Refine project documentation and track metric files
Close gaps found in a review of the documentation: - Track data/metrics/ and data/metric_sources.json in git so the data checker passes on a fresh clone (finding 23; decision logged) - State the Alaska and Hawaii coverage gap in the README limitations and extend finding 12 - File findings 24-26: the data-sources doc lacks gridMET and several pipeline commands; wettest/driest month are computed twice; solar GHI is written by the extreme-temperature apply step - Add the stale "fallback values" note to filter 2's tasks Tidy the document system: - Add docs/reviews/README.md with the numbering rules and a finding index - Rename koppen-mixed-display-plan.md to koppen-mixed-display.md and fix its stale Puerto Rico and "stage 5" text - Add the precipitation-month step to the README enrichment list - Describe the Current method / Previous method pattern in plan section 5 - Add CLAUDE.md with the project guardrails and doc layout Format filter-calculations.md so it renders on GitHub and in VS Code: inline math uses $...$, ranges use en dashes, and implementation references name functions instead of line numbers. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
Claude Opus 5
+4
-1
@@ -15,10 +15,13 @@ Thumbs.db
|
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!.env.example
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# Downloaded and generated climate datasets are too large for Git.
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# Keep only the assets required by the browser application.
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# Keep the assets required by the browser application, the per-metric county
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# files, and the metric metadata the data checker reads.
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data/*
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!data/climate-data.csv
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!data/geojson-counties-fips.json
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!data/metrics/
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!data/metric_sources.json
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# Runtime logs
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*.log
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@@ -0,0 +1,45 @@
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# Project notes for Claude
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US County Climate Explorer: a static Leaflet app (`index.html`, `app.js`,
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`styles.css`) over `data/climate-data.csv`, built by the Python scripts in
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`scripts/`. The 12 filters are being reviewed one at a time before the CSV is
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restructured; see [docs/pipeline-plan.md](docs/pipeline-plan.md).
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## Guardrails
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- Never rerun `scripts/build_county_climate_data.py` over
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`data/climate-data.csv`. It drops live columns and overwrites `koppenZone`
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(pipeline plan §7).
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- Change one filter at a time. After every apply step, run the checker and
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compare changed counties against expectations.
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- Run scripts from the project root with the virtual environment:
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- `.venv\Scripts\python.exe scripts\check_climate_data.py`
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- `.venv\Scripts\python.exe -m unittest discover -s tests`
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- When `app.js` or the data files change, bump `APP_ASSET_VERSION` in `app.js`
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(it also versions the CSV and GeoJSON URLs) and the matching `app.js?v=`
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query in `index.html`. `styles.css` has its own query in `index.html`.
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- The map and every filter cover the 50 states and DC. Puerto Rico rows stay in
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the data files but are never shown.
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- Do not start the Phase 3 CSV restructure until all 12 filters are reviewed.
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## Writing
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- Write "Köppen" with the umlaut in prose, UI text, help text, and messages.
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Use ASCII `koppen` only in identifiers, file names, and data paths.
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## Documentation layout
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Each fact has one home:
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- `docs/pipeline-plan.md`: current pipeline, target design, phases, the
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per-filter checklist (§5), the filter tracker (§6), and guardrails (§7).
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Keep it about 200 lines.
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- `docs/reviews/`: one file per filter with its findings, decision links, and
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tasks; `00-cross-filter.md` for findings that affect several filters.
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`docs/reviews/README.md` has the numbering conventions and the finding index.
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- `docs/decisions.md`: open decisions and a dated log of decided ones. An item
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leaves "Open decisions" only when the project owner decides it.
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- `docs/filter-calculations.md`: what each calculation is. No review status.
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- `scripts/common/README.md`: rules for shared helpers.
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Keep the tracker status in the plan and the review-file checkboxes in sync.
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@@ -46,7 +46,7 @@ calendar year. Definitions and time periods are shown in the application's
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### Requirements
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- A modern web browser
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- Python 3
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- Python 3 (the data pipeline targets Python 3.11)
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- PowerShell for the included convenience script
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- An internet connection for Leaflet, map tiles, and hosted fonts
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@@ -167,6 +167,7 @@ are:
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```powershell
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.venv\Scripts\python.exe scripts\build_county_koppen_metric.py
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.venv\Scripts\python.exe scripts\apply_koppen_metric_to_climate_data.py
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.venv\Scripts\python.exe scripts\apply_precipitation_month_metrics_to_climate_data.py
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.venv\Scripts\python.exe scripts\build_county_locally_extreme_data.py --skip-download
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.venv\Scripts\python.exe scripts\apply_locally_extreme_metric_to_climate_data.py
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.venv\Scripts\python.exe scripts\build_county_diurnal_temperature_range.py
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@@ -176,8 +177,9 @@ are:
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.venv\Scripts\python.exe scripts\apply_nsrdb_cloud_metric_to_climate_data.py
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```
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The order matters when rebuilding from scratch: run the Köppen apply step after
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the base build, generate the locally extreme comparison and solar summaries
|
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These stages follow the base build, `build_county_climate_data.py`, which must
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not be rerun over the live CSV. The order matters when rebuilding from scratch:
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run the Köppen and precipitation-month apply steps after the base build, generate the locally extreme comparison and solar summaries
|
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before running their apply step, and summarize gridMET or NSRDB downloads
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before merging them. See the data-source document linked above for acquisition
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commands, expected artifacts, FIPS handling, and the representative-point and
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@@ -193,7 +195,7 @@ After updating the CSV, validate it with:
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Run the current automated tests with:
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```powershell
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python -m unittest discover -s tests
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.venv\Scripts\python.exe -m unittest discover -s tests
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```
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## Planned Mood Analysis
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@@ -223,6 +225,10 @@ causes changes in mood.
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represent every location inside a county.
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- Source datasets use different methods and, in some cases, different time
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periods.
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- Alaska and Hawaii have values only for the Köppen class and the two solar
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metrics. The NOAA and gridMET sources behind the other nine metrics cover the
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contiguous U.S. only, so those counties show "No data". Puerto Rico is not
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shown.
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- Some solar metrics use representative-point values where county polygon
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summaries are unavailable.
