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.
Define 0.125-degree CONUS grid (25-50N, 125-66W) for propagation
scoring and create propagation_scores table with composite unique
index on lat/lon/valid_time/band_mhz for upsert support.
Add extract_values/3 to SimplePacking and ComplexPacking for batch
index extraction from a single GRIB2 message. Add extract_grid/2 to
Extractor which takes a list of {lat, lon} points and returns all
variable values for each point, skipping points outside the grid.
This enables extracting weather data for many grid points from a
single HRRR download instead of re-parsing per point.
Single source of truth for all scoring parameters: weights, thresholds,
seasonal tables, and per-band coefficients for 8 microwave bands
(10G through 241G). Includes ITU-R P.838-3 rain attenuation
coefficients, humidity effects, refractivity scoring thresholds,
and sunrise/tier definitions.
Enqueue worker now gathers atmospheric data at pos1, midpoint, and pos2
along each QSO path instead of only pos1. Existing has_* guards prevent
duplicate fetches at each grid point.
- Add Radio.qso_path_points/1 for path point extraction
- Update hrrr_job_for_qso, iemre_job_for_qso, jobs_for_qso to iterate path points
- Refactor Weather into find_nearest_hrrr/3 and find_nearest_iemre/3
- Add hrrr_profiles_for_path/1 and iemre_for_path/1 query functions
- Add mix reset_enrichment task to trigger re-processing
System.cmd :timeout option doesn't exist in Elixir 1.19, causing every
poll to crash silently. Also translate SNMPv2-SMI::enterprises prefix
to numeric OID so the lookup maps match correctly.
Weather job fan-out can exceed PostgreSQL's 65535 parameter limit
when many QSOs produce thousands of jobs in a single batch. Chunk
insert_all into batches of 1000 jobs.
Add idempotent migration to ensure precip_1h_in and wx_codes columns
exist, then reset weather_queued flag and clear stale observations
so the cron re-fetches with precipitation data included.
- Add precip_1h_in and wx_codes fields to ASOS surface observations
- Add IEMRE reanalysis schema for radar-derived hourly precipitation
- Add IemreFetchWorker with exponential backoff and idempotency
- Integrate IEMRE enqueue into cron weather backfill pipeline
- All existing QSOs marked iemre_queued=false for automatic backfill
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.
Previously each run only enqueued 500 QSOs (the query limit).
Now weather, HRRR, and terrain enqueue functions recurse until
no unprocessed QSOs remain.
extract_n_values_array used Enum.take(count) on a reversed list
before reversing it, which included padding values from byte
alignment and dropped actual values. When group count * bits
wasn't a multiple of 8, the extra padding bits produced a
phantom value that shifted the entire array by one position.
This caused cascading errors in spatial differencing — values
started correct but diverged exponentially (DPT decoded as
38 billion K instead of 275 K).
Fix: reverse the list first, then take count, so padding values
at the end are discarded instead of actual values at the start.
AWS S3 doesn't support multi-range HTTP requests. When given
Range: bytes=0-999, 2000-2999 it ignores the header and returns
the full file (200 instead of 206). Download each range separately.
Instead of listing every permanent failure string, only retry on known
transient errors (5xx, 429, network exceptions). Everything else —
GRIB decode errors, 404s, range request failures, index out of range —
is cancelled immediately.
S3 returns 200 with the full ~116MB file instead of 206 for some older
HRRR data. Treat this as a permanent failure instead of trying to parse
the entire file.
Instead of returning "malformed section" on trailing bytes or truncated
sections, attempt to return parsed results. This handles older HRRR
files (2019) that have padding bytes after the last section.
When a local .hgt tile is missing, download it from the public AWS S3
skadi bucket, decompress with zlib, and write to the tiles directory
before retrying the lookup. Falls back to Open-Meteo/OpenTopo APIs if
the download fails.
HTTP 404 means the HRRR data doesn't exist on NOAA S3 (pre-2014
dates, etc.) and will never succeed. Return {:cancel, reason}
instead of {:error, reason} so Oban stops retrying immediately.
consume_bits would crash with a MatchError when the remaining
bitstring had fewer bits than the group width. Added a guard
clause to stop consuming when insufficient bits remain, matching
how wgrib2 handles trailing padding in packed data sections.
Eliminates the external wgrib2 C tool dependency that blocked HRRR
processing. Implements Lambert Conformal projection, simple packing
(Template 5.0), complex packing with spatial differencing (Template 5.3),
and GRIB2 section parsing — enough to extract point values from HRRR
grid data using only Elixir.
Previously retry: :transient only retried connection errors, not HTTP
429 rate limits. All clients now use a custom retry function that
handles 429, 500, 502, 503, 504 with 5 retries and jittered backoff.