Backfill page now sums child partition stats for partitioned tables
like hrrr_profiles (relkind 'p') which were excluded by the relkind
'r' filter. Contacts map defers Leaflet init to requestAnimationFrame
so the flex container has dimensions before map initialization.
SRTM profiles no longer abort on missing tiles — water/ocean areas
return 0m elevation instead of failing the entire profile and falling
back to the rate-limited API. Elevation client and viewshed now pass
download: true to auto-fetch missing tiles from S3. NFS mount changed
to writable so downloaded tiles persist across pods.
Replace the JS-built Leaflet control panel with a server-side
sidebar (desktop) and mobile floating controls. Band checkboxes,
callsign filter, and nav links now match the main propagation map
layout. Filter state managed by LiveView, pushed to JS via events.
Registered users can suggest edits to any contact's core fields
(callsigns, grids, band, mode, timestamp). Edits enter an admin
approval queue with field-by-field diff view. On approve, changes
are applied and enrichment re-enqueued if grids/band changed.
Users receive email notification on approve or reject.
Also updates dependabot.yml for mix ecosystem.
- Callsign input filters contacts where either station matches
(case-insensitive substring match, debounced 300ms)
- Band checkboxes now show per-band count of visible contacts
- All/None buttons for quick band selection
- Header count updates dynamically with filters
- Complete rewrite: rebuilds map on any filter change instead of
toggling individual layers (simpler, handles cross-filter correctly)
The sidebar and mobile floating controls overlay the dark map tiles
but inherited light theme colors, making dropdowns, inputs, and
menus invisible (white-on-white). Adding data-theme="dark" forces
all daisyUI components within these containers to use dark variants
regardless of the page's theme setting.
When clicking a grid point, fetches the latest NEXRAD composite
reflectivity and identifies rain cells within 300 km that could
enable rain scatter contacts. Shows:
- Scatter classification (excellent/good/marginal/none)
- Top 3 cells with dBZ, distance, bearing, and relative signal
- Colored circle markers on the map at rain cell locations
- Markers sized by reflectivity, colored by intensity
Uses simplified bistatic radar equation accounting for reflectivity,
frequency-dependent scattering (Rayleigh/Mie), and R^4 path loss.
NEXRAD cells sampled every ~5 km within bounding box for efficiency.
Terrain elevations now include the earth bulge correction, so the
profile visually humps up in the middle relative to the straight
LOS beam — showing how the curved earth rises into the signal path.
Uses actual k-factor from HRRR refractivity when available, otherwise
standard 4/3. For a 300 km path at k=4/3, the midpoint bulge is
~2,650 m (8,700 ft).
When clicking a grid point with ducting, the panel now shows each
duct layer with base-top height in feet, thickness in meters, and
minimum trapped frequency. Data flows from Duct.analyze through
the scoring factors as a ducts array.
- Update all 9 hardcoded weights to match recalibrated values
- Add missing PWAT factor (11.3% weight) to FACTOR_META and FACTOR_ORDER
- Reorder factors by weight (highest first)
- Fix pressure explanation (low pressure is better, not rising)
- Add PWAT factor explanation (beneficial vs harmful by band)
- Show duct info panel when native data detects ducting layers
(count, thickness, minimum trapped frequency)
- Replace stale April 2026 manual weights with recalibrated values
- Document native hybrid-sigma data in data flow section
- Note refractivity factor now uses native 10-50m resolution
- Add hourly grid integration section to Part 12
- Expose duct_info (count, freq, thickness) in scoring factors for UI
The PropagationGridWorker now fetches native hybrid-sigma levels
(TMP, SPFH, HGT, PRES × 50 levels) alongside the standard surface
and pressure products. Native data provides 10-50m vertical spacing
vs 250m from pressure levels, detecting thin surface ducts invisible
to the standard product.
Key design: cell-by-cell reducer in Wgrib2.extract_grid_from_file_mapped
processes each of the 95k CONUS cells through a duct analysis function
inline, keeping only scalar metrics per cell. Peak memory ~86 MB
instead of ~1.8 GB for the full grid map.
Per-cell output: native_min_gradient, best_duct_freq_ghz,
max_duct_thickness_m, duct_count. The scorer prefers the native
gradient over the pressure-level gradient when available.
Native fetch is optional — if it fails, scoring continues with
pressure-level data only.
Backtest on 11,431 native profiles (2026-04-11):
- Drop duct_usable_10/24/47ghz (always 1.0, no discrimination)
- Drop bulk_richardson (near-identical QSO vs baseline means)
- Document all feature results with signal strength assessment
- theta_e_jump is strongest native discriminator (44% lift)
- best_duct_freq and duct_thickness show clear physical signal
- Round grid-derived lat/lon in maybe_fill_latlon changeset step
- Format lat/lon to 6 decimal places on index table
- Migrate existing beacon data to 6 decimal precision
- Add comma separators to EIRP mW display (e.g. 10,000 mW)
- Extract shared add_commas helper for format_freq and format_mw
Height in feet doesn't need decimal precision. Migrates the DB
column, updates schema type, and strips trailing .0 from form
input so the integer cast succeeds.
