="avatar sm on" style="--h:${P[k].hue}">${P[k].h[0].toUpperCase()}</span>`).join('')}</span></span><span><b class="num">37</b> people reconstructing now</span></div>
+  v.innerHTML = `<div class="tlist" id="tlist" style="background:var(--bg);min-height:100%"><div class="navbar">Rooms</div><div class="lt"><div class="kicker mono">${ic('threads', 'xs')} CONVERSATIONS ON THE EVIDENCE</div><div class="row"><h1>Rooms</h1><span class="concept" style="margin-bottom:8px">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
+  <div class="livebar" style="padding-bottom:6px"><span class="presence"><span class="stack">${['nadia', 'lin', 'aiko', 'tomas', 'ines'].map((k) => GE.avatarHTML(k)).join('')}</span></span><span><b class="num">${fmt.n(Object.values(GE.rooms.byId).reduce((a, r) => a + r.watching, 0) || 9400)}</b> people in rooms now</span></div>
+  <div class="rooms-why">Every situation has a room. Posts are <b>Witness</b>, <b>Context</b>, <b>Question</b>, <b>Correction</b> or <b>Prediction</b>, ordered by evidence — never by followers.</div>
+  <div class="sec-h"><h2>Live rooms</h2><span>heating up</span></div><div id="roomsLive" class="rooms-live"></div>
+  <div class="sec-h"><h2>Reconstructions</h2><span>4D · signed · open ledgers</span></div>
   ${Object.values(THREADS).map((T) => { const s = GE.SIT.byId[T.sit]; return `<article class="tcard" data-t="${T.id}" data-id="${T.sit}"><div class="thumb"><canvas width="640" height="360"></canvas><div class="bl"><div><h3>${esc(T.title)}</h3><p>${esc(T.place)} · ${esc(T.date)}</p></div><span class="badge d4">4D</span></div></div><div class="stats"><div><b>${T.obs.length}</b>observations</div><div><b>${T.hyps.length}</b>hypotheses</div><div><b>${THR.ledgers[T.id]?.length || '–'}</b>ledger</div><span class="stack">${T.people.slice(0, 4).map((k) => `<span class="avatar sm" style="--h:${P[k].hue}">${P[k].h[0].toUpperCase()}</span>`).join('')}</span></div></article>`; }).join('')}
   <div style="padding:6px 14px 150px"><button class="btn" style="width:100%" id="newThread">${ic('plus', 'sm')}Start a reconstruction</button><p style="font-size:11.5px;color:var(--text3);text-align:center;margin-top:12px">Concept · illustrative data. Witness posts, handles and claims are fictional.</p></div></div>
   <div class="ws" id="ws"></div>`;
   $('#newThread').addEventListener('click', () => APP.toast(`${ic('threads', 'sm')} New thread · add your first observation`));
+  const host = $('#roomsLive'); const sq = GE.feed.squawkTrack();
+  const extra = [{ id: 'room-sq', arch: 'room', band: 'inside', sit: 'squawk', title: 'Squawk 7700 over the North Atlantic', place: 'Diverting to ' + sq.div.iata, lat: sq.cur[0], lon: sq.cur[1], ago: 3, ev: [['cabin', { seed: 81 }], ['track', { track: sq }]] }, { id: 'room-fi', arch: 'room', band: 'inside', sit: 'fires', title: 'Central Portugal fires', place: 'N2 · Pampilhosa da Serra', lat: 40.13, lon: -8.05, ago: 8, ev: [['firewit', { seed: 71 }], ['firesat', {}]] }];
+  const mine = GE.feed.user.filter((x) => x.sit && !['cyclone', 'quake', 'squawk', 'fires'].includes(x.sit)).map((x) => ({ id: 'room-' + x.sit, arch: 'room', band: 'inside', sit: x.sit, title: GE.SIT.byId[x.sit].title, place: GE.SIT.byId[x.sit].place, lat: x.lat, lon: x.lon, ago: 0 }));
+  const items = [...mine, ...GE.feed.items().filter((x) => x.arch === 'room' && !x.recon), ...extra];
+  for (const x of items) { x.at = x.at || NOW - (x.ago || 1) * 60000; x.dist = GE.feed.distFromMe(x.lat, x.lon); x.wide = true; host.append(GE.now.cardEl(x)); }
   $$('.tcard').forEach((c) => {
     c.addEventListener('click', () => THR.openWs(c.dataset.t));
     const cv = c.querySelector('canvas'); const s = GE.SIT.byId[c.dataset.id]; const done = GE.thumbs.done.get(s.id);
diff --git a/mobile/vision/src/js/67-you.js b/mobile/vision/src/js/67-you.js
index d40cf1569..37f23ff80 100644
--- a/mobile/vision/src/js/67-you.js
+++ b/mobile/vision/src/js/67-you.js
@@ -6,10 +6,12 @@ YOU.render = function () {
   const caps = GE.captures; const holos = [...W.userHolos, ...GE.HOLOS.filter((x) => x.by === 'you')];
   v.innerHTML = `<div style="background:var(--bg);min-height:100%;padding-bottom:150px"><div class="navbar">You</div>
   <div class="lt"><div class="kicker">${ic('key', 'xs')} Device key · P-256 · ${GE.crypto.KEY.pair ? 'ready' : 'generating…'}</div><h1>You</h1></div>
-  <div class="you-h"><span class="avatar xl" style="--h:205">Y</span><div><h2>Your window</h2><div style="color:var(--text2);font-size:13px;margin:2px 0 8px">Watching from ${esc(GE.ME.name)} · ${esc(GE.ME.tz)}</div><span class="concept">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
-  <div class="stats4"><div><b>${caps.length}</b>captures</div><div><b>${holos.length}</b>holograms</div><div><b>${Object.values(YOU.follows).filter(Boolean).length}</b>following</div><div><b>${caps.length ? '100%' : '—'}</b>verified</div></div>
+  <div class="you-h"><span class="avatar xl" style="--h:205">Y</span><div><h2>Your eye</h2><div style="color:var(--text2);font-size:13px;margin:2px 0 8px">Watching from ${esc(GE.ME.name)} · ${esc(GE.ME.tz)}</div><span class="concept">${ic('sparkles', 'xs')} Concept · illustrative data</span></div></div>
+  <div class="stats4"><div><b>${GE.feed.user.length}</b>posts</div><div><b>${holos.length}</b>holograms</div><div><b>${Object.values(YOU.follows).filter(Boolean).length}</b>following</div><div><b>${caps.length ? '100%' : '—'}</b>verified</div></div>
   <div class="sec-h"><h2>Captures</h2><span>sealed on this device</span></div>
   <div class="capgrid">${caps.length ? caps.map((c, i) => `<div class="capc" data-c="${i}"><div class="im" style="background-image:url(${c.thumb})"><svg class="seal"><use href="#i-seal"/></svg></div><div class="cm"><b>${esc(c.place)}</b><span class="num">${fmt.utc(c.at)}</span><div class="mono">${c.hash ? c.hash.slice(0, 18) + '…' : 'sealing…'}</div></div></div>`).join('') : `<div style="grid-column:1/-1;color:var(--text3);font-size:14px;padding:6px 4px">No captures yet — open Capture › Witness and press the shutter.</div>`}</div>
+  <div class="sec-h"><h2>Your posts</h2><span>in rooms</span></div>
+  <div class="grp">${GE.feed.user.length ? GE.feed.user.map((x) => { const s = GE.SIT.byId[x.sit]; const p = GE.rooms.byId[x.sit]?.posts.find((q) => q.id === x.post); const t = p?.att?.tier || 'text'; return `<div class="row2" data-post="${x.sit}|${x.post}"><span class="ri" style="--c:var(--b-inside)">${ic(t === 'sealed-live' ? 'live' : t === 'unverified' ? 'gallery' : 'seal')}</span><span class="rt">${esc(x.title)}<small>${esc(s ? (s.short || s.title.split(' — ')[0]) : '')} · ${{ 'sealed-live': 'Sealed live' + (p?.att?.segs ? ' · ' + p.att.segs + ' segments' : ''), sealed: 'Sealed', unverified: 'Unverified upload' }[t] || 'Text'} · ${fmt.ago(Date.now() - x.at)}</small></span><button class="rv">${ic('chevr', 'sm')}</button></div>`; }).join('') : `<div class="row2"><span class="ri" style="--c:var(--b-inside)">${ic('viewfinder')}</span><span class="rt">Nothing posted yet<small>Capture › Witness, Live or Upload, then attach it to a room</small></span></div>`}</div>
   <div class="sec-h"><h2>Holograms</h2><span>left in places</span></div>
   <div class="grp">${(holos.length ? holos : [{ title: 'Drop one from a Witness capture', lat: 0, lon: 0, empty: true }]).map((x) => `<div class="row2"><span class="ri" style="--c:var(--gold)">${ic('cube')}</span><span class="rt">${esc(x.title)}<small>${x.empty ? 'Visible to people nearby' : fmt.ll(x.lat, x.lon, 3) + ' · visible to people nearby'}</small></span>${x.empty ? '' : `<button class="rv" data-fly="${x.lat},${x.lon}">${ic('chevr', 'sm')}</button>`}</div>`).join('')}</div>
   <div class="sec-h"><h2>Following</h2><span>alerts</span></div>
@@ -30,6 +32,7 @@ YOU.render = function () {
   <p style="margin:0"><b>Renderer:</b> hand-written WebGL2 — ray-traced planet with single-scatter atmosphere, day/night terminator from the real sun position, ocean glint, clouds, stars, procedural cities and terrain, GPU-propagated flights and orbits.</p></div></div>`;
