Graham McIntire
e82e631135
- HrrrClient.hrrr_url accepts forecast_hour param (wrfsfcfHH.grib2) - PropagationGridWorker fetches all 19 forecast hours per run - Propagation.scores_at/3 queries scores at specific valid_time - Propagation.available_valid_times/1 returns all forecast times for timeline - Pruning keeps scores with valid_time >= now - 2h (forecast-aware) - MapLive: select_time event, timeline data pushed to JS - JS: forecast timeline bar at bottom of map with clickable hour buttons - PubSub broadcast sends list of valid_times instead of single time
81 lines
5.3 KiB
Markdown
81 lines
5.3 KiB
Markdown
# GOES-R Satellite Data for Propagation Prediction
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## Summary
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**Verdict: Low priority. GOES-R data is already baked into HRRR, and the satellite cannot resolve the vertical gradients that cause ducting.**
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## What is "GOES-R Rapid Refresh"?
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There is no product called "GOES-R Rapid Refresh" or "GRR." These are two separate systems:
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- **GOES-R** — geostationary satellite series (GOES-16, 17, 18, 19) with the Advanced Baseline Imager (ABI)
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- **HRRR** — High-Resolution Rapid Refresh, a ground-based NWP model
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They are complementary: NOAA assimilates GOES-R satellite observations (cloud-top data, satellite winds) into the HRRR model. By consuming HRRR output, we are already indirectly consuming GOES-R data — processed through full 3D physics.
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## Relevant GOES-R Products
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| Product | Resolution | Cadence | Clear Sky Only? | Relevance |
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|---------|-----------|---------|-----------------|-----------|
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| Derived Stability Indices (K-Index, LI, CAPE) | 10 km | 5 min | Yes | Moderate — but K-index inversely correlated with ducting per our analysis |
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| Total Precipitable Water | 10 km | 5 min | Yes | Low — our analysis found PWAT is NOT a ducting discriminator |
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| Vertical Temperature Profile | 10 km | 5 min | Yes | **Very low** — see critical caveat below |
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| Vertical Moisture Profile | 10 km | 5 min | Yes | Same limitation as temperature |
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| Land Surface Temperature | 2 km | 5 min | Yes | Minor — land-sea contrasts drive coastal ducting |
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| Sea Surface Temperature | 2 km | hourly | Yes | Same — coastal ducting indicator |
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| Rain Rate | 2 km | 5 min | No | Redundant — HRRR already provides precip |
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| Derived Motion Winds | varies | 5 min | Partially | Redundant — HRRR already provides wind fields |
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| Cloud Imagery (water vapor) | 2 km | 1-5 min | No | Visual supplement only — moisture plume tracking |
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## Critical Limitation: Cannot Resolve Ducting
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The ABI is an imager with 16 spectral bands, not a hyperspectral sounder. Key problems:
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1. **The "vertical profiles" lean heavily on the NWP model first guess.** The ABI lacks the spectral resolution to independently resolve temperature/moisture structure. The 54-level temperature profile sounds impressive, but with only 16 IR bands, the independent information content is very low. The retrieved profiles "retain features of the first guess" — meaning they're essentially a slightly nudged version of the same NWP model we're already using.
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2. **Ducting requires detecting gradients over 50-200m vertical scales.** The ABI simply cannot resolve this. A 100m-thick temperature inversion looks identical to a smooth profile from the satellite's perspective.
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3. **Clear-sky only.** All the useful derived products (TPW, stability indices, profiles) only work under cloud-free conditions. HRRR gives us data everywhere, always.
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## Comparison: What GOES-R Adds vs. What We Have
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| What We Need | HRRR (current) | GOES-R (proposed) |
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|---|---|---|
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| Surface temp/dewpoint | 3 km, hourly, all-sky | 10 km, 5 min, clear-sky only |
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| Vertical profiles | 8 pressure levels with T/Td/height, all-sky | 54 levels but low information content, clear-sky only |
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| Refractivity gradient | Computed from HRRR profiles — our key ducting indicator | Cannot resolve the vertical structure needed |
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| Boundary layer depth | HPBL from model physics | No direct product |
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| Wind | 10m wind components, all-sky | Cloud-tracked winds at various levels |
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| Precipitation | Model physics + radar assimilation | IR-only rain rate (less accurate) |
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| Forecast capability | 18-48 hours ahead | None — observation only |
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## Where GOES-R Could Help (Minor)
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**Real-time nowcasting between HRRR cycles:** HRRR updates hourly with ~60 min latency, meaning displayed data can be up to 2+ hours old. GOES-R's 5-minute cadence could fill the gap for:
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- Cloud cover changes (water vapor imagery)
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- Rapid destabilization (stability indices flagging convective onset)
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- Land-sea temperature contrasts (coastal ducting indicator)
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These would be supplementary monitoring products, not improvements to the core scoring algorithm.
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## Data Access
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All GOES-R data is freely available on AWS S3 (no auth):
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- `s3://noaa-goes19/` (current GOES-East, operational since April 2025)
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- `s3://noaa-goes18/` (current GOES-West)
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- Path: `ABI-L2-{PRODUCT}{REGION}/{YEAR}/{DOY}/{HOUR}/{filename}.nc`
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- Format: NetCDF4
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- Also available on Microsoft Planetary Computer (Azure)
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## Future: GeoXO Hyperspectral Sounder
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The upcoming GeoXO satellite series (late 2020s/early 2030s) will carry a true hyperspectral IR sounder (GXS) with ~1,550 spectral bands. This would dramatically improve vertical temperature/moisture profiling from geostationary orbit and could genuinely detect inversion layers relevant to ducting. Worth revisiting when GeoXO data becomes available.
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## Recommendation
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**Don't integrate GOES-R now.** The HRRR-based approach already consumes better data for ducting prediction than GOES-R can provide directly. The complexity cost (S3 polling, NetCDF parsing, spatial interpolation, handling clear-sky gaps) is not justified by the marginal benefit.
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**Priority order for improving predictions:**
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1. HRRR forecast hours (f01-f18) — already designed in `prediction.md`
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2. Radiosonde data (already partially ingested — better vertical profiles than any satellite)
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3. GeoXO hyperspectral sounder (when available, late 2020s)
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4. GOES-R products (low value-add given HRRR already assimilates them)
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