Last Chance Fire - WRF Simulation

Last Chance Fire simulation. The simulated fire was a grass fire that spread through Last Chance, Colorado, on June 25, 2012. The simulation shows both smoke concentration and burned areas as the fire spread.

To safely manage wildland fires, decision makers need reliable, accurate, frequently updated, easily accessible, geo-referenced current and predicted weather and fire behavior information. Timely information allows decision makers to better assess current conditions and future trends. Reliable information about the potential for rapid rate of fire spread and extreme fire behaviors is essential to saving life and property.

Currently, operational wildland fire spread prediction systems are not coupled to numerical weather prediction models. These systems often rely on wind fields coarsely resolved in space and time. However, highly resolved wind fields in time and space are needed to accurately predict fire spread when flows are rapidly evolving due to storm outflows, density currents, frontal passages, and other factors, or when the winds are spatially variable due to complex terrain effects. Furthermore, large wildfires result in significant surface heat fluxes that generate strong updrafts and consequently intensify local winds, which in turn cause more rapid fire spread rates. Large wildfires also result in significant smoke plumes that can affect radiative transfer, while lofted particulate matter and moisture can result in the formation of pyrocumulus clouds. All of these phenomena can only be predicted using coupled models. Therefore, development of an operational coupled wildland fire spread capability – coupling the spread model with the NWP model – is essential for accurate wildland fire spread prediction.

To achieve this goal RAL researchers are extending capabilities of the Weather Research and Forecasting (WRF) NWP model based on the Coupled Atmosphere Wildland Fire Environment (CAWFE) model. The new developments focus on improvements to the fire spread model and the level-set based fire perimeter tracking algorithm, as well as investigations into alternative fuel models and fuel moisture data. These developments are being included in the community WRF-Fire model. The modeling system is being extensively evaluated using observed fires in Colorado and other parts of the United States.