Forest Fire Predictor Model
November 14, 2013

New Computer Model May Accurately Predict Path Of Forest Fires

Brett Smith for - Your Universe Online

Just as forest fire season appear to be winding down, scientists at the National Center for Atmospheric Research (NCAR) and the University of Maryland have developed a new computer model that can constantly update daylong predictions during extensive blazes, according to a new report in an online issue of Geophysical Research Letters.

“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 study author Janice Coen, a wildfire expert at NCAR. “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.”

Current models only estimate the speed of the leading edge a fire and don’t consider crucial interactions between fire and weather.

Coen has been developing a tool known as the Coupled Atmosphere-Wildland Fire Environment (CAWFE) computer model over the past decade. Using CAWFE, she has been able to simulate how large historical fires grew.

However, CAWFE could not reliably predict the behavior of an ongoing fire without the most updated fire and weather data. An accurate forecast to accomplish this would have to include updates on the effects of firefighting and natural processes such as spotting, when embers from a fire are sent high into the air and dropped ahead of a fire, igniting new flames.

To create a more refined model, Coen turned to her colleague Wilfrid Schroeder from the University of Maryland to produce higher-resolution fire data from a new satellite instrument called the Visible Infrared Imaging Radiometer Suite (VIIRS). Launched in 2011, the satellite provides coverage of the Earth at intervals of 12 hours or less. The satellite’s high resolution data allowed the two researchers to get data on the active fire perimeter in much better detail.

By feeding data from the VIIRS fire observations into the CAWFE model, the researchers could refresh their model every 12 hours using the latest observations of the fire — a process known as cycling.

The team said their model could have accurately predicted the course of the 2012 Little Bear fire in 12- to 24-hour increments during the five days of the blaze. They added their model could simulate the entire lifetime of very long-lived fire, from start to finish.

“The transformative event has been the arrival of this new satellite data,” said Schroeder, a professor of geographical sciences who is also a visiting scientist with NOAA. “The enhanced capability of the VIIRS data favors detection of newly ignited fires before they erupt into major conflagrations. The satellite data has tremendous 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.”