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- The current interface is an exploratory visualization, not a completed
|
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|
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@@ -0,0 +1,4 @@
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{
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"schemaVersion": 1,
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"metrics": {}
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}
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File diff suppressed because it is too large
Load Diff
+6
-2
@@ -8,7 +8,7 @@ filter-by-filter review. The findings that led to them are in
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| Decision | Options | Needed by |
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| --- | --- | --- |
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| Committing large intermediates | Commit metric files only, or also source summaries | Phase 3 |
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| Committing source summaries | Also commit the source summaries that metric files are built from (for example `data/nrel/county_polygon_ghi_summary.csv`), or keep them out of git. Metric files are committed; see "Committing metric files" below | Phase 3 |
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| Alaska and Hawaii coverage | Leave blank with a stated coverage gap, or add a source that covers them (for example Daymet or TerraClimate). NOAA nClimGrid and gridMET cover the contiguous U.S. only, so 29 AK and 5 HI counties are blank in filters 2–10; see finding 12 in [reviews/00-cross-filter.md](reviews/00-cross-filter.md) | Before Phase 3 |
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## Decided
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@@ -23,7 +23,7 @@ filter-by-filter review. The findings that led to them are in
|
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starting with `koppen.csv`.
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- **Mixed climate display (2026-09-13):** diagonal stripes of each Mixed
|
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county's top two classes; see
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[koppen-mixed-display-plan.md](koppen-mixed-display-plan.md).
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[koppen-mixed-display.md](koppen-mixed-display.md).
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- **Puerto Rico (2026-09-13):** off the map and out of every filter. The app
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already drops state FIPS 72; the data files keep the rows.
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- **Shared helpers (2026-09-13):** `scripts/common/` holds only code used by
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@@ -43,3 +43,7 @@ filter-by-filter review. The findings that led to them are in
|
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unless all 12 monthly values are present (WMO-No. 1203 §4.3.3).
|
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- **Annual avg temperature in Alaska and Hawaii (2026-09-15):** left blank for
|
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now; tracked as the cross-filter "Alaska and Hawaii coverage" open decision.
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- **Committing metric files (2026-09-15):** `data/metrics/` and
|
||||
`data/metric_sources.json` are tracked in git, so the data checker passes on a
|
||||
fresh clone and reproduction tier 2 is possible. Closes finding 23. Whether
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to also commit source summaries stays open.
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|
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+73
-74
@@ -6,20 +6,20 @@ for the 12 county filters currently exposed by the climate explorer.
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## Scope and notation
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The current metric list is defined in `app.js` under `METRICS`. Unless noted
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otherwise, long-term climate metrics use the 1991--2020 reference period.
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otherwise, long-term climate metrics use the 1991–2020 reference period.
|
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||||
| Symbol | Meaning |
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| --- | --- |
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| \(c\) | County |
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| \(i\) | Raster or model grid cell |
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| \(m\) | Calendar month |
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| \(d\) | Calendar day |
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| \(h\) | Hour or NSRDB time row |
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||||
| \(y\) | Year |
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||||
| \(G_c\) | Valid grid cells assigned to county \(c\) |
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| \(V_c\) | Valid observations for county \(c\) |
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| \(\mathbf{1}[A]\) | 1 when condition \(A\) is true; otherwise 0 |
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| \(\operatorname{clip}(x,a,b)\) | Restrict \(x\) to the interval \([a,b]\) |
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| $c$ | County |
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| $i$ | Raster or model grid cell |
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| $m$ | Calendar month |
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| $d$ | Calendar day |
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| $h$ | Hour or NSRDB time row |
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| $y$ | Year |
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||||
| $G_c$ | Valid grid cells assigned to county $c$ |
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| $V_c$ | Valid observations for county $c$ |
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| $\mathbf{1}[A]$ | 1 when condition $A$ is true; otherwise 0 |
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| $\operatorname{clip}(x,a,b)$ | Restrict $x$ to the interval $[a,b]$ |
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Missing values are omitted from means unless a metric-specific rule below says
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otherwise.
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@@ -60,7 +60,7 @@ in `app.js`.
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| Temperature & Extremes | Annual Extreme Temperature Days | `absoluteExtremeDays` | Numeric | Days/year |
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| Temperature & Extremes | Annual 90 F+ Heat Index Days | `humidHeatDays` | Numeric | Days/year |
|
||||
| Precipitation & Moisture | Annual Precipitation (Normals) | `annualPrecipIn` | Numeric | Inches/year |
|
||||
| Precipitation & Moisture | Seasonality Index | `seasonalityIndex` | Numeric | 0--100 index |
|
||||
| Precipitation & Moisture | Seasonality Index | `seasonalityIndex` | Numeric | 0–100 index |
|
||||
| Precipitation & Moisture | Wettest Month | `wettestPrecipMonth` | Categorical | Month |
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||||
| Precipitation & Moisture | Driest Month | `driestPrecipMonth` | Categorical | Month |
|
||||
| Precipitation & Moisture | Summer Specific Humidity | `avgSummerSpecificHumidityGKg` | Numeric | g/kg |
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@@ -76,9 +76,9 @@ There is no continuous numerical score. Each county is classified from the
|
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share of its land covered by each Köppen class. The rule was adopted on
|
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2026-09-12 and applied to `data/climate-data.csv` on 2026-09-13.
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||||
Let \(s_{c,k}\) be the share of county \(c\)'s land area covered by class \(k\).
|
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Let $s_{c,k}$ be the share of county $c$'s land area covered by class $k$.
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Each valid raster cell is weighted by the area of the cell that lies inside the
|
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county, \(a_{c,i}\); ocean and no-data cells are excluded:
|
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county, $a_{c,i}$; ocean and no-data cells are excluded:
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||||
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||||
$$
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||||
s_{c,k}
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||||
@@ -86,9 +86,9 @@ s_{c,k}
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\frac{\sum_{i}a_{c,i}\,\mathbf{1}[K_i=k]}{\sum_{i}a_{c,i}}.
