Quantifying the current and future likelihood of the 2022 extreme wildfire weather conditions in France with anthropogenic climate change

Abstract

In 2022, southwestern France experienced an exceptional wildfire season, recording a burned area 14 times higher than the 2006–2023 average. Here, we assess the rarity (return period) of the fire weather conditions observed in 2022 and how anthropogenic climate change (ACC) has already altered and will continue to alter the probability of fire weather conditions associated with the three largest wildfires (Landiras-1: 12 552 ha; Landiras-2: 7124 ha; La Teste-de-Buch: 5709 ha). Drawing from the daily Fire Weather Index (FWI) computed from two reanalysis datasets (1959–2023) and a nationwide wildfire record dataset (2006–2023), we first sought to quantify the rarity of those conditions across a range of spatial (local vs. regional) and temporal (fire duration vs. 30 d window) scales. Our results demonstrate that the rarity of FWI conditions is generally the highest at local and fire duration scales with the associated return periods increasing from 6 to 34 years, from 22 to 38 years, and from 6 to 101 years when moving from the coarsest to the finest spatiotemporal scale for the Landiras-1, Landiras-2, and La Teste-de-Buch wildfires, respectively. Using climate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we examined how ACC has modified and will modify the probability of such fire weather conditions over the period 1950–2100. The multi-model median suggests that, in 2022, FWI conditions of the same exceedance probability as the 2022 wildfire-related conditions were approximately 2–10 times more likely under anthropogenic and natural forcings combined than under the natural-forcing-only climate, depending on the spatiotemporal scale, with considerable inter-model spread. By the end of the century under the Shared Socioeconomic Pathway 2-4.5 (SSP2-4.5), these FWI conditions are projected to become roughly 1 to 2 orders of magnitude more probable, with still large inter-model uncertainty. Our study underlines the growing influence of ACC on the risk of extreme wildfires in France across a range of scales.