Rolling-origin harness gains rise_rain_quantile, rise_rain_quantile_uw,
rise_rain_qsigma (L2 point + quantile sigma) and rise_rain_fc48, all
opt-in, plus --from-cache for reproducible offline reruns. Results in
models/eval_2026-09-12*.json, write-up in docs/FLOOD_FORECASTING.md:
- quantile point prediction: better MAE, worse first-alert lead at 5 of
11 events (P.103 2022-08-14 +6h -> +1h) -> rejected
- quantile sigma only: Brier within noise (0.0031 -> 0.0029) -> not worth 3x heads
- rain_fc48: neutral everywhere except 2024-10-03 P.1 (+21h -> +72h), n=1
-> deferred to after the 2026 season
src/ml/hii_rain.py: catchment-mean hourly rain from the ~130 HII gauges in
the upper-Ping box and a 24h-sum comparison against Open-Meteo. Not a
training feature (table exists only since 2026-08-11, no archive); exposed
at GET /api/hii/rainfall/catchment so the two sources' agreement is on
record by the time a fold can test it.
data._read_cache now skips non-station files in models/cache/ (the shared
dir also holds rain_openmeteo / dam_* caches, which crashed the reader).
scripts/summarize_eval.py prints per-variant lead/peak-error tables.