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$$
|
||||
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||||
Rank the classes so that \(s_{c,(1)}\ge s_{c,(2)}\ge\cdots\), with
|
||||
\(s_{c,(2)}=0\) when only one class is present. A county is **predominantly**
|
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class \(k_{(1)}\), shown as a single color, if and only if both conditions hold:
|
||||
Rank the classes so that $s_{c,(1)}\ge s_{c,(2)}\ge\cdots$, with
|
||||
$s_{c,(2)}=0$ when only one class is present. A county is **predominantly**
|
||||
class $k_{(1)}$, shown as a single color, if and only if both conditions hold:
|
||||
|
||||
$$
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||||
K_c=
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@@ -100,19 +100,19 @@ $$
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||||
|
||||
The gap is measured in percentage points. A county that fails either condition
|
||||
is classified as **Mixed** (shown as "Mixed Climate"). For Mixed counties,
|
||||
\(p_c=k_{(1)}\) and \(q_c=k_{(2)}\) are stored in `koppenPrimaryClass` and
|
||||
$p_c=k_{(1)}$ and $q_c=k_{(2)}$ are stored in `koppenPrimaryClass` and
|
||||
`koppenSecondaryClass`, and the map draws the county with stripes of those two
|
||||
classes (see [koppen-mixed-display-plan.md](koppen-mixed-display-plan.md)).
|
||||
classes (see [koppen-mixed-display.md](koppen-mixed-display.md)).
|
||||
Both columns are blank for predominant counties. A county with no valid raster
|
||||
cells is left blank; none in the 50 states and DC is.
|
||||
|
||||
Each county is read from a small raster window around its polygon. Each cell is
|
||||
split into 16 × 16 sub-cells to estimate the fraction inside the county, and
|
||||
scaled by \(\cos(\text{latitude})\) for its true surface area. A county whose
|
||||
scaled by $\cos(\text{latitude})$ for its true surface area. A county whose
|
||||
polygon crosses the 180th meridian (Aleutians West, AK) is split into one piece
|
||||
on each side, and each piece is read from its own window.
|
||||
|
||||
**Filter.** Choosing a class \(F\) shows counties that are predominantly that
|
||||
**Filter.** Choosing a class $F$ shows counties that are predominantly that
|
||||
class and Mixed counties where it is the primary or secondary class; the
|
||||
"Mixed Climate" option shows every Mixed county:
|
||||
|
||||
@@ -136,13 +136,13 @@ condition catches near 50/50 splits, such as Schenectady, NY (Dfb 50.1%,
|
||||
Dfa 49.9%), where a single label would rest on a margin of a few tenths of a
|
||||
point. Map-unit purity standards from other fields were considered and
|
||||
rejected: the FAO Land Cover Classification System treats a unit as single
|
||||
only above 80%, and USDA soil survey consociations allow roughly 15--25%
|
||||
only above 80%, and USDA soil survey consociations allow roughly 15–25%
|
||||
dissimilar inclusions. Applied to counties, those thresholds would mark about
|
||||
40--47% of the map area as mixed. A published county-level Köppen dataset
|
||||
40–47% of the map area as mixed. A published county-level Köppen dataset
|
||||
(Audirac, Harvard Dataverse, 2024) uses the plurality class and reports the
|
||||
share of every class, without a threshold.
|
||||
|
||||
**Results.** Using the Beck et al. 2023 1991--2020 1 km raster, for the 3,143
|
||||
**Results.** Using the Beck et al. 2023 1991–2020 1 km raster, for the 3,143
|
||||
counties in the 50 states and DC:
|
||||
|
||||
| Classification | Counties | Share of counties | Share of map area |
|
||||
@@ -194,7 +194,7 @@ the Köppen apply step must run after it.
|
||||
|
||||
**Data key:** `avgTempF`
|
||||
|
||||
The annual value is a 1991--2020 climatological standard normal: the mean of
|
||||
The annual value is a 1991–2020 climatological standard normal: the mean of
|
||||
the 12 monthly normals of NOAA nClimGrid-Monthly average temperature, averaged
|
||||
over each county's area. The definition was adopted on 2026-09-15. It is not
|
||||
yet applied to `data/climate-data.csv`, whose values still use the current
|
||||
@@ -206,8 +206,8 @@ the present. Its average temperature, `tavg`, is the mean of maximum and
|
||||
minimum temperature, (Tmax + Tmin)/2, not a 24-hour mean. Alaska and Hawaii
|
||||
are outside the grid, so their counties are blank.
|
||||
|
||||
**Cell normals.** For each grid cell \(i\) and calendar month \(m\), the
|
||||
normal is the mean over the 1991--2020 years with a valid value:
|
||||
**Cell normals.** For each grid cell $i$ and calendar month $m$, the
|
||||
normal is the mean over the 1991–2020 years with a valid value:
|
||||
|
||||
$$
|
||||
T_{i,m}^{\mathrm{norm}}
|
||||
@@ -224,7 +224,7 @@ values can differ slightly from NCEI's published grids. The result is not
|
||||
NCEI's station-based U.S. Climate Normals product.
|
||||
|
||||
**County monthly values.** Each cell is weighted by the area of the cell that
|
||||
lies inside the county, \(a_{c,i}\), estimated as for Köppen (§1). Cells
|
||||
lies inside the county, $a_{c,i}$, estimated as for Köppen (§1). Cells
|
||||
without data, such as ocean, are excluded:
|
||||
|
||||
$$
|
||||
@@ -234,7 +234,7 @@ T_{c,m}
|
||||
$$
|
||||
|
||||
**Annual value.** Every month has equal weight. The value is defined only when
|
||||
all 12 monthly values \(T_{c,m}\) exist; otherwise the county is blank:
|
||||
all 12 monthly values $T_{c,m}$ exist; otherwise the county is blank:
|
||||
|
||||
$$
|
||||
T_c(^\circ\mathrm{F})
|
||||
@@ -248,7 +248,7 @@ Values are kept at full precision until the stored value is rounded to
|
||||
0.1 °F.
|
||||
|
||||
**Rationale.** The method follows the WMO rules for annual normals, which
|
||||
NOAA also applies to its 1991--2020 Normals:
|
||||
NOAA also applies to its 1991–2020 Normals:
|
||||
|
||||
- *Equal month weights.* For a mean, WMO-No. 1203 §4.3.3(a) defines the annual
|
||||
normal as "the mean of the monthly normals", and its footnote says weighting
|
||||
@@ -286,7 +286,7 @@ T_{c,m}
|
||||
\sum_{i\in G_{c,m}}T_{i,m}^{\mathrm{norm}},
|
||||
$$
|
||||
|
||||
and the annual value averages whichever of the \(M_c\) monthly values are
|
||||
and the annual value averages whichever of the $M_c$ monthly values are
|
||||
available, normally 12:
|
||||
|
||||
$$
|
||||
@@ -297,9 +297,8 @@ T_c(^\circ\mathrm{F})
|
||||
\right)\frac{9}{5}+32.
|
||||
$$
|
||||
|
||||
Implementation: `scripts/build_county_climate_data.py:124--166`,
|
||||
`scripts/build_county_climate_data.py:206--221`, and
|
||||
`scripts/build_county_climate_data.py:478--514`.
|
||||
Implementation: `_as_monthly_climatology`, `_zonal_mean`, and
|
||||
`build_county_records` in `scripts/build_county_climate_data.py`.
