fire_preprocess

A standalone Python tool that adds fire-specific input fields (NFUEL_CAT and ZSF) directly to WPS output files (geo_em or met_em) for use with the Community Fire Behavior Model (https://github.com/NCAR/fire_behavior), bypassing the traditional workflow that requires converting data to WPS geogrid binary format and editing GEOGRID.TBL.

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1. Environment setup

conda (recommended)

conda env create -f environment.yaml
conda activate fire_preprocess

pip

pip install -r requirements.txt

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2. Retrieving input data

Two datasets are required. Both are available as GeoTIFF and can be downloaded for any region of the contiguous US.

Fuel categories (NFUEL_CAT)

Download from the LANDFIRE data viewer: https://landfire.gov/viewer/

1. Draw your area of interest on the map.
2. Under Fire Behavior Fuel Models, select either:
   • FBFM13 – Anderson 13-category model (default)
   • FBFM40 – Scott & Burgan 40-category model
3. Choose GeoTIFF as the output format and download.
4. If the download covers multiple tiles, merge them before use:

   rio merge LF2025_FBFM13_*.tif --output fuel.tif

High-resolution terrain (ZSF)

Download from the USGS National Map / 3D Elevation Program (3DEP): https://apps.nationalmap.gov/downloader/

1. Under Elevation Products (3DEP), select 1/3 Arc-Second DEM (~10 m). 1 Arc-Second (~30 m) is also available if coarser resolution is acceptable.
2. Select your area of interest and download.
3. Merge tiles if needed:

   rio merge USGS_13_*.tif --output dem.tif

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3. Running the tool

Command-line usage

python fire_preprocess.py \
    --wps-files geo_em.d02.nc \
    --fuel      fuel.tif \
    --zsf       dem.tif \
    --namelist  namelist.wps \
    --domain    2

All arguments can also be supplied via a YAML config file (see below).

Command-line arguments

Argument	Default	Description
--wps-files	—	WPS output file (geo_em/met_em) or glob pattern (e.g. 'met_em.d02.*.nc')
--fuel	—	LANDFIRE fuel-category GeoTIFF (NFUEL_CAT source)
--zsf	—	High-resolution terrain DEM GeoTIFF (ZSF source)
--namelist	namelist.wps	Path to namelist.wps
--domain	1	Domain number, used to read the correct subgrid_ratio_x/y from the namelist
--fuel-table	fbfm13	Fuel remapping table (see below)
--overwrite	false	Overwrite existing fire fields without prompting
--config	config.yaml	YAML config file (loaded automatically if present)

Config file

Any argument can be set in a YAML config file. CLI flags override config values.

wps_files:  'met_em.d02.2024-09-08_*.nc'
zsf:        /path/to/dem.tif
fuel:       /path/to/fuel.tif
namelist:   namelist.wps
fuel_table: fbfm13
domain:     2
overwrite:  false

Run with a config file:

python fire_preprocess.py --config config.yaml

Fuel tables

Name	Description
fbfm13	Anderson 13-category model — LANDFIRE codes 1–13 passed through directly (default)
fbfm40	Scott & Burgan 40-category model — LANDFIRE 3-digit codes (101–204) passed through unchanged; CFBM converts them to Anderson 13 internally via Crosswalk_from_scottburgan_to_anderson
fbfm40_to_anderson13	Scott & Burgan 40 pre-converted to Anderson 13 using the exact crosswalk from CFBM's fuel_mod.F90

A custom remapping can be supplied as a two-column CSV file:

source,target
1,1
2,2
101,1
91,14

python fire_preprocess.py --fuel-table my_remap.csv ...

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Background

The standard CFBM workflow requires:

1. Downloading LANDFIRE and USGS terrain data in their native formats
2. Converting both datasets to WPS geogrid binary format (a technically involved process with no widely-available open-source tooling)
3. Manually adding NFUEL_CAT and ZSF entries with subgrid=yes to GEOGRID.TBL
4. Re-running geogrid.exe to embed the fire fields

fire_preprocess replaces steps 2–4 entirely. It reads GeoTIFF directly, reprojects to the WRF fire subgrid using the projection parameters and subgrid_ratio_x/y values from namelist.wps, and writes NFUEL_CAT and ZSF into the existing WPS netCDF files. The rest of the workflow (real.exe → WRF) is unchanged.