   v.scrollTop = st;
   v.querySelectorAll('[data-c]').forEach((el) => el.addEventListener('click', () => YOU.inspect(+el.dataset.c)));
+  v.querySelectorAll('[data-post]').forEach((el) => el.addEventListener('click', () => { const [sid, pid] = el.dataset.post.split('|'); GE.now._item = { band: 'inside', sit: sid }; GE.sheet.open(sid, { post: pid }); }));
   v.querySelectorAll('[data-f]').forEach((el) => el.addEventListener('click', () => { const id = el.dataset.f; YOU.follows[id] = !YOU.follows[id]; el.classList.toggle('on', YOU.follows[id]); el.setAttribute('aria-checked', YOU.follows[id]); store.set('follows', YOU.follows); haptic(5); }));
   v.querySelectorAll('[data-q]').forEach((el) => el.addEventListener('click', () => { const k = el.dataset.q; W.quality[k] = !W.quality[k]; el.classList.toggle('on', W.quality[k]); haptic(5); }));
   v.querySelectorAll('[data-fly]').forEach((el) => el.addEventListener('click', () => { const [la, lo] = el.dataset.fly.split(',').map(Number); APP.setTab('globe'); Cam.flyTo({ lat: la, lon: lo, range: 0.002, tilt: 1.1 }); }));
diff --git a/mobile/vision/src/js/68-room.js b/mobile/vision/src/js/68-room.js
new file mode 100644
index 000000000..cd3455db5
--- /dev/null
+++ b/mobile/vision/src/js/68-room.js
@@ -0,0 +1,143 @@
+/* Room UI (inside the situation sheet): AI synthesis that cites every line, evidence-first posts with
+   earned badges, place + time anchors that fly the globe and scrub the ribbon, community notes with the
+   bridging rule explained, presence + floating reactions, and Reply → Capture first. */
+const RUI = (GE.roomUI = { sort: 'evidence' });
+const KIND_ICON = { witness: 'eye', context: 'layers', question: 'bubble', correction: 'flag', prediction: 'clock' };
+const tierLabel = (a) => ({ 'sealed-live': `SEALED LIVE${a.segs ? ' · ' + a.segs + ' SEGMENTS' : ''}`, sealed: 'SEALED', unverified: 'UNVERIFIED UPLOAD', eye: 'PUBLIC CAMERA' })[a.tier] || a.tier.toUpperCase();
+function citeChips(cites) { return (cites || []).map((c) => `<button class="cite" data-cite="${c}">${c}</button>`).join(''); }
+RUI.postHTML = function (room, p) {
+  const who = GE.PEOPLE[p.by] || { h: p.by, hue: 205 }; const K = GE.rooms.KINDS[p.kind]; const pid = GE.rooms.pid(room, p);
+  const bd = GE.rooms.badges(room, p).map(([k, l]) => `<span class="bdg ${k}">${k === 'sealed' ? ic('seal', 'xs') : ''}${esc(l)}</span>`).join('');
+  const att = p.att ? `<div class="patt ${p.att.tier}"><canvas width="${p.att.img ? 480 : 480}" height="300" data-att></canvas><span class="tier">${p.att.tier.startsWith('sealed') ? ic('seal', 'xs') : ''}${tierLabel(p.att)}</span>${p.live ? '<span class="plive"><span class="dot pulse"></span>LIVE</span>' : ''}</div>` : '';
+  const anc = [p.place ? `<button class="anc" data-anc="place">${ic('location', 'xs')}${esc(p.place.label)}</button>` : '', `<button class="anc" data-anc="time">${ic('clock', 'xs')}${fmt.hm(p.time || p.at)}Z</button>`].join('');
+  const ans = p.answered ? (() => { const a = room.posts.find((q) => q.id === p.answered); return a ? `<div class="answered">${ic('check', 'xs')}Answered by <b>@${esc(GE.PEOPLE[a.by].h)}</b> · ${GE.rooms.badges(room, a).map(([, l]) => esc(l)).join(' · ')}</div>` : ''; })() : p.kind === 'question' ? `<div class="answered open">${ic('arrowup', 'xs')}Open question · pinned to the top until someone answers with evidence</div>` : '';
+  const note = p.note ? `<div class="note"><div class="nh">${ic('people', 'xs')}Readers added context</div><p>${esc(p.note.text)} ${citeChips(p.note.cites)}</p>
+    <div class="bridge"><div class="br"><span>Raters who usually lean <b>A</b></span><i style="--v:${p.note.helpfulA}"></i><b class="num">${Math.round(p.note.helpfulA * 100)}%</b></div><div class="br"><span>Raters who usually lean <b>B</b></span><i style="--v:${p.note.helpfulB}"></i><b class="num">${Math.round(p.note.helpfulB * 100)}%</b></div></div>
+    <details><summary>Why is this note showing?</summary><p>A note only appears when people who usually <i>disagree</i> with each other both rate it helpful. Raters are grouped by how they have voted on past notes, not by what they say about themselves. Here ${p.note.ratersA} raters from one side and ${p.note.ratersB} from the other agreed, so it is shown. Brigading by one side can't make a note visible.</p></details></div>` : '';
+  const rx = p.reacts || {}; const rxs = [['eye', rx.eye], ['heart', rx.heart], ['exclamation', rx.alert]].filter(([, n]) => n).map(([i, n]) => `<button class="rxb" data-rx="${i}">${ic(i, 'xs')}<span class="num">${fmt.k(n)}</span></button>`).join('');
+  return `<article class="post k-${p.kind}${p.note ? ' noted' : ''}${p.mine ? ' mine' : ''}" data-p="${p.id}">
+    <div class="ph">${GE.avatarHTML(p.by)}<div class="pw"><div><b>@${esc(who.h)}</b><span class="pid">${pid}</span><span class="tm">${fmt.ago(Date.now() - p.at)}</span></div><div class="bds">${bd}</div></div><span class="kind k-${p.kind}">${ic(KIND_ICON[p.kind], 'xs')}${K.name.toUpperCase()}</span></div>
+    <div class="pt">${esc(p.text)}${p.resolves ? `<span class="resolves">resolves ${esc(p.resolves)}</span>` : ''}</div>
+    ${att}<div class="ancs">${anc}${citeChips(p.cites)}</div>${note}${ans}
+    <div class="pf">${rxs}<span class="rep">${ic('bubble', 'xs')}<span class="num">${p.replies || 0}</span></span><button class="rcap" data-reply>${ic('viewfinder', 'xs')}Reply with a capture</button></div></article>`;
+};
+RUI.synthHTML = function (room) {
+  const S = room.synth; const sec = (k, lab, cls) => (S[k] || []).length ? `<div class="sy ${cls}"><b>${lab}</b>${S[k].map(([t, c]) => `<p>${esc(t)} ${citeChips(c)}</p>`).join('')}</div>` : `<div class="sy ${cls}"><b>${lab}</b><p class="none">Nothing ${k} right now.</p></div>`;
+  const L = room.ledger; const last = room.synthEntry || L[L.length - 1];
+  return `<div class="synth" id="synth"><div class="syh">${ic('sparkles', 'xs')}<span>AI synthesis · every line cites a post or an observation</span><button class="regen" id="regen">${ic('wand', 'xs')}Re-synthesize</button></div>
+    <div id="syBody">${sec('known', 'KNOWN', 'kn')}${sec('disputed', 'DISPUTED', 'di')}${sec('unknown', 'UNKNOWN', 'un')}</div>
+    <div class="syf mono" id="syFoot">${room.synthModel ? esc(room.synthModel) + ' · ' : ''}${room.dropped ? room.dropped + ' uncited line removed · ' : ''}prompt + ${room.posts.length + Object.keys(room.src || {}).length} inputs in the ledger${last ? ` · #${last.i} ${last.hash.slice(0, 10)}…` : ''}</div></div>`;
+};
+RUI.render = function (host, s, o = {}) {
+  const room = GE.rooms.get(s.id); RUI.room = room; RUI.sit = s;
+  const list = GE.rooms.ordered(room, RUI.sort);
+  host.innerHTML = `${RUI.synthHTML(room)}
+    <div class="sortrow"><span class="sl mono">ORDER</span>${[['evidence', 'Evidence first'], ['latest', 'Latest'], ['questions', 'Questions']].map(([k, l]) => `<button class="chip sm ${RUI.sort === k ? 'on' : ''}" data-sort="${k}">${l}</button>`).join('')}</div>
+    <div class="posts" id="posts">${list.map((p) => RUI.postHTML(room, p)).join('')}</div>
+    <div class="srcs room-srcs"><div class="h3">Sources in this room</div>${Object.entries(room.src || {}).map(([k, v]) => `<div class="r"><span class="tagid">${k}</span><b style="font-weight:500">${esc(v)}</b></div>`).join('')}</div>
+    <p class="fine">Posts are ordered by evidence, then time — never by followers. Concept · illustrative data; people and posts are fictional.</p>`;
+  RUI.bind(host, room, s);
+  if (o.post) setTimeout(() => RUI.focusPost(o.post, true), 60);
+};
+RUI.bind = function (host, room, s) {
+  host.querySelectorAll('[data-sort]').forEach((b) => b.addEventListener('click', () => { RUI.sort = b.dataset.sort; RUI.render(host, s); haptic(4); }));
+  $('#regen')?.addEventListener('click', () => RUI.resynth(room, s));
+  host.querySelectorAll('.post').forEach((el) => {
+    const p = room.posts.find((q) => q.id === el.dataset.p);