|
||||
|
||||
## 3. Diurnal Temperature Range
|
||||
|
||||
@@ -312,7 +311,7 @@ DTR_{c,d}=T^{\max}_{c,d}-T^{\min}_{c,d}.
|
||||
$$
|
||||
|
||||
Days with a missing input or a negative range are excluded. The final metric is
|
||||
the mean across all retained days in 1991--2020, followed by conversion of a
|
||||
the mean across all retained days in 1991–2020, followed by conversion of a
|
||||
Celsius temperature *difference* to a Fahrenheit difference:
|
||||
|
||||
$$
|
||||
@@ -324,11 +323,12 @@ $$
|
||||
\right).
|
||||
$$
|
||||
|
||||
There is correctly no \(+32\) term when converting a temperature difference.
|
||||
There is correctly no $+32$ term when converting a temperature difference.
|
||||
The output artifact stores two decimal places.
|
||||
|
||||
Implementation: `scripts/build_county_diurnal_temperature_range.py:46--104`
|
||||
and `scripts/build_county_diurnal_temperature_range.py:132--151`.
|
||||
Implementation: `build_diurnal_temperature_range`, `c_delta_to_f_delta`, and
|
||||
`write_diurnal_temperature_range_csv` in
|
||||
`scripts/build_county_diurnal_temperature_range.py`.
|
||||
|
||||
## 4. Annual Extreme Temperature Days
|
||||
|
||||
@@ -354,21 +354,20 @@ $$
|
||||
E_c=\frac{1}{Y_c}\sum_{y\in V_c}E_{c,y}.
|
||||
$$
|
||||
|
||||
The checked-in data uses 1991--2025. The Boolean OR means that a hypothetical
|
||||
The checked-in data uses 1991–2025. The Boolean OR means that a hypothetical
|
||||
day meeting both conditions is still counted only once. A year is included when
|
||||
an annual record exists; counts are not normalized to 365 or 366 valid days.
|
||||
|
||||
Implementation: `scripts/build_county_locally_extreme_data.py:473--540`,
|
||||
`scripts/build_county_locally_extreme_data.py:669--674`, and
|
||||
`scripts/build_county_locally_extreme_data.py:705--722`.
|
||||
Implementation: `build_annual_counts`, `_average_or_none`, and
|
||||
`write_comparison_csv` in `scripts/build_county_locally_extreme_data.py`.
|
||||
|
||||
## 5. Annual 90 F+ Heat Index Days
|
||||
|
||||
**Data key:** `humidHeatDays`
|
||||
|
||||
The daily proxy pairs NOAA nClimGrid-Daily county Tmax, \(T\), with the gridMET
|
||||
county daily minimum relative humidity, \(R\). Relative humidity is clipped to
|
||||
\([0,100]\).
|
||||
The daily proxy pairs NOAA nClimGrid-Daily county Tmax, $T$, with the gridMET
|
||||
county daily minimum relative humidity, $R$. Relative humidity is clipped to
|
||||
$[0,100]$.
|
||||
|
||||
The NWS simple Heat Index estimate is calculated in two steps:
|
||||
|
||||
@@ -380,7 +379,7 @@ $$
|
||||
HI_s=\frac{S+T}{2}.
|
||||
$$
|
||||
|
||||
When \(HI_s\ge80^\circ\mathrm{F}\), the Rothfusz regression is used:
|
||||
When $HI_s\ge80^\circ\mathrm{F}$, the Rothfusz regression is used:
|
||||
|
||||
$$
|
||||
\begin{aligned}
|
||||
@@ -390,7 +389,7 @@ HI_r={}&-42.379+2.04901523T+10.14333127R-0.22475541TR\\
|
||||
\end{aligned}
|
||||
$$
|
||||
|
||||
For \(R<13\) and \(80\le T\le112\), subtract:
|
||||
For $R<13$ and $80\le T\le112$, subtract:
|
||||
|
||||
$$
|
||||
A_{low}
|
||||
@@ -399,7 +398,7 @@ A_{low}
|
||||
\sqrt{\max\left(\frac{17-|T-95|}{17},0\right)}.
|
||||
$$
|
||||
|
||||
For \(R>85\) and \(80\le T\le87\), add:
|
||||
For $R>85$ and $80\le T\le87$, add:
|
||||
|
||||
$$
|
||||
A_{high}=\frac{R-85}{10}\frac{87-T}{5}.
|
||||
@@ -428,17 +427,17 @@ $$
|
||||
H_c=\frac{1}{Y_c}\sum_{y\in V_c}H_{c,y}.
|
||||
$$
|
||||
|
||||
The period is 1991--2020. A year with at least one valid paired day contributes
|
||||
The period is 1991–2020. A year with at least one valid paired day contributes
|
||||
equally to the final average; there is no completeness adjustment.
|
||||
|
||||
Implementation: `scripts/summarize_county_gridmet_humidity.py:439--474` and
|
||||
`scripts/summarize_county_gridmet_humidity.py:547--617`.
|
||||
Implementation: `_heat_index_f` and `summarize` in
|
||||
`scripts/summarize_county_gridmet_humidity.py`.
|
||||
|
||||
## 6. Annual Precipitation (Normals)
|
||||
|
||||
**Data key:** `annualPrecipIn`
|
||||
|
||||
Each monthly county total, \(P_{c,m}\), is the unweighted mean of valid raster
|
||||
Each monthly county total, $P_{c,m}$, is the unweighted mean of valid raster
|
||||
cells touched by the county. Annual precipitation is the sum of available
|
||||
monthly totals, converted from millimeters to inches:
|
||||
|
||||
@@ -452,8 +451,8 @@ $$
|
||||
The stored value is rounded to 0.1 inch. The implementation only requires one
|
||||
valid month, so missing months produce a partial annual sum rather than a blank.
|
||||
|
||||
Implementation: `scripts/build_county_climate_data.py:401--412` and
|
||||
`scripts/build_county_climate_data.py:478--511`.
|
||||
Implementation: `_zonal_mean` and `build_county_records` in
|
||||
`scripts/build_county_climate_data.py`.
|
||||
|
||||
## 7. Seasonality Index
|
||||
|
||||
@@ -485,9 +484,10 @@ SI_c=
|
||||
\right).
|
||||
$$
|
||||
|
||||
If \(\mu_c\le0\), the index is set to zero. The value is stored as an integer.
|
||||
If $\mu_c\le0$, the index is set to zero. The value is stored as an integer.
