Full Citation: Guyette, Richard P.; Thompson, Frank R.; Whittier, Jodi; Stambaugh, Michael C.; Dey, Daniel C. 2014. Future fire probability modeling with climate change data and physical chemistry. Forest Science 60(5):862-870.
External Identifier(s): 10.5849/forsci.13-108 Digital Object Identifier
Location: Contiguous U.S.
Ecosystem types: None specified
Southwest FireCLIME Keywords: None
FRAMES Keywords: dendrochronology, fire frequency, fire scars, climate change, fire probability, ecosystems, GCM - Global Climate Model , physical chemistry, PC2FM - Physical Chemistry Fire Frequency Model , fire models, fire scar analysis, wildfires, climate change, precipitation, statistical analysis, temperature, ecosystem dynamics, fire management, forest management, SFP - Southern Fire Portal

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

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.

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.