- Document Finding 11: regional QSO performance by Maidenhead field
- Explain why regional weight adjustments are not justified
- Fix algo.md table formatting (blank lines before tables for Earmark)
- Change page title from Phoenix Framework to North Texas Microwave Society
- Wrap upsert_scores in Repo.transaction for all-or-nothing visibility
- Prune scores older than the 2 most recent valid_times after each upsert
- Add band-specific latest_valid_time/1 to eliminate N+1 query
- Add require Logger to Propagation module
- Remove factors from heatmap scores, fetch on-demand via point_detail
- Pre-encode initial scores JSON once instead of per-render
- Don't store scores in socket assigns (reduce memory)
- Pre-calculate RGBA color lookup table for canvas rendering
- Batch fillStyle changes, hoist math out of inner loop
- Show topbar immediately on data requests (no 300ms delay)
- Port grid square rendering from gridmap-web with toggle control
- Consolidate band selector, grid toggle, data timestamp, and links
into unified control panel
- Add "How this works" (/algo) and "Submit a QSO" (/submit) links
- Add back-to-map link on algo page
- Darken range circles for visibility over propagation overlay
- Fix popup blocking double-click zoom with pointer-events passthrough
- Prevent control panel from intercepting map click/scroll events
- Scores now include factors and valid_time in the viewport query,
eliminating the server round-trip for popups
- Click shows two range circles: solid inner (typical range) and
dashed outer (max estimated range), colored by score tier
- Circles disappear when popup closes
- Band info pushed to client on band switch for accurate range estimates
Click anywhere on the propagation map to see a detailed popup with:
- Overall score and tier label with color
- Estimated range for the selected band (CW mode)
- All 9 scoring factors with visual bar charts, individual scores,
and weight percentages
- Grid point coordinates and data timestamp
Factors are displayed in weight order so users can immediately see
which atmospheric conditions are driving the prediction.
New AsosAdjustmentWorker runs every 10 minutes:
- Fetches latest ASOS observations from all ~2900 US stations via
IEM bulk currents API (parallel fetch across 51 state networks)
- For each grid point within 75km of a reporting station, re-scores
using fresh ASOS data (temp, dewpoint, wind, sky, pressure, precip)
with HRRR refractivity gradient from the last hourly computation
- Pushes updated scores to the map via PubSub
Also stores HRRR profiles in the database during grid computation
so the data persists for reference and ASOS blending.
The JS hook sends map bounds on load and on pan/zoom. The server
queries only scores within those bounds, dramatically reducing the
payload for band switches and map updates. At zoom 7 (DFW area)
this sends ~2k scores instead of ~95k.
Add a separate wgrib2-builder stage that compiles wgrib2 from source.
Docker layer caching means this only builds once — subsequent deploys
reuse the cached layer. The binary is copied into the final runtime
image. Also fixed wgrib2 path lookup to be runtime instead of
compile-time so it works in the Docker build pipeline.
Replace circle markers with a canvas tile layer that renders smooth,
flowing colored regions using bilinear interpolation between grid
points. Colors interpolate between tiers for gradients. ~95k grid
points at 0.125 degree resolution with wgrib2 extraction.
Add Wgrib2 module that shells out to wgrib2 binary for fast GRIB2
grid extraction using -lola (nearest-neighbor to regular lat-lon grid).
Falls back to pure-Elixir decoder if wgrib2 is not installed.
Also: parallel GRIB2 range downloads, merge adjacent byte ranges,
skip corrupt messages instead of failing, pressure fetch is optional.
Both extract_points and extract_grid now skip messages with missing
data sections instead of halting. Pressure product fetch is now
optional for both grid and single-point modes — if pressure data
has corrupt messages, surface-only profiles are still stored. Fixes
historical HRRR backfill failing on old data with incomplete files.
95k points at 0.125 degree resolution caused the GRIB2 extraction to
take too long. 0.5 degree (~55 km) resolution gives 6k points which
completes in under a minute. Can increase resolution later once the
extraction is optimized.
The hrrr/weather/iemre/terrain backfill queues (20+ concurrent jobs)
were competing for bandwidth with the propagation grid HRRR download.
Now pauses those queues before the grid fetch and resumes them after,
ensuring the hourly propagation update completes reliably.
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.
Vendor Leaflet 1.9.4 (JS, CSS, marker images) and wire it into
the esbuild/Tailwind asset pipeline. Create MapLive with band
selector buttons, auto-refresh, and a colocated JS hook that
renders propagation scores as color-coded circle markers with a
legend. Stub Propagation context and BandConfig modules provide
the data interface for the scoring pipeline.
Add nav bar with links to Map, QSOs, and Submit pages.
Add fetch_grid/3 for batch HRRR data retrieval across multiple lat/lon
points in a single download pass. Expand surface messages to include
wind (UGRD/VGRD), cloud cover (TCDC), and precipitation (APCP). Add
extract_grid/2 to the GRIB2 extractor for multi-point extraction from
a single GRIB binary, and add GRIB2 variable identifiers for the new
surface fields.