|
||||
|
||||
Implementation: `scripts/build_county_climate_data.py:487--521`.
|
||||
Implementation: `build_county_records` in
|
||||
`scripts/build_county_climate_data.py`.
|
||||
|
||||
## 8. Wettest Month
|
||||
|
||||
@@ -500,8 +500,8 @@ $$
|
||||
Missing monthly values are ignored. An exact tie resolves to the earliest tied
|
||||
month because `numpy.nanargmax` returns the first occurrence.
|
||||
|
||||
Implementation:
|
||||
`scripts/apply_precipitation_month_metrics_to_climate_data.py:56--90`.
|
||||
Implementation: `build_precip_month_lookup` in
|
||||
`scripts/apply_precipitation_month_metrics_to_climate_data.py`.
|
||||
|
||||
## 9. Driest Month
|
||||
|
||||
@@ -514,15 +514,15 @@ $$
|
||||
Missing monthly values are ignored. An exact tie likewise resolves to the
|
||||
earliest tied month.
|
||||
|
||||
Implementation:
|
||||
`scripts/apply_precipitation_month_metrics_to_climate_data.py:56--90`.
|
||||
Implementation: `build_precip_month_lookup` in
|
||||
`scripts/apply_precipitation_month_metrics_to_climate_data.py`.
|
||||
|
||||
## 10. Summer Specific Humidity
|
||||
|
||||
**Data key:** `avgSummerSpecificHumidityGKg`
|
||||
|
||||
gridMET cells whose centers fall inside a county are weighted by the cosine of
|
||||
their latitude to approximate their relative surface areas on a latitude--longitude
|
||||
their latitude to approximate their relative surface areas on a latitude–longitude
|
||||
grid:
|
||||
|
||||
$$
|
||||
@@ -550,9 +550,8 @@ $$
|
||||
If no grid-cell center falls inside a county, the nearest grid cell to an
|
||||
interior representative point is used.
|
||||
|
||||
Implementation: `scripts/summarize_county_gridmet_humidity.py:297--380`,
|
||||
`scripts/summarize_county_gridmet_humidity.py:409--434`, and
|
||||
`scripts/summarize_county_gridmet_humidity.py:555--605`.
|
||||
Implementation: `_build_county_grid_map`, `_county_means_chunk`, and
|
||||
`summarize` in `scripts/summarize_county_gridmet_humidity.py`.
|
||||
|
||||
## 11. Mean Daily Global Horizontal Radiation (GHI)
|
||||
|
||||
@@ -576,19 +575,19 @@ G_c
|
||||
\frac{\sum_s A_{c,s}G_s}{\sum_s A_{c,s}},
|
||||
$$
|
||||
|
||||
where \(A_{c,s}\) is the estimated overlap area between the county geometry and
|
||||
the 4 km square grid cell centered on site \(s\). A representative-point value
|
||||
where $A_{c,s}$ is the estimated overlap area between the county geometry and
|
||||
the 4 km square grid cell centered on site $s$. A representative-point value
|
||||
is used when a polygon summary is unavailable.
|
||||
|
||||
Implementation: `scripts/summarize_nsrdb_county_polygon_archives.py:189--192`
|
||||
and `scripts/summarize_nsrdb_county_polygon_archives.py:335--378`.
|
||||
Implementation: `site_average_daily_ghi` and `area_weighted_average` in
|
||||
`scripts/summarize_nsrdb_county_polygon_archives.py`.
|
||||
|
||||
## 12. Clear-Sky GHI Reduction Index
|
||||
|
||||
**Data key:** `clearSkyGhiReductionIndex`
|
||||
|
||||
Only rows with valid observed and clear-sky GHI and
|
||||
\(CSGHI_{s,h}\ge50\;\mathrm{W/m^2}\) are treated as daylight rows. For each
|
||||
$CSGHI_{s,h}\ge50\;\mathrm{W/m^2}$ are treated as daylight rows. For each
|
||||
retained row:
|
||||
|
||||
$$
|
||||
@@ -613,11 +612,11 @@ $$
|
||||
|
||||
A representative-point index is used where a polygon summary is unavailable.
|
||||
This definition is the mean of time-row ratios; it is not generally equal to
|
||||
\(1-\sum GHI/\sum CSGHI\).
|
||||
$1-\sum GHI/\sum CSGHI$.
|
||||
|
||||
Implementation:
|
||||
`scripts/summarize_nsrdb_county_polygon_cloud_archives.py:138--218` and
|
||||
`scripts/summarize_nsrdb_county_polygon_cloud_archives.py:222--304`.
|
||||
Implementation: `site_cloud_metrics`, `weighted_metric`, and
|
||||
`summarize_archives` in
|
||||
`scripts/summarize_nsrdb_county_polygon_cloud_archives.py`.
|
||||
|
||||
## Review findings
|
||||
|
||||
@@ -625,4 +624,4 @@ Review findings and their status are kept with the filter reviews in
|
||||
[reviews/](reviews/): findings specific to one filter in that filter's file,
|
||||
and findings that affect several filters in
|
||||
[reviews/00-cross-filter.md](reviews/00-cross-filter.md). Findings keep their
|
||||
original numbers.
|
||||
original numbers; [reviews/README.md](reviews/README.md) lists every one.
|
||||
|
||||
@@ -158,7 +158,7 @@ After changing `app.js`, bump `APP_ASSET_VERSION` and the `app.js?v=` query in
|
||||
and only if `koppenZone` is `Mixed`, with valid and different Köppen codes.
|
||||
- **Tests:** `tests/test_koppen_metric.py` and `tests/test_check_climate_data.py`.
|
||||
|
||||
## 6. Documentation (stage 5, done 2026-09-14)
|
||||
## 6. Documentation (done 2026-09-14)
|
||||
|
||||
- `filter-calculations.md` §1 describes the applied rule, the stripe columns,
|
||||
and the filter; the old method is kept as a short "Previous method" note.
|
||||
@@ -195,5 +195,5 @@ Decisions that were reversed or refined during the browser review:
|
||||
The app already leaves Puerto Rico off the map: `prepareCountyFeature` in
|
||||
`app.js` drops counties with state FIPS 72, and the dropdown and legend are built
|
||||
from the counties on the map. The rows remain in `data/climate-data.csv` and
|
||||
`data/metrics/koppen.csv`. Whether to also remove them from the data files is a
|
||||
separate decision.
|
||||
`data/metrics/koppen.csv`, as decided on 2026-09-13; see "Puerto Rico" in
|
||||
[decisions.md](decisions.md).