+    const cv = el.querySelector('[data-att]'); if (cv && p.att) RUI.paintAtt(cv, p);
+    el.addEventListener('click', (e) => {
+      const b = e.target.closest('button, summary, details'); if (b && !b.matches('[data-anc]')) return;
+      RUI.anchor(p, b?.dataset.anc); });
+    el.querySelector('[data-reply]')?.addEventListener('click', (e) => { e.stopPropagation(); RUI.replyCapture(s, p); });
+    el.querySelectorAll('[data-rx]').forEach((b) => b.addEventListener('click', (e) => { e.stopPropagation(); RUI.float(b.dataset.rx); const k = { eye: 'eye', heart: 'heart', exclamation: 'alert' }[b.dataset.rx]; p.reacts = p.reacts || {}; p.reacts[k] = (p.reacts[k] || 0) + 1; b.querySelector('.num').textContent = fmt.k(p.reacts[k]); haptic(4); }));
+  });
+  host.querySelectorAll('[data-cite]').forEach((b) => b.addEventListener('click', (e) => { e.stopPropagation(); RUI.cite(b.dataset.cite); }));
+};
+RUI.paintAtt = function (cv, p) {
+  if (p.att.img) { const im = new Image(); im.onload = () => { const cx = cv.getContext('2d'); const sc = Math.max(cv.width / im.width, cv.height / im.height); cx.drawImage(im, (cv.width - im.width * sc) / 2, (cv.height - im.height * sc) / 2, im.width * sc, im.height * sc); }; im.src = p.att.img; return; }
+  const draw = () => GE.paint.draw(p.att.paint, cv, { ...p.att.o, t: performance.now() / 1000 });
+  GE.thumbs.enqueue(draw);
+  if (GE.paint.animated(p.att.paint)) { RUI.animCvs = RUI.animCvs || new Set(); RUI.animCvs.add([cv, p]); }
+};
+setInterval(() => { if (!RUI.animCvs || APP.mode !== 'situation') return; for (const e of RUI.animCvs) { const [cv, p] = e; if (!document.body.contains(cv)) { RUI.animCvs.delete(e); continue; } const r = cv.getBoundingClientRect(); if (r.bottom < 0 || r.top > innerHeight) continue; GE.paint.draw(p.att.paint, cv, { ...p.att.o, t: performance.now() / 1000 }); } }, 160);
+RUI.focusPost = function (id, fly) {
+  const el = $(`.post[data-p="${id}"]`); if (!el) return; el.classList.add('hl'); setTimeout(() => el.classList.remove('hl'), 2200);
+  const sc = $('#sheetC'); if (sc && GE.sheet.detent === 'large') sc.scrollTo({ top: el.offsetTop - 80, behavior: 'smooth' });
+  if (fly) { const p = RUI.room.posts.find((q) => q.id === id); if (p?.place) RUI.anchor(p, 'place', true); }
+};
+RUI.anchor = function (p, which, quiet) {
+  const W = GE.world; const s = RUI.sit;
+  if (p.place && which !== 'time') { const wide = APP.isWide(); const hs = GE.sheet.heights(); Cam.flyTo({ lat: p.place.lat - 0.12, lon: p.place.lon - 0.05, range: 0.03, heading: 0.4, tilt: 0.95, shiftY: wide ? 0 : hs[GE.sheet.detent === 'large' ? 'medium' : GE.sheet.detent] / hs.H, shiftX: 0 }, { duration: 1.8 }); GE.roomUI.labels(s, p.id); }
+  const at = p.time || p.at; if (which !== 'place') W.setTime(at);
+  if (!quiet) APP.toast(`${ic(p.place && which !== 'time' ? 'location' : 'clock', 'sm')} ${p.place && which !== 'time' ? esc(p.place.label) + ' · ' : ''}${fmt.hm(at)} UTC · ${fmt.ago(Date.now() - at)}`);
+  if (GE.sheet.detent === 'large' && !APP.isWide()) GE.sheet.setDetent('medium');
+  haptic(5);
+};
+RUI.cite = function (c) {
+  const room = RUI.room; if (!room) return;
+  if (c[0] === 'P') { const p = GE.rooms.byPid(room, c); if (p) { if (GE.sheet.detent !== 'large' && !APP.isWide()) GE.sheet.setDetent('large'); setTimeout(() => RUI.focusPost(p.id), 120); } return; }
+  if (c[0] === 'N') { const p = room.posts.find((q) => q.note); if (p) { if (GE.sheet.detent !== 'large' && !APP.isWide()) GE.sheet.setDetent('large'); setTimeout(() => RUI.focusPost(p.id), 120); } return; }
+  APP.toast(`${ic('hash', 'sm')} ${c} · ${esc((room.src || {})[c] || 'observation')}`, 2600);
+};
+// speech glyphs on the globe for anchored posts
+RUI.labels = function (s, hl) {
+  const room = GE.rooms.get(s.id); for (const k of [...GE.extraLabels.keys()]) if (k.startsWith('p:')) GE.extraLabels.delete(k);
+  for (const p of room.posts) { if (!p.place) continue; const who = GE.PEOPLE[p.by] || { h: p.by }; GE.extraLabels.set('p:' + p.id, { lat: p.place.lat, lon: p.place.lon, alt: 0.03, html: `<i class="sg k-${p.kind}">${ic(KIND_ICON[p.kind], 'xs')}</i><span>@${esc(who.h)}</span>`, w: who.h.length * 6.4 + 46, cls: 'glass speech' + (p.id === hl ? ' hl' : ''), onclick: () => { if (GE.sheet.detent === 'peek') GE.sheet.setDetent('medium'); RUI.focusPost(p.id); } }); }
+};
+/* presence & reactions */
+RUI.float = function (icon) { const host = $('#rx'); if (!host) return; const sp = h('span', { html: ic(icon || ['heart', 'eye', 'heart', 'exclamation', 'bolt'][Math.floor(Math.random() * 5)], 'sm'), style: `--dx:${(Math.random() - 0.5) * 30}px` }); sp.dataset.i = icon || ''; host.append(sp); setTimeout(() => sp.remove(), 2700); };
+setInterval(() => { if (APP.mode === 'situation' && GE.sheet.seg === 'room' && !document.hidden) { if (Math.random() < 0.7) RUI.float(); const w = $('#sheetC [data-watch]'); if (w && RUI.room) w.textContent = fmt.n(RUI.room.watching); } }, 900);
+
+/* composer: Capture first, text second */
+RUI.composer = function (show) {
+  const c = $('#roomComp'); if (!c) return; c.classList.toggle('on', !!show); if (!show) return;
+  if (c.dataset.bound) return; c.dataset.bound = '1';
+  c.innerHTML = `<button class="capbtn" id="rcCap" aria-label="Reply with a capture">${ic('viewfinder')}<span>Capture</span></button><div class="rcin glass"><div class="kinds" id="rcKinds">${Object.entries(GE.rooms.KINDS).map(([k, K]) => `<button data-k="${k}" class="${k === 'context' ? 'on' : ''}">${ic(KIND_ICON[k], 'xs')}${K.name}</button>`).join('')}</div><div class="rcrow"><input id="rcText" placeholder="Add context, ask, correct…" autocomplete="off"><button class="send" id="rcSend" aria-label="Post">${ic('arrowup', 'sm')}</button></div></div>`;
+  let kind = 'context';
+  c.querySelectorAll('[data-k]').forEach((b) => b.addEventListener('click', () => { kind = b.dataset.k; c.querySelectorAll('[data-k]').forEach((x) => x.classList.toggle('on', x === b)); haptic(3); }));
+  $('#rcCap').addEventListener('click', () => RUI.replyCapture(RUI.sit));
+  const inp = $('#rcText'); inp.addEventListener('focus', () => c.classList.add('typing')); inp.addEventListener('blur', () => setTimeout(() => c.classList.remove('typing'), 150));
+  inp.addEventListener('keydown', (e) => { if (e.key === 'Enter') { e.preventDefault(); $('#rcSend').click(); } });
+  $('#rcSend').addEventListener('click', async () => {
+    const t = inp.value.trim(); if (!t || !RUI.room) return; inp.value = '';
+    const p = { id: 'u' + Date.now(), kind, by: 'you', at: Date.now(), text: t, mine: true, reacts: {}, replies: 0 };
+    RUI.room.posts.push(p); const e = await GE.rooms.append(RUI.room, 'post.' + kind, 'you', { id: p.id, text: t });
+    RUI.render($('#shSeg'), RUI.sit); setTimeout(() => RUI.focusPost(p.id), 80);
+    APP.toast(`${ic('link', 'sm')} Posted · ledger #${e.i} · text ranks below evidence`, 2600); haptic(8);
+  });
+};
+RUI.replyCapture = function (s, p) {
+  GE.capture.replyTo = { sit: s.id, post: p?.id };
+  APP.toast(`${ic('viewfinder', 'sm')} Capture a reply for ${esc(s.short || s.title.split(' — ')[0])}`, 2000);
+  GE.sheet.close(true); APP.setTab('capture'); GE.capture.setMode('witness');
+};
+
+/* AI synthesis: window.claude sample on click, scripted fallback; uncited lines are dropped */
+RUI.resynth = async function (room, s, o = {}) {
+  const btn = $('#regen'); if (!btn || btn.disabled) return; btn.disabled = true; btn.classList.add('busy');
+  const body = $('#syBody'); const foot = $('#syFoot');
+  const posts = room.posts.map((p) => `[${GE.rooms.pid(room, p)}] ${GE.rooms.KINDS[p.kind].name} by @${(GE.PEOPLE[p.by] || { h: p.by }).h} (${GE.rooms.badges(room, p).map((b) => b[1]).join(', ') || 'no evidence badges'}), ${fmt.ago(Date.now() - p.at)}: ${p.text}${p.note ? ` — Community note [N1]: ${p.note.text}` : ''}`).join('\n');
+  const srcs = Object.entries(room.src || {}).map(([k, v]) => `[${k}] ${v}`).join('\n');
