PNNL

Abstract

Wildfires have significant hydrological and ecological impacts in the western U.S. Using a high-resolution regional climate simulation and wildfire observations for 1984-2018, this study investigates the antecedent hydrometeorological conditions (AHCs) of wildfires in the western U.S. During the warm season (April - September), the wildfire AHCs feature diverse surface pressure (PS), soil moisture (SM), and longwave/shortwave radiation (LW/SW) conditions. K-means clustering classifies wildfires into four types with distinct AHCs: low-PS-type and high-PS-type with lower and higher PS anomalies, respectively, LW-type featuring intense LW but weak SW anomalies, and wet-soil-type with wet soil anomalies. Each fire cluster represents 22%-27% of all the wildfires, featuring different combinations of climate and vegetation conditions and their diverse relations to regional hydrometeorological conditions, with wet-soil-type fires often exhibiting opposite correlations with AHCs compared to those of the other three types. In five major Köppen climate zones over the western US, type-based predictions improve the seasonal wildfire prediction accuracy (R2) by 10% compared to prediction without classification. Such improvement comes from separating the opposite relationships between wet-soil-type fires and seasonal AHCs from the other three types, along with separating LW-type fires, which include most of the lightning-ignited fires that occur more randomly. Increases in wildfire occurrence during 1984-2018 are dominated by the increases in the LW-type fires, while the wet-soil-type fires have decreased, consistent with the long-term drying in the western U.S.