|
||||
@@ -50,8 +50,6 @@ run after it.
|
||||
6. `summarize_county_gridmet_humidity.py` → `apply_gridmet_humidity_metric_to_climate_data.py`
|
||||
7. `apply_nsrdb_cloud_metric_to_climate_data.py`
|
||||
|
||||
The README's enrichment list starts at step 2 and omits steps 1 and 3.
|
||||
|
||||
### Problems
|
||||
|
||||
1. **Rerunning a step can destroy data.** The base build writes 12 columns,
|
||||
@@ -66,7 +64,8 @@ The README's enrichment list starts at step 2 and omits steps 1 and 3.
|
||||
2. **Order is implicit.** The sequence lives in the README, in
|
||||
`scripts/county_data_sources.md`, and in each script's assumptions.
|
||||
3. **Column ownership is unclear.** GHI is finalized by the extreme-temperature
|
||||
apply script; wettest/driest month are computed in two places.
|
||||
apply script; wettest/driest month are computed in two places. See findings
|
||||
25 and 26 in [reviews/00-cross-filter.md](reviews/00-cross-filter.md).
|
||||
4. **County aggregation is inconsistent.** See finding 11 in
|
||||
[reviews/00-cross-filter.md](reviews/00-cross-filter.md).
|
||||
5. **No single entry point or final check.** A new user must piece together
|
||||
@@ -160,20 +159,24 @@ For each filter:
|
||||
filter's review file under `docs/reviews/`.
|
||||
2. Decide any rule or method changes with the project owner, and record them in
|
||||
`decisions.md`.
|
||||
3. Record the adopted definition in `filter-calculations.md`.
|
||||
3. Record the adopted definition in `filter-calculations.md`. Until the new
|
||||
values are applied, keep the old definition below it under "Current
|
||||
method".
|
||||
4. Implement the calculation, writing `data/metrics/<metric>.csv`.
|
||||
5. Add a single-column apply step for the current CSV.
|
||||
6. Update the rules in `check_climate_data.py`.
|
||||
7. Add or update unit tests.
|
||||
8. Apply to the CSV, run `check_climate_data.py`, and compare changed counties
|
||||
against expectations.
|
||||
against expectations. Then rename "Current method" to "Previous method" in
|
||||
`filter-calculations.md`, as §1 does.
|
||||
9. Update the app if the value set or display changes.
|
||||
|
||||
## 6. Filter tracker
|
||||
|
||||
Each filter's findings, decisions, and tasks are in its review file. Findings
|
||||
that affect more than one filter are in
|
||||
[00-cross-filter.md](reviews/00-cross-filter.md).
|
||||
[00-cross-filter.md](reviews/00-cross-filter.md), and
|
||||
[reviews/README.md](reviews/README.md) indexes every finding number.
|
||||
|
||||
| # | Filter | Status | Review |
|
||||
| --- | --- | --- | --- |
|
||||
|
||||
@@ -1,10 +1,7 @@
|
||||
# Cross-filter review
|
||||
|
||||
Findings that affect more than one filter. Each finding lives in exactly one
|
||||
review file; the filter reviews it affects link here and record only how it
|
||||
applied to them. Findings keep their numbers across all review files, and new
|
||||
findings take the next number wherever they are filed. A finding that turns out
|
||||
to affect other filters moves here, leaving a link behind.
|
||||
Findings that affect more than one filter. The numbering conventions and an
|
||||
index of every finding are in [README.md](README.md).
|
||||
|
||||
## Findings
|
||||
|
||||
@@ -19,7 +16,7 @@ Affects filters 1 (resolved), 2, 6, and 7.
|
||||
**11. Spatial weighting is inconsistent across metric families.** Base NOAA
|
||||
normals use equal touched-cell weights, Köppen uses area-weighted class
|
||||
shares, gridMET humidity uses
|
||||
\(\cos(\phi)\) weights on cell centers, and NSRDB polygon metrics use
|
||||
$\cos(\phi)$ weights on cell centers, and NSRDB polygon metrics use
|
||||
estimated overlap areas. Cross-metric comparisons should account for these
|
||||
different county aggregation methods.
|
||||
|
||||
@@ -35,7 +32,12 @@ clear-sky reduction (filters 11 and 12) cover both states.
|
||||
`check_climate_data.py` allows these blanks (`OUTSIDE_CONUS`). The notes on
|
||||
the base build in `scripts/county_data_sources.md` say "fallback values are
|
||||
applied" for counties outside NOAA coverage, but `build_county_climate_data.py`
|
||||
leaves them blank (lines 499–520).
|
||||
leaves them blank (`build_county_records`).
|
||||
|
||||
The README's "Current Limitations" states the gap (added 2026-09-15), but the
|
||||
app's county panel shows only "No data". If these counties stay blank, the app
|
||||
should give the reason, for example "Not covered: source data is contiguous
|
||||
U.S. only".
|
||||
|
||||
Affects filters 2–10. Open decision: "Alaska and Hawaii coverage" in
|
||||
[decisions.md](../decisions.md).
|
||||
@@ -99,6 +101,56 @@ neither column is in `data/climate-data.csv`. The list has no entry for
|
||||
|
||||
Affects filters 3 and 4.
|
||||
|
||||
**23. The metric files and `metric_sources.json` were not in git.**
|
||||
`.gitignore` excluded everything under `data/` except the app CSV and the
|
||||
county GeoJSON, so `data/metrics/koppen.csv` and `data/metric_sources.json`
|
||||
existed only locally. On a fresh clone, `check_climate_data.py` failed its
|
||||
metric sources check, and reproduction tier 2 in
|
||||
[pipeline-plan.md](../pipeline-plan.md) (reassemble from committed metric
|
||||
files) was impossible. Found 2026-09-15. *Resolved on 2026-09-15: `.gitignore`
|
||||
now keeps both; see "Committing metric files" in
|
||||
[decisions.md](../decisions.md).*
|
||||
|
||||
Affects every filter, since each adds a metric file.
|
||||
|
||||
**24. The data-sources doc does not cover several pipeline steps.**
|
||||
`scripts/county_data_sources.md` has source sections for Köppen, the NOAA
|
||||
gridded normals, county geometry, NSRDB solar, and nClimGrid-Daily, but none
|
||||
for gridMET: no dataset link, license, variables, or commands for
|
||||
`download_gridmet_data.py` → `summarize_county_gridmet_humidity.py` →
|
||||
`apply_gridmet_humidity_metric_to_climate_data.py`. gridMET appears only in two
|
||||
metric-definition lines. The doc also has no commands for
|
||||
`build_county_diurnal_temperature_range.py` /
|
||||
`apply_diurnal_temperature_range_to_climate_data.py` or
|
||||
`apply_precipitation_month_metrics_to_climate_data.py`. Found 2026-09-15.
