Trailblazer: Development of a global empirical-statistical framework for the probabilistic assessment of wildfire risk under climate change

The occurrence of extensive wildfires across the world in recent years has raised important questions about the extent to which the changing nature of such incidents can be attributed to human-induced climate change. Offering reliable answers to these questions is essential for communicating risk and increasing resilience to major wildfires. While attribution of extreme events to anthropogenic climate change has developed into an important subfield of climate science, wildfires have received less attention compared to other heat-related extremes such as heatwaves and drought. This is primarily due to the scarcity of the observational datasets and the absence of a widely agreed-upon and effective methodological framework for wildfire attribution.

This PhD project, funded by the 'Trailblazer' scheme and led by doctoral researcher Zhongwei Liu, aims to develop a globally applicable framework to better understand and quantify how wildfire risk is responding to a changing climate. The framework is based on an empirical-statistical methodology, facilitating its application to ’fire weather’ extremes from both observational records and the latest generation of global climate model ensembles. The conclusions drawn from this work will provide a platform to guide future attribution analysis of fire weather events, and facilitate reliable recommendations for responding to the hazards associated with wildfires and enhancing resilience in the face of climate change.