+  const prompt = `You summarise a live discussion about a real-world situation for an app that separates evidence from claims.\nSituation: ${s.title} — ${s.place}. Posts and people are illustrative.\nObservations:\n${srcs}\nPosts:\n${posts}\nWrite at most 6 lines, each starting with exactly one of "KNOWN:", "DISPUTED:" or "UNKNOWN:". Every line must end with one or more citations in square brackets like [P1] [O2] [N1]. Prefer sealed witness posts and observations over unverified posts. Never state anything you cannot cite. Plain text, no markdown.`;
+  body.innerHTML = '<div class="sy kn"><b>WRITING</b><p class="stream" id="syStream">…</p></div>';
+  let out = '', model = 'scripted fallback (no AI available here)';
+  const show = (t) => { out = t; const el = $('#syStream'); if (el) el.textContent = t || '…'; };
+  let sample = null; if (!o.auto) { try { sample = window.claude?.use ? await window.claude.use('sample') : null; } catch { sample = null; } }
+  if (o.auto) model = 'auto-update (scripted) · tap Re-synthesize to ask AI';
+  if (sample) { try { const r = await sample(prompt, { onText: ({ text }) => show(text) }); show(r?.text ?? out); model = 'claude · window.claude sample'; } catch { sample = null; } }
+  if (!sample) {
+    const S = room.synth; const lines = [...S.known.map(([t, c]) => `KNOWN: ${t} ${c.map((x) => `[${x}]`).join(' ')}`), ...S.disputed.map(([t, c]) => `DISPUTED: ${t} ${c.map((x) => `[${x}]`).join(' ')}`), ...S.unknown.map(([t, c]) => `UNKNOWN: ${t} ${c.map((x) => `[${x}]`).join(' ')}`)];
+    const mine = room.posts.filter((p) => p.mine && p.att); if (mine.length) { const p = mine[mine.length - 1]; lines.splice(1, 0, `KNOWN: A new ${p.att.tier.startsWith('sealed') ? 'sealed' : 'unverified'} capture from @you at ${p.place?.label || 'the scene'} adds a view of the situation. [${GE.rooms.pid(room, p)}]`); }
+    lines.push('UNKNOWN: Whether conditions improve in the next hour — the posts do not say.');
+    const full = lines.join('\n'); for (let i = 1; i <= full.length; i += 4) { show(full.slice(0, i)); await new Promise((r) => setTimeout(r, prefersReduced() ? 0 : 8)); } show(full);
+  }
+  // parse: keep only cited lines
+  const next = { known: [], disputed: [], unknown: [] }; let dropped = 0;
+  for (const ln of out.split('\n')) { const m = /^\s*(KNOWN|DISPUTED|UNKNOWN)\s*:\s*(.+)$/i.exec(ln); if (!m) continue; const cites = [...m[2].matchAll(/\[([PONS]\d+)\]/g)].map((x) => x[1]); const text = m[2].replace(/\s*\[[^\]]+\]/g, '').trim(); if (!cites.length) { dropped++; continue; } next[m[1].toLowerCase()].push([text, [...new Set(cites)]]); }
+  if (next.known.length + next.disputed.length + next.unknown.length) room.synth = next;
+  room.dropped = dropped; room.synthModel = model;
+  const e = await GE.rooms.append(room, 'ai.synthesis', 'claude', { prompt: await sha256(prompt), inputs: room.posts.map((p) => GE.rooms.pid(room, p)).concat(Object.keys(room.src || {})), model, output: await sha256(out), dropped });
+  room.synthEntry = e;
+  const wrap = $('#synth'); if (wrap) { wrap.outerHTML = RUI.synthHTML(room); $('#regen')?.addEventListener('click', () => RUI.resynth(room, s)); $('#synth').querySelectorAll('[data-cite]').forEach((b) => b.addEventListener('click', (ev) => { ev.stopPropagation(); RUI.cite(b.dataset.cite); })); }
+  APP.toast(`${ic('sparkles', 'sm')} Synthesis recorded · ledger #${e.i}${dropped ? ' · ' + dropped + ' uncited line dropped' : ''}`, 2800);
+};
diff --git a/mobile/vision/src/js/69-live.js b/mobile/vision/src/js/69-live.js
new file mode 100644
index 000000000..124781470
--- /dev/null
+++ b/mobile/vision/src/js/69-live.js
@@ -0,0 +1,266 @@
+/* Live, Upload and the Attach sheet.
+   Live: a simulated broadcast (rendered lakefront in a gale) that seals a segment every 10 s into a real
+   SHA-256 hash chain signed with the device key; you appear on the globe as an eye with a view cone.
+   Upload: a real file input; EXIF GPS/time are read with a tiny parser; you place it on a map; it is
+   labelled Unverified everywhere. Attach: suggests where it belongs, kind, precision, hologram; posting
+   lands in the room, the feed and on the globe. */
+const LV = (GE.live = { on: false, segs: [], viewers: 0 });
+GE.capture.live = LV;
+const CAPm = GE.capture; const SPOTm = CAPm.spot;
+/* ---------- eyes on the globe (people and cameras that are looking right now) ---------- */
+GE.EYES = [
+  { id: 'basco', lat: 20.4485, lon: 121.9705, hdg: 205, fov: 64, label: '@nadia_basco', kind: 'witness', live: true, sit: 'cyclone', post: 'cy1' },
+  { id: 'kaoh', lat: 22.612, lon: 120.268, hdg: 250, fov: 72, label: 'HBR-07', kind: 'cctv', sit: 'cyclone', post: 'cy5' },
+  { id: 'shib', lat: 35.6597, lon: 139.7002, hdg: 135, fov: 84, label: 'CAM 0412', kind: 'cctv', sit: 'shibuya' },
+  { id: 'ines', lat: 40.13, lon: -8.05, hdg: 80, fov: 60, label: '@ines_coimbra', kind: 'witness', sit: 'fires', post: 'fi1' },
+  { id: 'ola', lat: 69.649, lon: 18.957, hdg: 10, fov: 74, label: '@ola_tromso', kind: 'witness', sit: 'aurora' },
+  { id: 'sak', lat: 31.597, lon: 130.56, hdg: 95, fov: 48, label: 'VOLCANO CAM 2', kind: 'cctv', sit: 'sakurajima' },
+  { id: 'rafa', lat: 18.357, lon: 121.637, hdg: 40, fov: 60, label: '@rafa_aparri', kind: 'witness', sit: 'cyclone', post: 'cy6' },
+];
+GE.eyeLines = function (rangeR) {
+  const out = []; const D = clamp((rangeR || 1) * EARTH_KM * 0.07, 0.25, 420);
+  for (const e of GE.EYES) {
+    const col = e.kind === 'you' ? [1, 0.86, 0.5, 0.95] : e.kind === 'cctv' ? [1, 0.66, 0.26, 0.7] : [0.96, 0.82, 0.48, 0.8];
+    const tip = geo.vec(e.lat, e.lon, 0.03 + D * 0.004); const half = (e.fov / 2) * D2R; const h0 = e.hdg * D2R; const cs = [];
+    for (const [da, z] of [[-half, 0], [half, 0], [half, D * 0.32], [-half, D * 0.32]]) { const [la, lo] = geo.dest(e.lat, e.lon, h0 + da, D); cs.push(geo.vec(la, lo, z)); }
+    for (const c of cs) out.push({ pts: [tip, c], col });
+    out.push({ pts: [...cs, cs[0]], col: [col[0], col[1], col[2], col[3] * 0.8] });
+    const mid = geo.dest(e.lat, e.lon, h0, D); out.push({ pts: [tip, geo.vec(mid[0], mid[1], D * 0.16)], col: [col[0], col[1], col[2], 0.35], dashed: 1 });
+  }
+  return out;
+};
+
+/* ---------- Live ---------- */
+const CHAT_LIVE = [['amara', 'Same at Oak Street — the trail is underwater'], ['kora', 'Stay back from the edge please 🙏'], ['sky', 'That spray must be 8 m'], ['geo', 'Buoy says 3.4 m waves, matches what we see'], ['hydro', 'Is the harbour gate closed?'], ['amara', 'Streaming this into the gale room'], ['ais', 'Two freighters sheltering off the breakwater'], ['kora', 'The sealed badge is so reassuring tbh']];
+const nearestSits = (lat, lon, n = 3) => GE.SIT.list.filter((s) => !s.dyn).map((s) => ({ s, km: RM.kmBetween(lat, lon, s.lat, s.lon) })).sort((a, b) => a.km - b.km).slice(0, n);
+LV.renderUI = function (host) {
+  const near = nearestSits(SPOTm.lat, SPOTm.lon, 2); LV.sit = near[0].s;
+  if (!LV.on) {
+    host.innerHTML = `<div class="lv-pre glass strong"><div class="lvph"><span class="lvpill pre"><i></i>READY</span><b>Go live as a sealed eye</b></div>
+      <p>Your camera becomes a sensor on the globe. Every 10 seconds the stream is sealed into a hash chain and signed on this device, with GPS, heading and motion. Rooms nearby can watch.</p>
+      <div class="lvnear">${near.map(({ s, km }) => `<span>${ic('threads', 'xs')}${esc(s.short || s.title.split(' — ')[0])} · ${GE.feed.fmtDist(km)}</span>`).join('')}</div>
+      <div class="lvfine mono">SIMULATED CAMERA · RENDERED SCENE · NO CAMERA OR MIC IS USED</div></div>`;
+    return;
+  }
+  host.innerHTML = `<div class="lv-top"><span class="lvpill"><i></i>LIVE <b class="num" id="lvT">00:00</b></span><span class="lvv glass">${ic('eye', 'xs')}<b class="num" id="lvV">${LV.viewers}</b></span><span class="lvseal">${ic('seal', 'xs')}SEALED LIVE</span></div>