|
||||
|
||||
Affects filters 3, 5, 8, 9, and 10; each filter's review adds its section or
|
||||
commands.
|
||||
|
||||
**25. Wettest and driest month are computed in two places.**
|
||||
`build_county_climate_data.py` writes `wettestPrecipMonth` and
|
||||
`driestPrecipMonth` (`_precip_month_extremes`), and
|
||||
`apply_precipitation_month_metrics_to_climate_data.py` recomputes and
|
||||
overwrites them (`build_precip_month_lookup`), reusing the base build's
|
||||
climatology and zonal-mean helpers. The live values are correct only if the
|
||||
second script runs after the base build. Noted in the original review;
|
||||
numbered 2026-09-15.
|
||||
|
||||
Affects filters 8 and 9. This is part of problem 3 in
|
||||
[pipeline-plan.md](../pipeline-plan.md) §1.
|
||||
|
||||
**26. Solar GHI is finalized by the extreme-temperature apply step.**
|
||||
`build_county_climate_data.py` can write
|
||||
`meanDailyGlobalHorizontalRadiationKwhM2Day`, but the live value is written by
|
||||
`apply_locally_extreme_metric_to_climate_data.py`, which prefers polygon GHI
|
||||
and falls back to representative-point GHI. Updating GHI therefore means
|
||||
rerunning the extreme-temperature apply step, and nothing in that script's name
|
||||
says it owns the solar column. Noted in the original review; numbered
|
||||
2026-09-15.
|
||||
|
||||
Affects filters 4 and 11. This is part of problem 3 in
|
||||
[pipeline-plan.md](../pipeline-plan.md) §1.
|
||||
|
||||
## Decisions
|
||||
|
||||
In [decisions.md](../decisions.md): Shared helpers (2026-09-13), and the open
|
||||
@@ -115,7 +167,8 @@ scripts, not solely from UI descriptions. No calculation code was changed. The
|
||||
automated test suite was not executed during this review because `pytest` is
|
||||
not installed in either the system Python environment or the project virtual
|
||||
environment. The suite uses `unittest` and runs without pytest:
|
||||
`python -m unittest discover -s tests`.
|
||||
`.venv\Scripts\python.exe -m unittest discover -s tests`. As of 2026-09-15,
|
||||
all 74 tests pass.
|
||||
|
||||
Section 1 and findings 2, 4, and 11 were updated on 2026-09-14, after the
|
||||
Köppen classification was reworked and applied.
|
||||
|
||||
@@ -6,7 +6,7 @@ updated.
|
||||
**Data keys:** `koppenZone`, `koppenPrimaryClass`, `koppenSecondaryClass`.
|
||||
Calculation: [filter-calculations.md](../filter-calculations.md) §1. Display
|
||||
design and history:
|
||||
[koppen-mixed-display-plan.md](../koppen-mixed-display-plan.md).
|
||||
[koppen-mixed-display.md](../koppen-mixed-display.md).
|
||||
|
||||
## Findings
|
||||
|
||||
@@ -69,7 +69,7 @@ covers at least 50% of the county's land and leads the runner-up by at least
|
||||
- [x] Allow `Mixed` in `check_climate_data.py`.
|
||||
- [x] Add a Mixed climate category to `app.js`, drawn as stripes of the
|
||||
county's top two classes; see
|
||||
[koppen-mixed-display-plan.md](../koppen-mixed-display-plan.md).
|
||||
[koppen-mixed-display.md](../koppen-mixed-display.md).
|
||||
- [x] Replace the plurality description in `filter-calculations.md` §1 and mark
|
||||
review findings 2 and 4 resolved for Köppen (2026-09-14).
|
||||
- [x] Update the Köppen descriptions and script lists in `README.md` and
|
||||
|
||||
@@ -76,6 +76,9 @@ Climate Normals*). Alaska and Hawaii stay blank; see
|
||||
- [ ] Correct `scripts/county_data_sources.md`: Source 2 says the build reads
|
||||
monthly normals files, but it reads the nClimGrid monthly series and
|
||||
averages 1991–2020. Update the `avgTempF` definition line to match.
|
||||
Also remove the "Run the generator" note that fallback values are
|
||||
applied to counties outside NOAA coverage; they are left blank
|
||||
(finding 12).
|
||||
- [ ] Add the area-weighted `avgTempF` to the §7 guardrail on rerunning
|
||||
`build_county_climate_data.py` in
|
||||
[pipeline-plan.md](../pipeline-plan.md).
|
||||
|
||||
@@ -11,7 +11,8 @@ No filter-specific findings yet.
|
||||
|
||||
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).
|
||||
13 (Lexington, VA blank), 17 (missing from the data-sources metric list), and
|
||||
24 (no build or apply commands in the data-sources doc).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -28,7 +28,8 @@ 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).
|
||||
13 (Lexington, VA blank), 17 (missing from the data-sources metric list), and
|
||||
26 (this filter's apply step also writes solar GHI).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -17,8 +17,9 @@ Tmax/RH pair is included in the equal-year average. A minimum valid-day rule
|
||||
would reduce low-biased partial-year counts.
|
||||
|
||||
Cross-filter findings that affect this filter, in
|
||||
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered)
|
||||
and 13 (Lexington, VA uses Rockbridge County as a proxy).
|
||||
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered),
|
||||
13 (Lexington, VA uses Rockbridge County as a proxy), and 24 (no gridMET
|
||||
section in the data-sources doc).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -7,12 +7,13 @@
|
||||
|
||||
## Findings
|
||||
|
||||
No numbered findings yet. Known issue to review: computed in both the base
|
||||
build and the precipitation-month script.
|
||||
No filter-specific findings yet.
|
||||
|
||||
Cross-filter findings that affect this filter, in
|
||||
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered)
|
||||
and 16 (the app's nClimGrid source link returns 404).
|
||||
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered),
|
||||
16 (the app's nClimGrid source link returns 404), 24 (no precipitation-month
|
||||
command in the data-sources doc), and 25 (computed in both the base build and
|
||||
the precipitation-month script).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -7,13 +7,13 @@
|
||||
|
||||
## Findings
|
||||
|
||||
No numbered findings yet. Known issue to review: same as wettest month, which
|
||||
is computed in both the base build and the precipitation-month script; see
|
||||
[08-wettest-month.md](08-wettest-month.md).
