The devastating impacts of natural disasters touch thousands of lives each year. People across the globe are forced to prepare for, battle and recover from Mother Nature’s wrath. UC Denver Professor of Mathematics Jan Mandel set out in 2003 to determine if statistical computer models could predict the behavior of one common natural disaster—wildfires. The Data Driven Numerical Simulation of Wildfires project aims to calculate how a wildfire would behave on a scale of hours by looking at the two-way interaction of fire and atmosphere.

Funded by the National Science Foundation, Mandel, principal investigator for the project, assembled colleagues from around the country to build on an existing code from the National Center for Atmospheric Research and develop new statistical computer models to accurately predict the spread of forest fires.

Four years later, Mandel and his team have reached their goals. They have created simulation models that respond to incoming data in a timely manner. The team is now taking data generated from past wildfires to test their models and determine if the simulation mirrors history. Additionally, they are expanding the computer code to accommodate more types of data, including real-time information from the field. “We’re testing the code, piece by piece, to validate that the model works. Our next step will be to layer new data sets to make this simulation even more representative,” says Mandel.

The process of overlapping various data sets to create real-time simulation could have implications beyond fire fighting. With the increasing ferocity of natural disasters due to global climate change, Mandel feels confident that the models developed by his team could better predict hurricanes and other significant weather events.

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