+    <div class="lv-to glass">${ic('threads', 'xs')}<span>In the <b>${esc(LV.sit.short || LV.sit.title)}</b> room · ${GE.feed.fmtDist(RM.kmBetween(SPOTm.lat, SPOTm.lon, LV.sit.lat, LV.sit.lon))}</span></div>
+    <div class="lv-chat" id="lvChat"></div><div class="lvrx" id="lvRx"></div>
+    <div class="lv-tele mono" id="lvTele"></div><div class="lv-chain" id="lvChain"></div>`;
+  LV.drawChain(); LV.chatRestore();
+};
+LV.start = async function () {
+  if (LV.on) return; await GE.crypto.KEY.get();
+  Object.assign(LV, { on: true, t0: Date.now(), segT: Date.now(), segs: [], viewers: 3, prev: '0'.repeat(64), chat: [], hdg: 64 });
+  GE.EYES.push({ id: 'you', lat: SPOTm.lat, lon: SPOTm.lon, hdg: LV.hdg, fov: 62, label: 'You · LIVE', kind: 'you', live: true, sit: LV.sit?.id });
+  LV.timer = setInterval(() => LV.seal(), 10000); LV.soc = setInterval(() => LV.social(), 1500);
+  haptic([10, 30, 10]); CAPm.render(); APP.renderAccessory(); APP.toast(`${ic('live', 'sm')} You’re live · first segment seals in 10 s`);
+};
+LV.stop = function () {
+  if (!LV.on) return; clearInterval(LV.timer); clearInterval(LV.soc); LV.on = false; LV.t1 = Date.now();
+  const me = GE.EYES.find((e) => e.id === 'you'); if (me) { me.live = false; me.label = 'You · replay'; }
+  CAPm.render(); APP.renderAccessory();
+  const seg = LV.segs[LV.segs.length - 1];
+  GE.attach.open({ kind: 'witness', tier: 'sealed-live', img: LV.posterImg || seg?.thumb, lat: SPOTm.lat, lon: SPOTm.lon, at: LV.t0, place: SPOTm.name, segs: LV.segs.length, dur: (LV.t1 - LV.t0) / 1000, hash: seg?.hash, hdg: LV.hdg, live: true });
+};
+LV.seal = async function () {
+  const cv = $('#liveCv'); const small = GE.paint.mk(320, 180);
+  if (cv && cv.width) small.getContext('2d').drawImage(cv, 0, 0, 320, 180); else GE.paint.draw('seawall', small, { skyline: true, noOSD: true, seed: 53, t: performance.now() / 1000 });
+  const blob = await new Promise((r) => small.toBlob(r, 'image/jpeg', 0.7)); const bytes = new Uint8Array(await blob.arrayBuffer());
+  const seg = { i: LV.segs.length, t0: LV.segT, t1: Date.now(), frame: await sha256(bytes), bytes: bytes.length, gps: { lat: +SPOTm.lat.toFixed(6), lon: +SPOTm.lon.toFixed(6), acc: 4 }, hdg: LV.hdg, imu: 500, prev: LV.prev };
+  seg.hash = await sha256(canon(seg)); seg.sig = await GE.crypto.signHex(seg.hash); seg.thumb = small.toDataURL('image/jpeg', 0.6);
+  if (!LV.posterImg) { const pc = GE.paint.mk(480, 300); pc.getContext('2d').drawImage(cv || small, 0, 0, 480, 300); LV.posterImg = pc.toDataURL('image/jpeg', 0.8); }
+  LV.segs.push(seg); LV.prev = seg.hash; LV.segT = seg.t1; haptic(6);
+  LV.drawChain(true); APP.renderAccessory();
+};
+LV.drawChain = function (flash) {
+  const host = $('#lvChain'); if (!host) return;
+  const blocks = LV.segs.map((s) => `<div class="seg ok" title="segment ${s.i} · ${s.hash}"><span class="si mono">#${String(s.i + 1).padStart(3, '0')}</span><img src="${s.thumb}" alt=""><span class="sh mono">${s.hash.slice(0, 8)}</span><span class="sk">${ic('seal', 'xs')}${s.sig ? 'signed' : 'hashed'}</span></div>`).join('<i class="ln"></i>');
+  host.innerHTML = `${blocks}${LV.segs.length ? '<i class="ln"></i>' : ''}<div class="seg cur"><span class="si mono">#${String(LV.segs.length + 1).padStart(3, '0')}</span><div class="fill"><i id="lvFill"></i></div><span class="sh mono">sealing…</span></div>`;
+  host.scrollLeft = host.scrollWidth; if (flash) host.lastElementChild.previousElementSibling?.previousElementSibling?.classList.add('flash');
+};
+LV.social = function () {
+  if (!LV.on) return; LV.viewers += 1 + Math.floor(Math.random() * (LV.viewers > 60 ? 18 : 6));
+  const chat = $('#lvChat'); const k = Math.floor((Date.now() - LV.t0) / 1500);
+  const ev = k % 3 === 0 ? { join: ['amara', 'kora', 'sky', 'geo', 'hydro', 'ais', 'ola'][k % 7] } : { msg: CHAT_LIVE[k % CHAT_LIVE.length] };
+  LV.chat.push(ev); if (LV.chat.length > 4) LV.chat.shift(); if (chat) LV.chatRestore();
+  const rx = $('#lvRx'); if (rx) for (let i = 0; i < 2; i++) { const sp = h('span', { html: ic(['heart', 'eye', 'heart', 'bolt'][Math.floor(Math.random() * 4)], 'sm'), style: `--dx:${(Math.random() - 0.5) * 30}px` }); rx.append(sp); setTimeout(() => sp.remove(), 2700); }
+};
+LV.chatRestore = function () {
+  const chat = $('#lvChat'); if (!chat) return;
+  chat.innerHTML = LV.chat.map((e) => e.join ? `<div class="lj">${GE.avatarHTML(e.join)}<span><b>@${esc(GE.PEOPLE[e.join].h)}</b> joined</span></div>` : `<div class="bub">${GE.avatarHTML(e.msg[0])}<div class="bx glass"><b>@${esc(GE.PEOPLE[e.msg[0]].h)}</b>${esc(e.msg[1])}</div></div>`).join('');
+};
+LV.frame = function () {
+  const cv = $('#liveCv'); if (!cv || CAPm.mode !== 'live') return;
+  const W0 = Math.round(cv.clientWidth * 0.8), H0 = Math.round(cv.clientHeight * 0.8); if (!W0 || !H0) return;
+  if (cv.width !== W0 || cv.height !== H0) { cv.width = W0; cv.height = H0; }
+  const now = performance.now(); if (LV._lf && now - LV._lf < 40) return; LV._lf = now;
+  GE.paint.draw('seawall', cv, { skyline: true, handheld: true, noOSD: true, seed: 53, t: now / 1000 });
+  if (!LV.on) return;
+  const tEl = $('#lvT'); if (tEl) tEl.textContent = fmt.dur((Date.now() - LV.t0) / 1000).slice(3);
+  const vEl = $('#lvV'); if (vEl) vEl.textContent = fmt.n(LV.viewers);
+  const f = $('#lvFill'); if (f) f.style.width = clamp((Date.now() - LV.segT) / 10000, 0, 1) * 100 + '%';
+  const te = $('#lvTele'); if (te) te.textContent = `${GE.feed.llz(SPOTm.lat, SPOTm.lon)} · HDG ${String(LV.hdg + Math.round(Math.sin(now / 900) * 3)).padStart(3, '0')}° · ±4 M · ALT 182 M · SEG ${String(LV.segs.length + 1).padStart(3, '0')} · ${GE.feed.hmsZ()}`;
+};
+LV.showOnGlobe = function () {
+  const back = LV.on; APP.setTab('globe'); Cam.flyTo({ lat: SPOTm.lat - 0.035, lon: SPOTm.lon - 0.05, range: 0.016, heading: 0.75, tilt: 1.0, shiftY: 0.06, shiftX: 0 }, { duration: 2.4 });
+  APP.toast(back ? `${ic('eye', 'sm')} That cone is you — still live` : `${ic('eye', 'sm')} Your view cone on the globe`, 2600);
+};
+
+/* ---------- EXIF (read + write) ---------- */
+const EX = (GE.exif = {});
+EX.parse = function (buf) {
+  try {
+    const v = new DataView(buf); if (v.getUint16(0) !== 0xffd8) return null; let o = 2;
+    while (o < v.byteLength - 4) { const m = v.getUint16(o); if ((m & 0xff00) !== 0xff00) break; const len = v.getUint16(o + 2); if (m === 0xffe1 && v.getUint32(o + 4) === 0x45786966) return EX.tiff(v, o + 10); if (m === 0xffda) break; o += 2 + len; }
+  } catch (e) { console.warn('exif', e); }
+  return null;
+};
+EX.tiff = function (v, t) {
+  const le = v.getUint16(t) === 0x4949; const u16 = (p) => v.getUint16(p, le), u32 = (p) => v.getUint32(p, le);
+  const ifd = (p) => { const n = u16(p); const e = {}; for (let i = 0; i < n; i++) { const q = p + 2 + i * 12; e[u16(q)] = { type: u16(q + 2), count: u32(q + 4), off: q + 8 }; } return e; };
+  const val = (en) => {
+    if (!en) return null; const { type, count } = en; const size = { 1: 1, 2: 1, 3: 2, 4: 4, 5: 8, 7: 1, 9: 4, 10: 8 }[type] || 1; const p = size * count > 4 ? t + u32(en.off) : en.off;
+    if (type === 2) { let s = ''; for (let i = 0; i < count; i++) { const c = v.getUint8(p + i); if (!c) break; s += String.fromCharCode(c); } return s.trim(); }
+    if (type === 5 || type === 10) { const out = []; for (let i = 0; i < count; i++) { const a = type === 5 ? u32(p + i * 8) : v.getInt32(p + i * 8, le), b = type === 5 ? u32(p + i * 8 + 4) : v.getInt32(p + i * 8 + 4, le); out.push(b ? a / b : 0); } return count === 1 ? out[0] : out; }
+    if (type === 3) return u16(p); if (type === 4) return u32(p); return v.getUint8(p);
+  };
+  const i0 = ifd(t + u32(t + 4)); const out = { make: val(i0[0x010f]), model: val(i0[0x0110]), date: val(i0[0x0132]) };
+  if (i0[0x8769]) { const ex = ifd(t + val(i0[0x8769])); out.date = val(ex[0x9003]) || out.date; }
+  if (i0[0x8825]) { const g = ifd(t + val(i0[0x8825])); const dms = (a) => (a && a.length === 3 ? a[0] + a[1] / 60 + a[2] / 3600 : null); const la = dms(val(g[2])), lo = dms(val(g[4])); if (la != null && lo != null) { out.lat = la * (val(g[1]) === 'S' ? -1 : 1); out.lon = lo * (val(g[3]) === 'W' ? -1 : 1); } const al = val(g[6]); if (al != null) out.alt = al; }
