- Spike docs at docs/research/hrrr_native_levels.md confirming files
are on AWS S3 for 5+ years, 50 hybrid levels, and include TKE and
SPFH needed for Phase 2 turbulence features. Architectural finding:
per-point on-demand fetching is impractical (~530 MB/file), so
the ingestion worker batches per (date, hour) instead.
- hrrr_native_profiles schema: arrays per level plus cached surface
scalars and placeholder columns for Phase 2/4 derived fields.
Strictly additive — the existing hrrr_profiles table is untouched.
- HrrrNativeClient: pure URL/message-list helpers, build_native_profile/1
that turns a parsed wgrib2 map into the schema shape (TDD'd).
- Exposed HrrrClient.download_grib_ranges/2 so the native client
reuses the existing parallel byte-range download + disk cache.
- HrrrNativeGridWorker: Oban worker keyed on {year, month, day, hour},
unique at :infinity, pulls distinct (lat, lon) points from contacts
in the ±30 min window, downloads the native grib2, extracts per
point, bulk-upserts.
- mix hrrr_native_backfill --limit N enqueues the top-N hours by
contact count.
Phase 1 gate still pending Task 1.6 (sanity-check backtest after
live data lands).
Multi-phase plan to incorporate the meteorologist's feedback on
algo.md: hybrid-sigma vertical resolution, boundary-layer turbulence
features, ray-traced duct geometry, frontal geometry, radar-based
stability, climatological anomalies, regional seasonal tuning, and
5-minute METAR. Every phase has a backtest-gated stop criterion so
features that don't show lift against the historical QSO corpus
don't ship.
Contact scoring now uses all HRRR profiles along the path instead of
just pos1. Aggregation strategy:
- Best along path for beneficial factors (refractivity, pressure)
- Worst along path for harmful factors (rain, wind)
- Average for neutral factors (temp, dewpoint, PWAT, BL depth)
Scorer.path_integrated_conditions/2 merges multiple profiles into a
single conditions map. Falls back gracefully to single-profile scoring
when only one profile is available.
SSB is not possible on rainscatter - the original analysis was wrong.
The 24 GHz PH advantage is entirely a contest strategy artifact: Great
Lakes operators line up on opposite shores for rapid-fire SSB contacts.
With EN/CM/DM cluster activity removed, CW leads by 16% at 24 GHz.
CW advantage is monotonically increasing with frequency as physics
predicts. No 24 GHz anomaly exists.
CW advantage scales dramatically with frequency: +29% at 10G, +48% at
47G, +221% at 75G. At 24 GHz the pattern reverses (PH wins by 8%)
due to rainscatter favoring wider-bandwidth modes. Above 122 GHz,
100% of contacts are CW — SSB can't close the path.
Raw features had vastly different scales (pressure ~1013, sin/cos ~[-1,1])
causing gradient explosion. Normalize all atmospheric features to ~[0,1]
using known physical bounds. Add Polaris dep for optimizer.
- 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
QSO enrichment now groups all path points by HRRR hour and creates
one batch job per hour instead of one job per point. The batch job
downloads the GRIB2 data once and extracts all needed points from
the same binary. Legacy single-point jobs are still supported for
backward compatibility.
Poll UBNT AirFiber radios (AF11X + AF60-LR) every 5 minutes via
net-snmp CLI, storing signal metrics in commercial_samples. Fetches
ASOS weather alongside each cycle for propagation correlation.
Includes 7 seeded link definitions, Oban cron worker, and net-snmp
in the Docker image.
