Scientists have developed a new computer modeling technique which can predict wildfire behavior when it interacts with other weather factors.
The new technique is a product of a collaboration between the National Center for Atmospheric Research (NCAR) and the University of Maryland. Scientists involved in the study used satellite observations of active wildfires and combined it with the simulations of earlier studies showing weather and fire interaction and behavior. The end result showed a more accurate and crucial details of the active wildfires.
“With this technique, we believe it’s possible to continually issue good forecasts throughout a fire’s lifetime, even if it burns for weeks or months,” said NCAR scientist Janice Coen, the lead author and model developer, in a statement. “This model, which combines interactive weather prediction and wildfire behavior, could greatly improve forecasting—particularly for large, intense wildfire events where the current prediction tools are weakest.”
The new tool dubbed as the Coupled Atmosphere-Wildland Fire Environment (CAWFE) computer model connects weather with fire and vise versa. It is then able to predict how big a certain wildfire can be which can allow firefighters prepare better. It uses satellite images captured by NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) instrument which provides coverage update every 12 hours with a higher resolution letting scientists see the perimeter of an active wildfire more clearly.
Furthermore, this new technique shows "potential to supplement fire management and decision support systems, sharpening the local, regional, and continental monitoring of wildfires.”
“Lives and homes are at stake, depending on some of these decisions, and the interaction of fuels, terrain, and changing weather is so complicated that even seasoned managers can’t always anticipate rapidly changing conditions,” Coen said. “Many people have resigned themselves to believing that wildfires are unpredictable. We’re showing that’s not true.”
The study was published in the Nov. 15 issue of the Geophysical Research Letters.