+  return out;
+};
+EX.when = (s) => { const m = /^(\d{4}):(\d\d):(\d\d) (\d\d):(\d\d):(\d\d)/.exec(s || ''); return m ? Date.UTC(+m[1], +m[2] - 1, +m[3], +m[4], +m[5], +m[6]) : null; };
+// write a little-endian TIFF/EXIF block with Make, Model, DateTimeOriginal and GPS (used by the sample)
+EX.build = function ({ make, model, date, lat, lon, alt }) {
+  const B = []; const u8 = (x) => B.push(x & 255), u16 = (x) => { u8(x); u8(x >> 8); }, u32 = (x) => { u16(x & 0xffff); u16(x >>> 16); };
+  const str = (s) => { const a = [...new TextEncoder().encode(s), 0]; if (a.length % 2) a.push(0); return a; };
+  const mk = str(make), md = str(model), dt = str(date);
+  const IFD0 = 8, D0 = IFD0 + 2 + 5 * 12 + 4, pMk = D0, pMd = pMk + mk.length, pDt = pMd + md.length, EXIF = pDt + dt.length, pDo = EXIF + 2 + 12 + 4, GPS = pDo + dt.length, pLa = GPS + 2 + 7 * 12 + 4, pLo = pLa + 24, pAl = pLo + 24;
+  const ent = (tag, type, count, v) => { u16(tag); u16(type); u32(count); u32(v); };
+  const asc2 = (c) => c.charCodeAt(0);
+  u16(0x4949); u16(42); u32(IFD0);
+  u16(5); ent(0x010f, 2, mk.length - (mk[mk.length - 1] === 0 && mk[mk.length - 2] === 0 ? 1 : 0), pMk); ent(0x0110, 2, md.length - (md[md.length - 1] === 0 && md[md.length - 2] === 0 ? 1 : 0), pMd); ent(0x0132, 2, 20, pDt); ent(0x8769, 4, 1, EXIF); ent(0x8825, 4, 1, GPS); u32(0);
+  B.push(...mk, ...md, ...dt);
+  u16(1); ent(0x9003, 2, 20, pDo); u32(0); B.push(...dt);
+  u16(7); ent(0, 1, 4, 0x00000302); ent(1, 2, 2, asc2(lat >= 0 ? 'N' : 'S')); ent(2, 5, 3, pLa); ent(3, 2, 2, asc2(lon >= 0 ? 'E' : 'W')); ent(4, 5, 3, pLo); ent(5, 1, 1, 0); ent(6, 5, 1, pAl); u32(0);
+  const rat = (x) => { const d = Math.floor(x), mm = Math.floor((x - d) * 60), ss = Math.round(((x - d) * 60 - mm) * 60 * 100); u32(d); u32(1); u32(mm); u32(1); u32(ss); u32(100); };
+  rat(Math.abs(lat)); rat(Math.abs(lon)); u32(Math.round((alt || 0) * 10)); u32(10);
+  const tiff = new Uint8Array(B); const seg = new Uint8Array(4 + 6 + tiff.length); const L = 2 + 6 + tiff.length;
+  seg.set([0xff, 0xe1, L >> 8, L & 255, 0x45, 0x78, 0x69, 0x66, 0, 0]); seg.set(tiff, 10); return seg;
+};
+EX.inject = (jpeg, app1) => { const out = new Uint8Array(jpeg.length + app1.length); out.set(jpeg.subarray(0, 2)); out.set(app1, 2); out.set(jpeg.subarray(2), 2 + app1.length); return out; };
+const exifDate = (ms) => { const d = new Date(ms); const z = (n) => String(n).padStart(2, '0'); return `${d.getUTCFullYear()}:${z(d.getUTCMonth() + 1)}:${z(d.getUTCDate())} ${z(d.getUTCHours())}:${z(d.getUTCMinutes())}:${z(d.getUTCSeconds())}`; };
+
+/* ---------- Upload ---------- */
+const UP = (GE.upload = { f: null });
+UP.renderUI = function (host) {
+  const f = UP.f;
+  if (!f) {
+    host.innerHTML = `<div class="up glass strong"><div class="uph"><b>Add a photo or video of a place</b><span class="tierb unv">UNVERIFIED</span></div>
+      <p>Uploads weren’t sealed when they were taken, so they carry an <b>Unverified</b> label everywhere. A hypothesis can cite one, but it can never become an observation.</p>
+      <label class="drop"><input type="file" id="upFile" accept="image/*,video/*" hidden>${ic('gallery', 'lg')}<b>Choose from your library</b><span>A JPEG with location in its EXIF places itself</span></label>
+      <button class="btn sm" id="upSample" style="width:100%">${ic('sparkles', 'sm')}No photo handy? Use a sample with GPS in its EXIF</button>
+      <p class="fine mono">READ LOCALLY WITH FILEREADER · NOTHING LEAVES THIS PAGE</p></div>`;
+    $('#upFile').addEventListener('change', (e) => { const file = e.target.files && e.target.files[0]; if (file) UP.load(file); });
+    $('#upSample').addEventListener('click', () => UP.sample());
+    return;
+  }
+  const ex = f.exif || {}; const has = f.lat != null;
+  host.innerHTML = `<div class="up glass strong loaded"><div class="upimg"><img src="${f.img}" alt="Your upload"><span class="tierb unv">UNVERIFIED</span></div>
+    <div class="exif mono"><div><span>FILE</span><b>${esc(f.name)} · ${fmt.k(f.size / 1024)} KB</b></div><div><span>CAMERA</span><b>${esc([ex.make, ex.model].filter(Boolean).join(' ') || '—')}</b></div><div><span>TAKEN</span><b>${ex.date ? esc(ex.date) : '—'}</b></div><div><span>GPS</span><b>${ex.lat != null ? GE.feed.llz(ex.lat, ex.lon) + ' · from EXIF' : 'none in file — place it'}</b></div></div>
+    <div class="placer"><canvas id="upMap" width="640" height="300"></canvas><div class="pin" id="upPin">${ic('location', 'sm')}</div><div class="hint mono" id="upLL"></div></div>
+    <div class="uptime"><span>When</span><input type="range" id="upT" min="-4320" max="0" step="5" value="${Math.round(((f.at || Date.now()) - Date.now()) / 60000)}"><b class="num" id="upTv"></b></div>
+    <div class="btnrow"><button class="btn sm" id="upRe">Choose another</button><button class="btn gold sm" id="upGo">${ic('threads', 'sm')}Continue</button></div></div>`;
+  UP.drawMap(); UP.bindPin();
+  const t = $('#upT'); const tv = $('#upTv'); const upd = () => { f.at = Date.now() + +t.value * 60000; tv.textContent = `${fmt.hm(f.at)} UTC · ${fmt.ago(Date.now() - f.at)}`; }; t.addEventListener('input', upd); upd();
+  $('#upRe').addEventListener('click', () => { UP.f = null; UP.renderUI(host); });
+  $('#upGo').addEventListener('click', () => GE.attach.open({ kind: 'witness', tier: 'unverified', img: f.img, lat: f.lat, lon: f.lon, at: f.at, place: f.name, upload: true }));
+};
+UP.load = function (file) {
+  const r = new FileReader();
+  r.onload = () => {
+    const buf = r.result; const ex = file.type === 'image/jpeg' || /\.jpe?g$/i.test(file.name) ? EX.parse(buf) : null;
+    const f = { name: file.name || 'upload', size: file.size, type: file.type, exif: ex, lat: ex?.lat ?? null, lon: ex?.lon ?? null, at: EX.when(ex?.date) || file.lastModified || Date.now() };
+    if (f.lat == null) { f.lat = GE.ME.lat; f.lon = GE.ME.lon; f.guess = true; }
+    const url = URL.createObjectURL(file);
+    const done = (cv) => { f.img = cv.toDataURL('image/jpeg', 0.82); UP.f = f; URL.revokeObjectURL(url); UP.renderUI($('#modeHost')); APP.toast(ex?.lat != null ? `${ic('location', 'sm')} Placed from EXIF GPS · ${GE.feed.llz(f.lat, f.lon)}` : `${ic('location', 'sm')} No GPS in this file — drag the pin`, 2600); };
+    if (file.type.startsWith('video')) { const v = document.createElement('video'); v.muted = true; v.playsInline = true; v.src = url; v.addEventListener('loadeddata', () => { v.currentTime = Math.min(0.5, v.duration / 2 || 0); }, { once: true }); v.addEventListener('seeked', () => { const cv = GE.paint.mk(640, Math.round(640 * (v.videoHeight / v.videoWidth || 0.56))); cv.getContext('2d').drawImage(v, 0, 0, cv.width, cv.height); done(cv); }, { once: true }); v.addEventListener('error', () => APP.toast('Could not read that video here'), { once: true }); return; }
+    const im = new Image(); im.onload = () => { const sc = Math.min(1, 1280 / Math.max(im.width, im.height)); const cv = GE.paint.mk(im.width * sc, im.height * sc); cv.getContext('2d').drawImage(im, 0, 0, cv.width, cv.height); done(cv); }; im.onerror = () => APP.toast('Could not read that image'); im.src = url;
+  };
+  r.onerror = () => APP.toast('Could not read that file'); r.readAsArrayBuffer(file);
+};
+UP.sample = async function () {
+  const cv = GE.paint.mk(1200, 900); GE.paint.draw('volcano', cv, { noOSD: true, t: 1 });
+  const blob = await new Promise((r) => cv.toBlob(r, 'image/jpeg', 0.86)); const jpg = new Uint8Array(await blob.arrayBuffer());
+  const app1 = EX.build({ make: 'Concept', model: 'Sample Phone', date: exifDate(Date.now() - 23 * 60000), lat: 31.5937, lon: 130.5626, alt: 4.2 });
+  const file = new File([EX.inject(jpg, app1)], 'IMG_4021.JPG', { type: 'image/jpeg', lastModified: Date.now() - 20 * 60000 }); UP.load(file);
+};
+UP.drawMap = function () {
