Projecting the burn probability (BP) under future climate scenarios would provide a scientific basis for the implementation of forest fire adaptation technology. This study compared the changes in the climate, fire weather, and burn probability during the fire season in Daxing’anling, China. A burn probability model was established and used to simulate the daily fire occurrence and spread at baseline (1971–2000) and into the 2030s (2021–2050) based on the outputs from five global climate models (GCMs) (GFDL-ESM2M, Had GEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and Nor ESM1-M) under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). The results showed that the average daily maximum temperature in the fire season will be increased by 2.1 °C (+16.6%) in the 2030s compared with the baseline and precipitation in the fire season will be increased by 7.1%. The average fire weather index (FWI) of the fire season in the 2030s will be increased by 4.2%, but this change is not significant. There will be 39 fires per year in the 2030s, representing an increase of 11.4%. The accuracy of simulated burned areas was 71.2% for the 1991–2010 period. The simulated and observed burned areas showed similar interannual fluctuations during period 1971–2010. The potential burned areas in the 2030s will increase by 18.8% over those in the baseline period and the BP will increase by 19.4%. The implementation of proactive fire management in areas with high predicted BP values will be key for an effective mitigation of future wildfire impacts.
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