|
||||
No filter-specific findings yet.
|
||||
|
||||
Cross-filter findings that affect this filter, in
|
||||
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered)
|
||||
and 16 (the app's nClimGrid source link returns 404).
|
||||
[00-cross-filter.md](00-cross-filter.md): 12 (Alaska and Hawaii not covered),
|
||||
16 (the app's nClimGrid source link returns 404), 24 (no precipitation-month
|
||||
command in the data-sources doc), and 25 (computed in both the base build and
|
||||
the precipitation-month script).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -7,12 +7,12 @@
|
||||
|
||||
## Findings
|
||||
|
||||
No filter-specific findings yet. Known issue to review: cell-center
|
||||
cos(latitude) aggregation differs from other metrics (finding 11).
|
||||
No filter-specific findings yet.
|
||||
|
||||
Cross-filter findings that affect this filter, in
|
||||
[00-cross-filter.md](00-cross-filter.md): 11 (inconsistent aggregation) and
|
||||
12 (Alaska and Hawaii not covered).
|
||||
[00-cross-filter.md](00-cross-filter.md): 11 (inconsistent aggregation),
|
||||
12 (Alaska and Hawaii not covered), and 24 (no gridMET section in the
|
||||
data-sources doc).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -25,11 +25,10 @@ representative-point fallback, and the per-row `source` tag is always
|
||||
`data/nrel/county_polygon_ghi_summary.csv`. The apply step later replaces both
|
||||
the value and the tag, so only the base build's output is mislabeled.
|
||||
|
||||
Known issue to review: finalized by the extreme-temperature apply script.
|
||||
|
||||
Cross-filter findings that affect this filter, in
|
||||
[00-cross-filter.md](00-cross-filter.md): 11 (inconsistent aggregation) and
|
||||
16 (the app's NSRDB source link no longer resolves).
|
||||
[00-cross-filter.md](00-cross-filter.md): 11 (inconsistent aggregation),
|
||||
16 (the app's NSRDB source link no longer resolves), and 26 (finalized by the
|
||||
extreme-temperature apply step).
|
||||
|
||||
## Decisions
|
||||
|
||||
|
||||
@@ -0,0 +1,53 @@
|
||||
# Filter reviews
|
||||
|
||||
Each filter has one review file (`01`–`12`) holding its findings, links to its
|
||||
decisions, and its task checklist. [00-cross-filter.md](00-cross-filter.md)
|
||||
holds findings that affect more than one filter. Review status is tracked in
|
||||
[pipeline-plan.md](../pipeline-plan.md) §6, and every review follows the
|
||||
checklist in §5.
|
||||
|
||||
## Conventions
|
||||
|
||||
- Each finding lives in exactly one review file. The other filter reviews it
|
||||
affects link to it and record only how it applied to them.
|
||||
- Findings keep one number across all review files. A new finding takes the
|
||||
next number (27 as of 2026-09-15) wherever it is filed, and is added to the
|
||||
index below.
|
||||
- A finding that turns out to affect other filters moves to `00`, leaving a
|
||||
link behind.
|
||||
- A resolved finding stays where it is, with its resolution in italics.
|
||||
- A finding accepted as a limitation becomes a caveat in
|
||||
[filter-calculations.md](../filter-calculations.md).
|
||||
|
||||
## Finding index
|
||||
|
||||
Status is kept in each finding, not here.
|
||||
|
||||
| # | Finding | File |
|
||||
| --- | --- | --- |
|
||||
| 1 | Annual temperature weights months equally | [02](02-annual-avg-temperature.md) |
|
||||
| 2 | Base NOAA aggregation is not area-weighted | [00](00-cross-filter.md) |
|
||||
| 3 | Partial precipitation years are accepted | [06](06-annual-precipitation.md) |
|
||||
| 4 | The Köppen fallback can create false data | [01](01-koppen.md) |
|
||||
| 5 | Extreme-day counts are not completeness-normalized | [04](04-extreme-temperature-days.md) |
|
||||
| 6 | The absolute-extreme metric depends on unrelated percentile thresholds | [04](04-extreme-temperature-days.md) |
|
||||
| 7 | Heat Index days are a daily-extrema proxy | [05](05-heat-index-days.md) |
|
||||
| 8 | Heat-year completeness is permissive | [05](05-heat-index-days.md) |
|
||||
| 9 | The GHI formula assumes hourly, 365-day input | [11](11-solar-ghi.md) |
|
||||
| 10 | Clear-sky reduction averages ratios rather than energy totals | [12](12-clear-sky-ghi-reduction.md) |
|
||||
| 11 | Spatial weighting is inconsistent across metric families | [00](00-cross-filter.md) |
|
||||
| 12 | Alaska and Hawaii are not covered by the NOAA and gridMET sources | [00](00-cross-filter.md) |
|
||||
| 13 | Lexington, VA (51678) is missing from the NOAA daily county files | [00](00-cross-filter.md) |
|
||||
| 14 | Helper functions are duplicated across scripts | [00](00-cross-filter.md) |
|
||||
| 15 | The app's source text for three NOAA metrics names the wrong product | [00](00-cross-filter.md) |
|
||||
| 16 | Source links point to retired or missing pages | [00](00-cross-filter.md) |
|
||||
| 17 | The data-sources metric list is out of date | [00](00-cross-filter.md) |
|
||||
| 18 | The data-sources doc describes the retired locally extreme metric | [04](04-extreme-temperature-days.md) |
|
||||
| 19 | The data-sources doc recommends a GHI raster the pipeline does not use | [11](11-solar-ghi.md) |
|
||||
| 20 | The base build labels any solar CSV as representative-point | [11](11-solar-ghi.md) |
|
||||
| 21 | The documented Köppen labels differ from the app | [01](01-koppen.md) |
|
||||
| 22 | The base build's docstring calls its Köppen value a majority class | [01](01-koppen.md) |
|
||||
| 23 | The metric files and `metric_sources.json` were not in git | [00](00-cross-filter.md) |
|
||||
| 24 | The data-sources doc does not cover several pipeline steps | [00](00-cross-filter.md) |
|
||||
| 25 | Wettest and driest month are computed in two places | [00](00-cross-filter.md) |
|
||||
| 26 | Solar GHI is finalized by the extreme-temperature apply step | [00](00-cross-filter.md) |
|
||||
Reference in New Issue
Block a user