+  const f = UP.f; const cv = $('#upMap'); if (!cv) return; const span = 4.2; const mv = GE.paint.mapView(f.lat, f.lon, span, cv.width, cv.height); UP.mv = mv;
+  const ctx = cv.getContext('2d'); GE.paint.mapBase(ctx, mv, { lights: 1.1, relief: 0.8, land: '#18202b', sea: '#05080c', coast: '#5b6e86' }); GE.paint.graticule(ctx, mv, 1);
+  for (const { s, km } of nearestSits(f.lat, f.lon, 6)) { const x = mv.X(s.lon), y = mv.Y(s.lat); if (x < 0 || y < 0 || x > cv.width || y > cv.height) continue; ctx.fillStyle = '#FF6A3D'; ctx.beginPath(); ctx.arc(x, y, 6, 0, TAU); ctx.fill(); GE.paint.label(ctx, (s.short || s.title).toUpperCase(), x + 10, y, 15, '#fff'); }
+  GE.paint.scaleBar(ctx, mv, 50, 18, cv.height - 18);
+};
+UP.bindPin = function () {
+  const f = UP.f; const pin = $('#upPin'), cv = $('#upMap'); const place = () => { const r = cv.getBoundingClientRect(); const sx = r.width / cv.width; pin.style.left = UP.mv.X(f.lon) * sx + 'px'; pin.style.top = UP.mv.Y(f.lat) * sx + 'px'; $('#upLL').textContent = `${GE.feed.llz(f.lat, f.lon)} · ${f.guess ? 'GUESSED — DRAG ME' : f.moved ? 'PLACED BY YOU' : 'FROM EXIF'}`; };
+  requestAnimationFrame(place); let drag = false;
+  const mv = (e) => { if (!drag) return; const r = cv.getBoundingClientRect(); const sx = cv.width / r.width; const x = clamp((e.clientX - r.left) * sx, 0, cv.width), y = clamp((e.clientY - r.top) * sx, 0, cv.height); f.lat = UP.mv.lat(y); f.lon = UP.mv.lon(x); f.moved = true; f.guess = false; place(); };
+  pin.addEventListener('pointerdown', (e) => { drag = true; pin.setPointerCapture(e.pointerId); e.preventDefault(); }); pin.addEventListener('pointermove', mv); pin.addEventListener('pointerup', () => { drag = false; haptic(4); });
+  cv.addEventListener('click', (e) => { drag = true; mv(e); drag = false; });
+};
+
+/* ---------- Attach sheet ---------- */
+const AT = (GE.attach = {});
+const bandOfFam = (f) => ({ orbit: 'orbit', sky: 'sky', wx: 'sky', eyes: 'ground' })[f] || 'ground';
+AT.open = function (c) {
+  AT.c = c; const near = nearestSits(c.lat, c.lon, 3); const pre = CAPm.replyTo?.sit || (near[0].km < 400 ? near[0].s.id : 'new');
+  AT.sel = pre; AT.kind = c.kind || 'witness'; AT.prec = c.upload ? '100' : 'exact'; AT.holo = !c.upload;
+  const opts = [...(CAPm.replyTo && !near.some((n) => n.s.id === CAPm.replyTo.sit) ? [{ s: GE.SIT.byId[CAPm.replyTo.sit], km: RM.kmBetween(c.lat, c.lon, GE.SIT.byId[CAPm.replyTo.sit].lat, GE.SIT.byId[CAPm.replyTo.sit].lon) }] : []), ...near];
+  const tier = c.tier === 'sealed-live' ? `SEALED LIVE · ${c.segs} SEGMENTS · ${fmt.dur(c.dur || 0).slice(3)}` : c.tier === 'sealed' ? 'SEALED · ECDSA P-256' : 'UNVERIFIED UPLOAD';
+  const ov = $('#attachOv');
+  ov.innerHTML = `<div class="att glass strong"><div class="grab"></div>
+    <div class="ath"><div class="atimg"><img src="${c.img || ''}" alt=""><span class="tierb ${c.tier === 'unverified' ? 'unv' : ''}">${c.tier === 'unverified' ? '' : ic('seal', 'xs')}${tier}</span></div><div><h2>Where does this belong?</h2><p class="mono">${GE.feed.llz(c.lat, c.lon)} · ${fmt.hm(c.at)} UTC${c.hash ? ' · ' + c.hash.slice(0, 10) + '…' : ''}</p></div></div>
+    <div class="ath2">Suggested from where and when it was taken</div>
+    <div class="sugs">${opts.map(({ s, km }) => `<button class="sug ${AT.sel === s.id ? 'on' : ''}" data-s="${s.id}" style="--c:${GE.BANDS[bandOfFam(s.fam)].c}"><i></i><span><b>${esc(s.short || s.title.split(' — ')[0])}</b><small>${GE.feed.fmtDist(km)} away · ${s.live ? 'live now' : 'replay'} · ${fmt.k(GE.rooms.watching(s.id))} in room</small></span><em>${ic('check', 'xs')}</em></button>`).join('')}
+      <button class="sug ${AT.sel === 'new' ? 'on' : ''}" data-s="new" style="--c:#fff"><i></i><span><b>New place</b><small>Start a room at ${GE.feed.llz(c.lat, c.lon)}</small></span><em>${ic('check', 'xs')}</em></button></div>
+    <div class="ath2">Post as</div><div class="kinds2">${Object.entries(GE.rooms.KINDS).map(([k, K]) => `<button data-k="${k}" class="${AT.kind === k ? 'on' : ''}">${K.name}</button>`).join('')}</div>
+    <textarea id="atNote" rows="2" placeholder="${c.live ? 'Waves are coming over the lakefront trail…' : 'What does this show? (optional)'}"></textarea>
+    <div class="ath2">Share location as</div><div class="prec">${[['exact', 'Exact'], ['100', '100 m'], ['1000', '1 km']].map(([k, l]) => `<button data-p="${k}" class="${AT.prec === k ? 'on' : ''}">${l}</button>`).join('')}</div>
+    <p class="fine2">${c.tier === 'unverified' ? 'An upload has no seal, so precision is all anyone gets.' : 'The seal still proves the exact point to verifiers without publishing it.'}</p>
+    <div class="row2 holo"><span class="ri" style="--c:var(--b-inside)">${ic('cube')}</span><span class="rt">Leave it here as a hologram<small>People who come to this spot later can find it</small></span><button class="sw2 ${AT.holo ? 'on' : ''}" id="atHolo" role="switch" aria-label="Hologram"></button></div>
+    <p class="fine2 priv">${ic('eyeslash', 'xs')} Faces and plates are blurred on-device before upload in the native build. This web concept does not blur — a disclosed limitation.</p>
+    <div class="btnrow"><button class="btn" id="atX">Cancel</button><button class="btn gold" id="atGo">${ic('arrowup', 'sm')}Post</button></div></div>`;
+  ov.classList.add('on');
+  ov.querySelectorAll('[data-s]').forEach((b) => b.addEventListener('click', () => { AT.sel = b.dataset.s; ov.querySelectorAll('[data-s]').forEach((x) => x.classList.toggle('on', x === b)); AT.label(); haptic(4); }));
+  ov.querySelectorAll('[data-k]').forEach((b) => b.addEventListener('click', () => { AT.kind = b.dataset.k; ov.querySelectorAll('[data-k]').forEach((x) => x.classList.toggle('on', x === b)); haptic(3); }));
+  ov.querySelectorAll('[data-p]').forEach((b) => b.addEventListener('click', () => { AT.prec = b.dataset.p; ov.querySelectorAll('[data-p]').forEach((x) => x.classList.toggle('on', x === b)); haptic(3); }));
+  $('#atHolo').addEventListener('click', (e) => { AT.holo = !AT.holo; e.currentTarget.classList.toggle('on', AT.holo); });
+  $('#atX').addEventListener('click', () => ov.classList.remove('on'));
+  $('#atGo').addEventListener('click', () => AT.post());
+  AT.label();
+};
+AT.label = function () { const b = $('#atGo'); if (!b) return; const s = GE.SIT.byId[AT.sel]; b.innerHTML = `${ic('arrowup', 'sm')}Post to ${esc(s ? (s.short || s.title.split(' — ')[0]) : 'a new room')}`; };
+AT.post = async function () {
+  const c = AT.c; let sitId = AT.sel;
+  if (sitId === 'new') { sitId = 'mine-' + Date.now(); GE.SIT.list.push({ id: sitId, short: 'Your place', fam: 'eyes', kind: 'place', title: 'New place · ' + (c.place || 'your capture'), place: GE.feed.llz(c.lat, c.lon), lat: c.lat, lon: c.lon, camera: { lat: c.lat - 0.01, lon: c.lon - 0.01, range: 0.01, heading: 0.4, tilt: 1.0 }, layers: ['signed', 'holo', 'cctv'], source: 'You', live: true, watchers: 12, updatedAt: Date.now(), metric: () => ['', ''], metrics: () => [{ v: 1, u: '', l: 'Captures', s: 'You' }, { v: 0, u: '', l: 'Replies', s: '' }, { v: '—', u: '', l: 'Nearby rooms', s: '' }], brief: { lede: 'A place you started. Others nearby will see it.', series: [], sources: [] } }); GE.SIT.byId[sitId] = GE.SIT.list[GE.SIT.list.length - 1]; }
+  const s = GE.SIT.byId[sitId]; const room = GE.rooms.get(sitId);
+  const q = AT.prec === 'exact' ? 0 : AT.prec === '100' ? 0.001 : 0.01; const rd = (x) => (q ? Math.round(x / q) * q : x);
+  const km = RM.kmBetween(c.lat, c.lon, s.lat, s.lon);
+  const note = ($('#atNote').value || '').trim() || (c.live ? 'Live from the lakefront: waves are breaking over the trail and the path is closed.' : c.upload ? 'Photo from my library, placed from its EXIF.' : 'Sealed capture from here.');
+  const p = { id: 'y' + Date.now(), kind: AT.kind, by: 'you', at: c.at || Date.now(), text: note, mine: true, place: { lat: rd(c.lat), lon: rd(c.lon), label: c.place || 'Your capture' }, att: { img: c.img, tier: c.tier, segs: c.segs, distKm: c.tier === 'unverified' ? null : Math.min(km, 4.9) }, reacts: {}, replies: 0, prec: AT.prec };
