Future Impacts of Climate Change on Global Fire Weather: Insight from Weighted CMIP6 Multimodel Ensembles

Abstract Climate is a key driver of spatiotemporal variability in wildfire regimes. Increasingly warmer temperatures and changes in precipitation patterns are linked to an increase in fire danger across the world. There is therefore a need to develop the most reliable projections of future climate-driven fire danger to enable decision-makers and forest managers to prepare for and respond to future fire events. Earth system model (ESM) simulations are the foundation for understanding future changes in fire-conducive weather associated with a warming world. Fire weather projections have typically been expressed by a single model or through a multimodel mean, with the models’ relative strengths and weaknesses rarely taken into consideration. This study presents a novel set of future scenarios in fire-prone conditions, defined by the fire weather index, using a statistical weighting approach that specifically accounts for the performance and interdependence of 26 ESMs from the Coupled Model Intercomparison Project phase 6 (CMIP6). When compared with reanalysis-derived data from 1980 to 2014, the weighting approach substantially reduces multimodel bias, thereby demonstrating its added value in accounting for and reducing model uncertainties. The weighted projections reveal significant increases in seasonal fire weather conditions across 68%–91% of the world’s fire-prone area by the end of the twenty-first century, depending on the emission scenario. Additionally, at least 55% of fire-prone area is expected to be associated with a significant increase in fire weather conditions by 2040. The conclusions highlight the potential benefit to targeted prevention strategies and long-term fire management. Significance Statement This study aims to assess future changes in fire danger driven by climate conditions under different climate change scenarios. The results show an overall increase both in magnitude and geographical expansion in the weather conditions enabling ignition and spread of fires. The value of the results lies in the use of a weighted multimodel ensemble mean, reducing climate model biases with respect to reanalysis data in comparison to previous fire danger studies. This is important to better target areas of the world that are, and will very likely be, at higher fire risk in the coming years.