摘要：Large wildfires across parts of France can cause devastating damage whichputs lives, infrastructure, and the natural ecosystem at risk. In the climatechange context, it is essential to better understand how these largewildfires relate to weather and climate and how they might change in a warmerworld. Such projections rely on the development of a robust modelingframework linking large wildfires to present-day atmospheric variability.Drawing from a MODIS product and a gridded meteorological dataset, we deriveda suite of biophysical and fire danger indices and developed generalizedlinear models simulating the probability of large wildfires (>100ha) at8km spatial and daily temporal resolutions across the entire country overthe last two decades. The models were able to reproduce large-wildfireactivity across a range of spatial and temporal scales. Differentsensitivities to weather and climate were detected across differentenvironmental regions. Long-term drought was found to be a significantpredictor of large wildfires in flammability-limited systems such as theAlpine and southwestern regions. In the Mediterranean, large wildfires werefound to be associated with both short-term fire weather conditions andlonger-term soil moisture deficits, collectively facilitating the occurrenceof large wildfires. Simulated probabilities on days with large wildfires wereon average 2–3 times higher than normal with respect to the mean seasonalcycle, highlighting the key role of atmospheric variability in wildfirespread. The model has wide applications, including improving ourunderstanding of the drivers of large wildfires over the historical periodand providing a basis on which to estimate future changes to large wildfiresfrom climate scenarios.
