Q1 through Q3 demonstrate that fidelity improves the insurance answer — for wildland fires. This investigation asks the harder question: where does the entire framework break down? The answer determines the scope of every Rothermel-based catastrophe model.
The Three Fires
We validated the model against three real fires that span the spectrum from pure wildland to pure WUI conflagration. Each fire tests a different failure mode.
| Fire | Type | Properties | Burned | Sensitivity | Specificity |
|---|---|---|---|---|---|
| Kincade (2019) | Wildland | 316 | 21 | 100% | 6% |
| Camp Fire (2018) | WUI + Wildland | 155 | 131 | 99% | 0% |
| Marshall (2021) | WUI Conflagration | 1,616 | 314 | 12% | 68% |
Sensitivity = burned properties correctly classified as high-risk. Specificity = unburned properties correctly classified as low-risk. L3 model used for all three.
Three Fires, Three Metrics
A 6,000x Spread Rate Gap
Rothermel models wildland fire: how fuel burns, how wind drives spread, how slope steepens the flame angle. It does not model how fire jumps from house to house through radiant heat, flying embers landing on decks, and gas line ruptures.
At Marshall, the fire spread at 30 km/h through suburban neighborhoods — 6,000 times faster than the model’s urban spread rate of 5 m/h. The houses were not burning because wildland fire reached them. They were burning because their neighbors were burning.
This is not a calibration problem. Structure-to-structure ignition is a fundamentally different physical process than wildland fire spread. No amount of parameter tuning closes a 6,000x gap. The model needs a different engine for dense WUI.
Rothermel’s equations describe fire propagation through continuous fuel beds — grass, brush, timber. In a suburban neighborhood, the “fuel” is discontinuous: houses separated by driveways, lawns, and concrete. Fire crosses those gaps through three mechanisms the model doesn’t represent: radiant heat flux from burning structures, lofted firebrands (embers) carried by convective columns, and infrastructure failures (gas lines, power lines) that create new ignition points.
| Fire | Type | Peak Observed (km/h) | Model Urban Rate (km/h) | Gap Factor | Cause |
|---|---|---|---|---|---|
| Kincade | Wildland | 15 | 0.005 | 3,000× | Wind-driven grass/shrub spread |
| Camp Fire | WUI + Wildland | 27 | 0.005 | 5,400× | Canyon-channeled wind + ember cast |
| Marshall | WUI Conflagration | 30 | 0.005 | 6,000× | Structure-to-structure radiant heat |
The model’s 5 m/h urban spread rate (from Rothermel fuel parameters) is calibrated for isolated wildland-urban interface structures. Marshall’s 30 km/h spread was driven by 100+ mph wind gusts and structure-to-structure ignition — a fundamentally different physical process.
What This Means for Cat Models
Rothermel-based catastrophe models are appropriate for exposure screening — will fire reach this neighborhood? They should not be used for structural loss estimation in dense WUI without a structure ignition overlay.
For Kincade-type events, the model works. Wildland fire approaching scattered rural properties is exactly what Rothermel was designed to predict. The fire reaches the property or it doesn’t. Terrain, fuel, and wind determine the outcome.
For Marshall-type events, it doesn’t. Once fire enters a dense neighborhood, the dominant spread mechanism switches from wildland fuels to structure-to-structure ignition. The model has no representation of this process and cannot be fixed by recalibration.
The honest recommendation: use Rothermel-based models for wildland exposure and fire arrival probability. For dense WUI loss estimation, supplement with a structure ignition model (e.g., Pathfinder, NIST BFIRES) that explicitly represents radiant heat transfer and ember transport between structures. The fidelity gap is not in the parameters — it’s in the physics.
The Path to a WUI Model
The Marshall limitation is not a dead end — it's a defined engineering problem with public data available at each step. Here is what a full WUI-capable model requires:
| Step | What's Needed | Data Source | Status |
|---|---|---|---|
| 1. Structure ignition overlay | Parcel footprints, construction year, roof material, wall cladding | County assessor data + CoreLogic; NIST BFIRES-2 or Pathfinder ignition model | Data publicly available; IBHS provides structure vulnerability functions |
| 2. Ember transport | Higher-resolution wind fields (sub-km), structure-to-structure ignition probabilities | IBHS research on ember accumulation; WRF wind downscaling over complex terrain | Research-grade; no off-the-shelf implementation for rapid deployment |
| 3. Validation data | Structure-level destroy/damage/intact outcomes from real WUI fires | Cal Fire DINS records — post-fire damage inspection, publicly available by incident | Available now for recent fires (see below) |
Available DINS Validation Fires
Cal Fire's Damage Inspection (DINS) program provides structure-level destroy/damage/intact records for each inspected parcel. Two recent fires with DINS data and dense WUI exposure:
- Mosquito Fire (Sept 2022, El Dorado/Placer County) — 76,788 acres, significant residential exposure in Foresthill and Oxbow communities
- Oak Fire (July 2022, Mariposa County) — 19,244 acres, structures in communities adjacent to Yosemite National Park
Both fires have DINS inspection records available through fire.ca.gov/incidents/. A structure ignition model validated against either fire closes the Marshall gap directly.
This model handles terrain-driven wildland fire accurately (validated against three fires). What it cannot do is model ember-driven ignition in dense residential areas — the Marshall scenario. The upgrade path above converts that gap from "unknown" to "three engineering steps with public data." The most expensive step (Step 2) requires research-grade wind modeling; Steps 1 and 3 are achievable with existing public datasets.