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Future fire probability modeling with climate change data and physical chemistry

Richard P. Guyette, Frank R. Thompson III, Jodi Whittier, Michael C. Stambaugh, Daniel C. Dey
Summary - what did the authors do and why?

The authors produced a model to predict a spatially explicit map of future fire probability and fire frequency based on climate projection models across the U.S.

Publication findings:

The authors found that future fire probabilities increased with increasing temperature; however predictions for each of the climate models diverged for the southwestern U.S. The CGCM data resulted in decreased future fire probability (0 to ?30%) while the GFDL data resulted in increased fire probability (near 0 to greater than 40%). The authors suggest this discrepancy is due to the limitations in predicting precipitation and moisture conditions and their effect on fuel production.

Climate and Fire Linkages

How do temperature, relative humidity, and vapor pressure deficit relate to fire frequency, rotation, and return interval?

The authors found that future fire probabilities increased with increasing temperature; however predictions for each of the climate models diverged for the southwestern U.S. The CGCM data resulted in decreased future fire probability (0 to ?30%) while the GFDL data resulted in increased fire probability (near 0 to greater than 40%). The authors suggest this discrepancy is due to the limitations in predicting precipitation and moisture conditions and their effect on fuel production.

How do snowpack and precipitation (snow/rain) relate to fire frequency, rotation, and return interval?

Predictions for each of the climate models diverged for the southwestern U.S. The CGCM data resulted in decreased future fire probability (0 to ?30%) while the GFDL data resulted in increased fire probability (near 0 to greater than 40%). The authors suggest this discrepancy is due to the limitations in predicting precipitation and moisture conditions and their effect on fuel production.