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Why This Exists

This is a citizen science project. We built it because the people who live in the path of western wildfires and droughts deserve access to the same data and analysis that federal agencies and insurance companies use to make decisions about their lives,for free, without a paywall, without a login, without asking permission.

What We Commit To
Data accuracy above everything. Every number traces to a specific federal, state, or provincial data source. When we make a mistake, we correct it publicly. When a claim is uncertain, we say so.
Boots on the ground. This is not a dashboard built from a desk. We verify conditions in the field, cross-reference agency reports with local observations, and update analysis based on what’s actually happening.
Real policy analysis. We read the bills, track the budgets, and grade the agencies on whether their actions match the threats the data identifies.
A self-healing data network. When the government turns off a data source, we find alternatives. When those get turned off, we derive equivalent insights from satellite imagery, state agencies, academic repositories, allied nations.
Always free, always honest. No subscriptions. No premium tier. No sponsored content. No softening findings to protect relationships. The people in fire and drought country are the audience.
Open methods, public data. Every number on this site traces to a specific federal, state, or provincial data source. No proprietary data. No black boxes. The model, training code, and data pipelines will be published to a public repository once the 2026 validation period is complete. If you find an error, tell us.
Firewatch Enginev1.0 · Production model

Our prediction model,Firewatch,is a gradient-boosted decision tree model (XGBoost) trained on 37 million observations across the western fire corridor (11 states + BC). It draws on 26 years of daily climate at 4km resolution, 1,830 SNOTEL stations, 9,800+ large-fire perimeters as prediction targets, 312,000 fires for cause classification, fuel maps, soil moisture, snow disappearance timing, and topography to identify where large fires are most likely to burn.

0.911
AUC-ROC
Held-out test (2020–2024)
10.4x
Lift over base rate
Base rate: 0.1% of cells
37M
Training observations
50 features

AUC-ROC of 0.911 means: given a cell that burned and a cell that didn’t, the model ranks the burned cell higher 91% of the time. It is a ranking metric, not a hit rate,at the 0.1% base rate, most flagged cells will not burn in a given month. The model identifies where large fires (>1,000 acres) concentrate, not individual ignitions. 2026 is the live public validation period.

Top PredictorsSHAP importance · v1.0
1. Seasonality
6. Fuel moisture (current)
2. Monthly precipitation
7. VPD × slope interaction
3. Elevation
8. Peak VPD
4. Lightning fire history
9. VPD — 2-month lag
5. Fuel moisture — 3-month lag
10. Slope

15. Snow disappearance date (new to v1.0, after Westerling et al. 2006)

Data Sourcesv1.0 · All public
DatasetSourceCoverage
Daily climate (VPD, fuel moisture, temp, precip, wind, BI)gridMET (U of Idaho)2000–2025, 4km, 32–49°N
Wind direction (east wind frequency)gridMET, 4km daily2000–2025, % summer easterly
Snowpack (daily SWE)NRCS SNOTEL + SNODAS1,830 stations, 11 states, 1981–2026
Snow disappearance dateComputed from SNOTEL2000–2025 (novel feature)
Soil moisture (8-inch)SNOTEL SMS sensors55 stations, summer 2000–2025
Fire perimetersNIFC WFIGS + MTBS6,853 perimeters, 11 states, 1992–2024
Burn severityUSGS MTBS7,949 fires >1,000 ac, 1984–2024
Fire causeFPA-FOD312,000 fires, lightning vs human
Canadian firesNFDB155,198 BC records + 1,878 polygons
Fuel type + canopyLANDFIREFBFM40, EVT, canopy cover, 30m
TopographyGMTED2010 DEMElevation, slope, aspect, 250m
Climate indicesNOAA CPCENSO Niño 3.4, PDO, ENSO velocity
Reservoir storageUSBR Hydromet, USACE, CDEC39 reservoirs, 11 states, real-time
Air quality (PM2.5)EPA AQS + PurpleAir700 monitors + 12,000+ sensors
Summer temperatureNOAA NCEI131 years (1895–2025), 11 states
Smoke feedbackEPA AQS annual PM2.5Prior-year smoke as predictor (novel)
Model Historyv0.1 → v1.0
VersionAUCKey change
v0.1–0.30.67–0.72PNW annual grid, added topography + LANDFIRE + fire cause
v0.40.841Monthly resolution (biggest single improvement)
v0.5–0.60.90–0.91Full western corridor, lag features, interaction terms, ensemble
v0.70.913*SNODAS gridded SWE. *Leaked metric — test set used during tuning.
v0.80.901Proper 3-way split, ENSO/PDO, held-out test.
v0.90.90911-state SNOTEL, SWE anomaly, VPD×SWE interaction.
v1.00.911Snow disappearance, east wind, prior-year precip, reservoir anomaly, ENSO velocity, soil moisture, smoke feedback. 50 features. First public production release.

