The future of wildfire prediction: WRF-Fire
Wildfire Weather-
Behavior Support
Megafires have become the new normal for the
American west. Attempting to manage them is like trying
to manage a hurricane or tornado. These fires have
devastated communities and risked the lives of first
responders more profoundly than ever.
Fire behavior is complex, shaped by interactions among
heat output, humidity changes, wind, updrafts and
downdrafts, fuel, and terrain, naming only a few. The
intensity and aberrant behavior of the largest and most
aggressive fires pose life-threatening challenges to fire management
efforts. Decision-makers need weather and
wildfire-prediction tools to develop more effective
strategies to protect property and lives.
Combining Wildfire & Atmospheric Models
Basic weather prediction is not enough to effectively inform fire-management strategies. To fill this gap, RAL scientists and engineers extended the Weather Research and Forecasting (WRF) numerical weather prediction model to simulate how a wildfire behaves in response to weather, fuel conditions, and terrain. In turn, the wildfire’s effect on the local weather is also simulated. The model-generated fire and atmosphere continually co-evolve, predicting the fire’s extent and rate of spread, flame length, heat, and smoke, thereby alerting firefighting personnel and local agencies to respond accordingly.
WRF-Fire is a physics module within WRF ARW that allows users to model the growth of a wildland fire in response to environmental conditions of terrain slope, fuel characteristics, and atmospheric conditions, and the dynamic feedbacks with the atmosphere. It is implemented as a physics package with two-way coupling between the fire behavior and the atmospheric environment allowing the latent and sensible heat released by the fire to alter the atmosphere surrounding it, i.e. ‘create its own weather’.
ral.ucar.edu/wrf-fire
1 окт 2024
