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The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems

Author(s): Daniel Jensen, John T. Reager, Brittany Zajic, Nick Rousseau, Matthew Rodell, Everett Hinkley
Year Published: 2018
Description:

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission with the USDA Forest Service's historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25 degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship's utility for the future development of national-scale predictive capability.

Citation: Jensen, Daniel; Reager, John T.; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett. 2018. The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems. Environmental Research Letters 13(1):014021.
Topic(s): Fire Behavior, Simulation Modeling, Weather
Ecosystem(s): None
Document Type: Book or Chapter or Journal Article
NRFSN number: 17379
FRAMES RCS number: 25903
Record updated: May 16, 2018