Roadmap

Planned · Not yet in production

TargetComponentGap it closes
v1.1Live forecast + fire trackingDaily 4km risk grids for 2026 fire season. VIIRS satellite hotspot detection (375m) for near-real-time active fire tracking.
v1.2Fuel + vegetationLANDFIRE fuel loading maps and NDVI-derived live fuel moisture. Closes the biggest input gap in the current model.
v1.3Wind + smoke dispersionSub-daily HRRR winds to capture Diablo, Santa Ana, and east wind events. Atmospheric mixing height for real smoke transport modeling. Fuel-composition smoke toxicity.
v2.0Data quality + coverageResolve SWE measurement discontinuity at 2010 (SNOTEL station interpolation vs. SNODAS gridded). Expand Canadian coverage with ECCC station data and CFS reanalysis.
v2.1Consequence modelingFire behavior (rate of spread, flame length, spotting). WUI structure exposure mapping. Post-fire burn severity (dNBR) for damage assessment and model retraining.
Version targets are goals, not commitments. Order may shift based on data availability, contributor expertise, and what fire season reveals. If you can help close one of these gaps, get in touch.
Compared to Published Models
NFDRS/WFAS0.780

Station-level, no spatial prediction

SMLFire1.0 (Buch et al. 2023)0.800

25km global, monthly (GMD). Uses r not AUC-ROC,0.80 is approx.

Burn-P3 (Canada)0.750

Monte Carlo simulation

FireCast (UCLA)0.780

Daily, 375m, not public

Firewatch v1.00.911

4km monthly, 50 features, held-out test, snow disappearance, soil moisture, ENSO velocity, smoke feedback, public data only

Known Limitations

Predicts large fires (>1,000 acres) only — not ignitions or small fires.
Wind at 4km daily average — extreme events (2020 Labor Day) underrepresented.
SWE methodological discontinuity at 2010 (SNOTEL IDW → SNODAS gridded).
BC predictions use nearest-grid climate interpolation.
Smoke forecast is distance-based, not fuel-composition-aware. A proper smoke model requires mapped fuel condition, plant stress, live fuel moisture (NDVI), and sub-4km atmospheric mixing height — all on the roadmap.
This is a research platform, not an operational tactical tool for evacuation or life-safety decisions.
Contact & Support

This platform is free, independent, and updated daily. No paywalls, no ads, no sponsors to answer to. Just the data. If it’s useful to you, here’s how to get involved.

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We’re building a network of named expert contributors,scientists, modelers, and domain specialists who maintain specific components of the platform.

Get in touch
Data correctionsIf you spot an error in our data, sourcing, or analysis, email us. We fix mistakes the same day and credit the correction.
Media & pressJournalists, researchers, and producers are welcome to use our data and visualizations with attribution to PCSN / pnw-firemap.org.
PartnershipsEmergency managers, state agencies, water utilities, and nonprofits working on fire and drought resilience in the western corridor.

All data from publicly available federal, state, and provincial sources. Model trained on 2000–2019, validated on held-out test years 2020–2024 never seen during training.