EGU24-13319, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-13319
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Probabilistic assessment of extreme fire risk under the impact of climate change

Zhongwei Liu1,2, Jonathan Eden2, Bastien Dieppois2, Igor Drobyshev3,4,5, Stefaan Conradie6, Carolina Gallo2, Matthew Blackett2,7, and Robert Parker1
Zhongwei Liu et al.
  • 1University of Leicester, National Centre for Earth Observation, United Kingdom of Great Britain – England, Scotland, Wales (zl341@leicester.ac.uk)
  • 2Centre for Agroecology, Water and Resilience, Coventry University, Coventry, UK
  • 3Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, Sweden
  • 4Institut de recherche sur les forêts, Chaire de recherche du Canada en aménagement forestier durable, Université du Québec en Abitibi-Témiscamingue (UQAT), Canada
  • 5Forest Research Institute of the Karelian Research Centre of the Russian Academy of Petrozavodsk, Russia
  • 6Climate System Analysis Group, University of Cape Town, Rondebosch, Cape Town, South Africa
  • 7School of Energy, Construction and Environment, Coventry University, Coventry, UK

As major natural hazards, wildfires pose a significant risk to many parts of the world. The occurrence of extensive fires in both hemispheres 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. However, the scarcity of wildfire attribution studies, combined with limited observational records and the complexity of representing fires by different models, poses a challenge in establishing robust and unified conclusions to better inform future forest management strategies.

Here, a globally applicable framework is developed 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 (e.g. from CMIP/UKESM). Particular attention is given to the sensitivity of the eventual findings to the spatial scale of the event, the chosen event definition and the climate model(s) used in the analysis. As part of a global analysis, a series of maps are constructed detailing the change in likelihood of fire weather extremes, defined by both intensity and duration, throughout the world’s fire-prone regions as a result of rising global temperatures. Both observation- and model-based analyses reveal an increase in likelihood of at least twofold across many parts of the world, with considerable regional and inter-model variation. The value of the framework is demonstrated by combining results from a series of case studies of recent high-impact wildfires that differ by scale, duration and location. The conclusions drawn from this work provide a platform to guide future 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.

How to cite: Liu, Z., Eden, J., Dieppois, B., Drobyshev, I., Conradie, S., Gallo, C., Blackett, M., and Parker, R.: Probabilistic assessment of extreme fire risk under the impact of climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13319, https://doi.org/10.5194/egusphere-egu24-13319, 2024.