- Explain on the page what wet-bulb temperature measures (the evaporative-cooling
ceiling on shedding heat), so the metric isn't opaque.
- Report the share of heat-stress "wet-bulb" days (peak wet bulb >= 26 C) vs
normal days, recent window vs the full record — mirroring the precip wet-day
frequency.
- Present the overall total as a direction-agnostic net change (magnitude only),
not "warmer/cooler"; per-metric cards still carry direction.
Bumps the score cache version.
Score how far a location's last 6 years have drifted from its full 45-year
record. For each metric and percentile category (p10/p25/p50/p75/p90), the
recent-years value is placed on the baseline distribution and the gap from the
expected percentile is the divergence — unit-free, so metrics compare directly.
Scored per meteorological season plus annual, weighted into per-metric and
overall scores (temps, humidity and feels-like weighted heaviest).
- backend/scoring.py: divergence math, seasonal slicing, precip zero-inflation
split (wet-day frequency + amount), tier mapping onto the existing temp scale.
- climate.py: derive a wet-bulb column (Stull 2011) at the read boundary, before
the humidity column is converted to absolute — via a shared _derive_metrics
wrapper at all four read sites.
- api/v2/score endpoint + build_score payload, cached on the history token with
a scoring-version key.
- frontend score page: overall hero, per-metric cards, by-season chips, and a
button-revealed summary (sentences + metrics×season table + per-percentile
detail). Score nav link across all headers.
- Tests for the scoring math, wet-bulb formula, payload shape and route.
