# Filter 4: Extreme temperature days

**Status:** Not started.

**Data key:** `absoluteExtremeDays`. Calculation:
[filter-calculations.md](../filter-calculations.md) §4.

## Findings

**5. Extreme-day counts are not completeness-normalized.** A partially observed
year contributes a raw count and receives the same weight as a complete year.
Consider requiring a minimum number of valid days or annualizing partial
counts explicitly.

**6. The absolute-extreme metric depends on unrelated percentile thresholds.**
`build_annual_counts` skips a county when its retired local p95/p05 thresholds
are missing, even though the active 95 °F / 0 °F calculation does not require
those percentiles. The absolute calculation should be separated from that
prerequisite.

**18. The data-sources doc describes the retired locally extreme metric.**
Source 5 in `scripts/county_data_sources.md` is headed `locallyExtremeDays`
and says `apply_locally_extreme_metric_to_climate_data.py` writes the locally
extreme average into `extremeDays`, keeps `oldExtremeDays`, and adds eight
detail and audit columns. None of those columns is in `data/climate-data.csv`,
and the script's docstring says locally percentile-based metrics are not
included in the app CSV.

Cross-filter findings that affect this filter, in
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered),
13 (Lexington, VA blank), and 17 (missing from the data-sources metric list).

## Decisions

None yet.

## Tasks

Not started; follow the per-filter review checklist in
[pipeline-plan.md](../pipeline-plan.md) §5.