Quantification of Climate-Wildfire Relationships Taking Into of Spatiotemporal Heterogeneity at Regional Scale: The Subtropical China Case

Understanding the extent to which climate affects interannual wildfire variability is key to project and mitigate wildfire. However, obtaining a robust quantification of the climate-wildfire relationship at large spatial scales remains challenging. This study employed hierarchical Bayesian framework to estimate the effect of drought on forest wildfire frequency in subtropical China. We quantified the drought-wildfire relationship across the subtropical China that the probability of excess wildfire (i.e., above normal wildfire activity level) shown disproportionate growth from 2.4% to 76.7% when vapor pressure deficit (VPD) increased from -3 to 3 (z-score). The extreme wildfires only occurred when VPD exceeds 0.5 (z-score). Our results suggest that Bayesian hierarchical model performs better in quantifying the impact of drought on wildfire by taking into account spatiotemporal heterogeneity of climate-wildfire relationship.