Serving Notes
FireWx-FM predicts 12-hour active-fire occupancy on a native 5 km grid. This page records the serving choices needed for full-map inference.
Use The Fixed Channel Contract
The model consumes a 16-channel tensor in [channel, y, x] order. The channel list and units are defined in:
models/metadata/input_channels.json
docs/inference_contract.md
Two details are especially important:
- The CAPE channel is NOAA HRRR CAPE for the 0-3000 m above-ground layer.
- Continuous channels are z-score normalized with
models/metadata/input_normalization_stats.json.
Apply The No-Exposure Serving Contract
The released checkpoint is served with channels 14 and 15 zeroed after normalization:
14: housing density.15: population.
The output should therefore be interpreted as active-fire occupancy probability under the released no-exposure serving contract.
Use Overlap-Window Inference
Training uses 32 by 32 crops to sample sparse active-fire labels. That crop size is not the full-map serving tile size. For CONUS-scale inference, use the default serving settings:
| Setting | Value |
|---|---|
| Window | 256 |
| Stride | 64 |
| Halo crop | 32 |
| Phase shifts | 0,4,8,12 along y and x |
The phase ensemble evaluates shifted versions of the same input and averages the shifted-back probability maps. This reduces dependence on tile origin and produces a smoother full-domain probability field.
Preserve Validity Masks
The validity masks are numeric input features:
dynamic_valid: dynamic weather-input validity after cache construction.static_valid: fraction of static layers valid after reprojection.
They are not output masks. They should be supplied with the physical channels so sanitized missing values are not confused with true zeros.