Wildland Fire Weather-Behavior Support

Hillside neighborhood in California engulfed in a wildland fire
Challenge: 

Wildland fires, and more recently, "megafires" have devastated resident populations, property, and risked the lives of first responders more profoundly than ever. Fire behavior is a complex feedback system characterized by heat output, humidity changes, updrafts, fuel, terrain, and so much more. The intensity and aberrant behavior of these fires pose life-threatening challenges to fire-suppression efforts. These decision-makers need weather- and behavior-prediction tools to develop more effective strategies to prevent loss of property and lives.

Solution: 

Basic weather prediction is not enough to effectively form fire-suppression strategies. To address this need, scientists and engineers in RAL extended the Weather Research and Forecasting (WRF) NWP model based on the Coupled Atmosphere Wildland Fire Environment (CAWFE) model, now named WRF-Fire. The CAWFE Modeling System simulates growth of a wildfire in response to weather, fuel conditions, and terrain. These elements constantly exchange their inputs Heat and water vapor fluxes from the fire alter the atmospheric state, notably producing fire winds. The atmospheric state continually evolves as do changes in humidity (including effects from the fire), simultaneously affect fire behavior. The WRF-Fire can illustrate how fast and in what direction the fire propagates, thereby alerting fireground personnel and local agencies to respond accordingly.

Benefits: 

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 on 1 July 2020.