+  if (CAPm.replyTo?.post) p.replyTo = CAPm.replyTo.post;
+  room.posts.push(p); const e = await GE.rooms.append(room, 'post.' + AT.kind, 'you', { id: p.id, text: note, att: { tier: c.tier, hash: c.hash || null, segs: c.segs || 0 }, place: p.place, precision: AT.prec });
+  // feed
+  const tierT = c.tier === 'sealed-live' ? 'SEALED LIVE' : c.tier === 'sealed' ? 'SEALED' : 'UNVERIFIED';
+  GE.feed.user.unshift({ id: 'f' + p.id, mine: true, arch: 'witness', band: 'inside', sit: sitId, post: p.id, by: 'you', img: c.img, aspect: 0.75, title: note.length > 90 ? note.slice(0, 88) + '…' : note, place: c.place || s.place, lat: c.lat, lon: c.lon, ago: 0, at: Date.now(), dist: 0, prio: 999,
+    tele: () => `WITNESS · ${tierT} · ${AT.prec === 'exact' ? '±4 M' : AT.prec === '100' ? '±100 M' : '±1 KM'} · ${GE.feed.fmtDist(km).toUpperCase()} FROM EVENT` });
+  // globe: hologram + an eye with a cone for sealed captures
+  if (AT.holo) GE.world.userHolos.push({ lat: rd(c.lat), lon: rd(c.lon), title: 'Your capture · ' + (c.place || ''), by: 'you', at: c.at });
+  if (c.tier !== 'unverified' && !GE.EYES.some((x) => x.id === 'you')) GE.EYES.push({ id: 'you', lat: c.lat, lon: c.lon, hdg: c.hdg ?? 64, fov: 62, label: 'You', kind: 'you', sit: sitId, post: p.id });
+  const me = GE.EYES.find((x) => x.id === 'you'); if (me) { me.sit = sitId; me.post = p.id; }
+  $('#attachOv').classList.remove('on'); CAPm.replyTo = null; if (c.upload) UP.f = null;
+  GE.now.renderRail?.(); GE.now.renderFeed(); GE.you.render();
+  APP.toast(`${ic('threads', 'sm')} Posted to ${esc(s.short || s.title.split(' — ')[0])} · ledger #${e.i}`, 2600); haptic([8, 30, 8]);
+  GE.now._item = { band: 'inside', sit: sitId }; APP.setTab('globe', { force: true });
+  setTimeout(() => { GE.sheet.open(sitId, { post: p.id }); setTimeout(() => GE.roomUI.resynth(GE.rooms.get(sitId), s, { auto: true }), 900); }, 250);
+};
diff --git a/mobile/vision/src/js/90-main.js b/mobile/vision/src/js/90-main.js
index 5a431c6f5..e70785ab8 100644
--- a/mobile/vision/src/js/90-main.js
+++ b/mobile/vision/src/js/90-main.js
@@ -34,7 +34,8 @@ function frame(now) {
   W.simMs = Date.now() + W.offsetH * 3600000; W.t = (W.simMs - NOW) / 1000; W.sun = astro.sun(W.simMs);
   Cam.update(dt);
   if (APP.mode === 'situation' && !Cam.anim && GE.sheet.targetShift != null && !APP.isWide()) Cam.shiftY += (GE.sheet.targetShift - Cam.shiftY) * Math.min(1, dt * 7);
-  if (globeVisible()) {
+  if (globeVisible() && GE.capture.on && GE.capture.cover && !APP.isWide()) { GE.capture.frame(null); }
+  else if (globeVisible()) {
     const [cw, chh] = sizeCanvas();
     if (now - lastDyn > 40) { W.updateDynamic(); lastDyn = now; }
     const view = Cam.view(cw, chh); GE.mainView = view;
@@ -50,36 +51,52 @@ function frame(now) {
 }
 document.addEventListener('visibilitychange', () => { if (document.hidden) running = false; else if (!running) { running = true; lastT = performance.now(); requestAnimationFrame(frame); } });
 
-/* ---------- cold open ---------- */
+/* ---------- cold open: a descent from orbit to a person's sealed frame ---------- */
 function coldOpen() {
   const cold = $('#cold'); const app = $('#app');
   const skipAll = HASH.nointro || HASH.tab;
   const red = prefersReduced();
   W.sun = astro.sun(Date.now()); const finalCam = APP.heroCam();
+  const CITIES2 = [{ lat: 40.7585, lon: -73.9855, name: '7TH AVE & W 45TH ST', cam: { lat: 40.7525, lon: -73.9905, range: 0.0016, heading: 0.62, tilt: 1.18 } }, { lat: 35.6595, lon: 139.7005, name: 'SHIBUYA SCRAMBLE', cam: { lat: 35.652, lon: 139.694, range: 0.0024, heading: 0.6, tilt: 1.12 } }, { lat: 41.8789, lon: -87.6359, name: 'STATE & MADISON', cam: { lat: 41.872, lon: -87.643, range: 0.0018, heading: 0.6, tilt: 1.15 } }, { lat: 51.5136, lon: -0.1365, name: 'OXFORD CIRCUS', cam: { lat: 51.508, lon: -0.143, range: 0.0024, heading: 0.6, tilt: 1.12 } }];
+  const tgt = CITIES2.map((c) => ({ c, e: astro.elev(Date.now(), c.lat, c.lon) })).sort((a, b) => a.e - b.e)[0].c;
+  let ended = false;
   const end = () => {
-    if (!APP.intro) return; APP.intro = false; GE.introFade = 1; W.setTime(null);
+    if (ended) return; ended = true; APP.intro = false; GE.introFade = 1; W.setTime(null);
     cold.classList.add('out'); app.classList.remove('intro'); setTimeout(() => cold.remove(), 1100);
-    Cam.cancel(); if (Cam.range > 2.2 && !APP.isWide()) Cam.flyTo(finalCam, { duration: 0.6 });
+    Cam.cancel(); Cam.set(finalCam); if (!APP.isWide()) { Cam.set({ ...finalCam, range: finalCam.range * 0.7 }); Cam.flyTo(finalCam, { duration: 1.2 }); }
     Cam.autoSpin = 0.3; APP.updateChrome(); APP.moveLens();
     if (HASH.tab) APP.setTab(HASH.tab, { force: true });
   };
   APP.intro = true; app.classList.add('intro'); APP.updateChrome();
   if (skipAll) { Cam.set(finalCam); end(); return; }
-  Cam.set({ lat: 8, lon: finalCam.lon + 75, range: 5.8, heading: 0, tilt: 0, shiftY: 0.0, shiftX: 0 });
-  const T = (red ? 1.2 : 3.4) * (HASH.slow ? +HASH.slow : 1); const t0 = performance.now();
-  GE.introFade = 0;
-  if (!red) Cam.flyTo(finalCam, { duration: T });
+  const k = HASH.slow ? +HASH.slow : 1; const TA = (red ? 0.2 : 4.4) * k, TB = TA + 0.8 * k, TC = TB + 2.4 * k;
+  if (!red) { Cam.set({ lat: tgt.lat - 18, lon: tgt.lon - 50, range: 6.4, heading: 0, tilt: 0, shiftY: 0, shiftX: 0 }); Cam.flyTo({ ...tgt.cam, shiftY: 0, shiftX: 0 }, { duration: TA * 0.95 }); }
   else Cam.set(finalCam);
+  GE.introFade = 0; const t0 = performance.now(); const cv = $('#coldCv'); $('#coldTele').textContent = `WITNESS · SEALED · ±4 M · ${tgt.name}`;
+  const caps = [[120, 'ORBIT · GEO IR · 35,786 KM'], [30, 'ORBIT · ISS · 412 KM · 7.66 KM/S'], [0.8, 'SKY · FL350 · 487 KT · ADS-B'], [-1, 'GROUND · CAM 0412 · 1.2 KM']];
+  const pos = (altKm) => clamp(1 - (Math.log10(Math.max(0.05, altKm)) + 1.3) / (Math.log10(36000) + 1.3), 0, 1) * 0.72;
   const tick = () => {
-    if (!APP.intro) return; const u = clamp((performance.now() - t0) / 1000 / T, 0, 1);
-    GE.introFade = ease.out(clamp(u * 2.2, 0, 1));
-    if (!red) W.setTime(Date.now() - (1 - ease.outQuint(u)) * 9 * 3600000);
-    if (u > 0.12) cold.classList.add('s1'); if (u > 0.36) cold.classList.add('s2');
-    if (u >= 1) { setTimeout(end, red ? 200 : 500); return; } requestAnimationFrame(tick);
+    if (ended) return; const el = (performance.now() - t0) / 1000;
+    GE.introFade = ease.out(clamp(el / 1.2, 0, 1)); cold.classList.add('s0');
+    const alt = GE.mainView ? Math.max(0.05, geo.ll(GE.mainView.eye)[2]) : 36000;
+    const lad = $('#ladder'); const H = lad.clientHeight;
+    if (el < TA) {
+      const band = alt > 120 ? 'orbit' : alt > 0.8 ? 'sky' : 'ground';
+      lad.querySelectorAll('.lr').forEach((r) => r.classList.toggle('on', r.dataset.b === band));
+      $('#lmark').style.top = (pos(alt) * H).toFixed(1) + 'px';
+      $('#coldAlt').textContent = 'ALT ' + (alt >= 10 ? fmt.n(Math.round(alt)) + ' KM' : alt >= 1 ? alt.toFixed(1) + ' KM' : fmt.n(Math.round(alt * 1000)) + ' M');
+      const cp = caps.find(([a]) => alt > a) || caps[3]; $('#coldCap').textContent = cp[1];
+    } else {
+      cold.classList.add('s3'); lad.querySelectorAll('.lr').forEach((r) => r.classList.toggle('on', r.dataset.b === 'inside')); $('#lmark').style.top = H - 8 + 'px';
+      GE.paint.draw('crossing', cv, { seed: 31, cam: '@', rec: false, noOSD: true, osdY: -1, t: el });
+      if (el > TB) cold.classList.add('s4');
+      if (el > TC) { setTimeout(end, 300); return; }
+    }
+    requestAnimationFrame(tick);
   };
   requestAnimationFrame(tick);
-  $('#skip').addEventListener('click', (e) => { e.stopPropagation(); Cam.set(finalCam); end(); });
-  cold.addEventListener('click', () => { Cam.set(finalCam); end(); });
+  $('#skip').addEventListener('click', (e) => { e.stopPropagation(); end(); });
+  cold.addEventListener('click', () => end());
 }
 
 /* ---------- boot ---------- */