Wildland Fire Weather-Behavior Support


This system is currently being tested and demonstrated by stakeholders, as well as being deployed for training purposes. The tool will go live for the State of Colorado to implement for their own decision-making in summer 2020.


Wildland fires, and more recently, "megafires," have devastated communities and risked the lives of first responders more profoundly than ever. Fire behavior is complex, shaped by feedbacks among heat output, humidity changes, wind, updrafts and downdrafts, fuel, terrain, and so much more. The intensity and aberrant behavior of the largest and most aggressive fires pose life-threatening challenges to fire-suppression efforts. Decision-makers need weather- and behavior-prediction tools to develop more effective strategies to prevent loss of property and lives.


Colorado Fire Prediction System (CO-FPS), Coupled Atmosphere-Wildland Fire Environment (CAWFE)

Basic weather prediction is not enough to effectively inform fire-suppression strategies. To address this need, scientists and engineers in RAL extended the Weather Research and Forecasting (WRF) numerical weather prediction model based on the Coupled Atmosphere Wildland Fire Environment (CAWFE) model, now named WRF-Fire. WRF-Fire simulates growth of a wildfire in response to weather, fuel conditions, and terrain. The WRF Model, in turn, accounts for the fire’s behavior, notably producing fire winds. The simulated fire and atmosphere continually co-evolve, predicting the fire’s extend and rate of spread, flame length, heat, and smoke, thereby alerting firefighting personnel and local agencies to respond accordingly.

Hillside neighborhood in California engulfed in a wildland fire