Knou/Climate-Mood-Analysis
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Complete Köppen-Geiger filter review with Mixed climate class

Browse Source 
Classify each county by area-weighted Köppen class shares: a county is
predominantly its top class when that class covers at least 50% of its
land and leads the runner-up by at least 5 percentage points; otherwise
it is Mixed (133 of 3,143 counties in the 50 states and DC).

- Add build_county_koppen_metric.py (writes data/metrics/koppen.csv) and
  apply_koppen_metric_to_climate_data.py (writes koppenZone plus
  koppenPrimaryClass/koppenSecondaryClass for Mixed counties).
- Move shared helpers into scripts/common/ (county loading, Köppen
  legend, area-weighted raster shares); fix the 180th-meridian raster
  window for Aleutians West.
- Add check_climate_data.py to validate the app CSV.
- Draw Mixed counties in app.js as diagonal stripes of their top two
  classes, fixed to the ground and following the map at every zoom, with
  a crossfade only when the stripe size changes. Filtering a class also
  matches Mixed counties where it is primary or secondary.
- Document the rule, display, and pipeline plan in docs/ and update the
  README and data-source notes.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
Knou
2026-09-14 02:54:25 -04:00
co-authored by Claude Opus 5
parent 92fbbfb2e9
commit 4d2b3e3d44
20 changed files with 6400 additions and 3450 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+23 -8
View File
@@ -28,7 +28,7 @@ The browser currently loads 3,221 county-level records from
| Group | Metrics |
| --- | --- |
| Koppen-Geiger Classification | Majority county climate class |
| Koppen-Geiger Classification | Predominant county climate class (covering at least 50% of the county's land and leading the runner-up by at least 5 points), or Mixed, drawn as stripes of the county's top two classes |
| Temperature & Extremes | Annual average temperature, diurnal temperature range, annual extreme temperature days, and annual 90 F+ heat-index days |
| Precipitation & Moisture | Annual precipitation, precipitation seasonality, wettest month, driest month, and summer specific humidity |
| Solar Resource | Mean daily global horizontal radiation (GHI) and clear-sky GHI reduction index |
@@ -92,11 +92,13 @@ will not work.
| `app.js` | Map rendering, filtering, county details, and source metadata |
| `serve.ps1` | Local HTTP server launcher |
| `data/climate-data.csv` | Browser-ready county climate records |
| `data/metrics/` | Per-metric county outputs, starting with `koppen.csv` |
| `data/geojson-counties-fips.json` | County geometry keyed by FIPS code |
| `scripts/` | Climate-data download, aggregation, and update tools |
| `scripts/county_data_sources.md` | Detailed metric definitions, data provenance, and pipeline examples |
| `scripts/requirements_county_etl.txt` | Python dependencies for the offline data pipeline |
| `tests/` | Tests for NSRDB request/download wrappers, cloud-metric merging, and gridMET heat-index calculations |
| `docs/` | Filter calculations, the pipeline plan, and design notes |
| `tests/` | Tests for the Köppen metric, the climate CSV check, NSRDB request/download wrappers, cloud-metric merging, and gridMET heat-index calculations |
## Climate Data Pipeline
@@ -133,7 +135,8 @@ default.
| Script | Current role |
| --- | --- |
| `build_county_climate_data.py` | Builds the base app CSV from county geometry, Koppen-Geiger data, NOAA temperature/precipitation data, and optional solar inputs. Its older `extremeDays` output is replaced by the current absolute-threshold stage below. |
| `build_county_climate_data.py` | Builds the base app CSV from county geometry, Koppen-Geiger data, NOAA temperature/precipitation data, and optional solar inputs. Its older `extremeDays` output is replaced by the current absolute-threshold stage below, and its largest-share `koppenZone` by the Köppen stage. It writes only the base columns, so do not run it over the live CSV. |
| `build_county_koppen_metric.py` / `apply_koppen_metric_to_climate_data.py` | Builds area-weighted Köppen class shares per county in `data/metrics/koppen.csv`, classifies each county as predominant or Mixed, and writes `koppenZone` plus the two stripe-class columns for Mixed counties. |
| `apply_precipitation_month_metrics_to_climate_data.py` | Recomputes and merges the 1991-2020 wettest- and driest-month categories from monthly nClimGrid precipitation. |
| `build_county_locally_extreme_data.py` | Downloads or reads cached nClimGrid-Daily county Tmax/Tmin files, calculates county-percentile diagnostics, and calculates the app-facing absolute 95 F / 0 F day counts. |
| `apply_locally_extreme_metric_to_climate_data.py` | Writes `absoluteExtremeDays`, removes retired locally extreme/legacy fields, and selects polygon GHI with representative-point GHI as fallback. The filename is retained from the earlier pipeline. |
@@ -150,6 +153,8 @@ default.
| `summarize_nsrdb_county_polygon_archives.py` | Combines county/tile GHI archives into area-weighted county summaries. |
| `summarize_nsrdb_county_polygon_cloud_archives.py` | Combines county/tile cloud archives into area-weighted clear-sky GHI reduction summaries. |
| `apply_nsrdb_cloud_metric_to_climate_data.py` | Merges the clear-sky GHI reduction index, preferring polygon summaries and falling back to representative points. |
| `check_climate_data.py` | Validates `data/climate-data.csv`, including Köppen codes and the stripe-class columns. |
| `common/` | Shared helpers: county loading, the Köppen legend, and area-weighted raster shares. |
The metric-specific NSRDB request and download wrappers are the normal entry
points. The shared engines remain available for custom attributes or artifact
@@ -160,6 +165,8 @@ Common local enrichment stages, after their source files have been downloaded,
are:
```powershell
.venv\Scripts\python.exe scripts\build_county_koppen_metric.py
.venv\Scripts\python.exe scripts\apply_koppen_metric_to_climate_data.py
.venv\Scripts\python.exe scripts\build_county_locally_extreme_data.py --skip-download
.venv\Scripts\python.exe scripts\apply_locally_extreme_metric_to_climate_data.py
.venv\Scripts\python.exe scripts\build_county_diurnal_temperature_range.py
@@ -169,11 +176,19 @@ are:
.venv\Scripts\python.exe scripts\apply_nsrdb_cloud_metric_to_climate_data.py
```
The order matters when rebuilding from scratch: generate the locally extreme
comparison and solar summaries before running their apply step, and summarize
gridMET or NSRDB downloads before merging them. See the data-source document
linked above for acquisition commands, expected artifacts, FIPS handling, and
the representative-point and polygon NSRDB workflows.
The order matters when rebuilding from scratch: run the Köppen apply step after
the base build, generate the locally extreme comparison and solar summaries
before running their apply step, and summarize gridMET or NSRDB downloads
before merging them. See the data-source document linked above for acquisition
commands, expected artifacts, FIPS handling, and the representative-point and
polygon NSRDB workflows. The full rebuild order is in
[`docs/pipeline-plan.md`](docs/pipeline-plan.md).
After updating the CSV, validate it with:
```powershell
.venv\Scripts\python.exe scripts\check_climate_data.py
```
Run the current automated tests with: