Extreme fire events have become increasingly frequent all over the world, as seen in recent fire seasons in Turkey, Southern Europe, Brazil, Chile, California, South Korea, and Canada. These extremes and megafires have disproportionate impacts on society and all components of the Earth system, yet much remains to be understood about their characteristics, drivers, links to climate change, methods for quantifying their impacts, and effective mitigation and prevention strategies.
A key area is how extreme fires are represented in fire models. Their stochastic behaviour, uncertainties in observations, and the difficulty of capturing local processes within global frameworks make simulating extremes and their impacts a persistent challenge for coupled models. Emerging big data and machine learning approaches show promise in capturing such events but remain limited in their ability to represent feedback to vegetation, soils, and the broader Earth system.
This session also invites case studies of regional extreme wildfire events, their impacts, and experiences with prevention and mitigation strategies from around the world. We welcome contributions from a wide range of disciplines, including global, regional, and landscape-scale modelling; statistical and process-based modelling; observational and field studies; and social science research on all time scales. Our goal is to foster knowledge exchange across disciplines and between scientists, decision-makers, and practitioners, to advance our collective ability to understand, model, and respond to the challenges posed by present and future extreme wildfires.
Carla Staver