EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Collective attribution and future risk assessment of recent high-impact wildfire events 

Zhongwei Liu1, Jonathan Eden1, Bastien Dieppois1, Igor Drobyshev2,3,4, Stefaan Conradie5, Carolina Gallo1, and Matthew Blackett1,6
Zhongwei Liu et al.
  • 1Coventry University, Centre for Agroecology, Water and Resilience, United Kingdom of Great Britain – England, Scotland, Wales (
  • 2Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, Sweden
  • 3Institut de recherche sur les forêts, Chaire de recherche du Canada en aménagement forestier durable, Université du Québec en Abitibi-Témiscamingue (UQAT), Canada
  • 4Forest Research Institute of the Karelian Research Centre of the Russian Academy of Petrozavodsk, Russia
  • 5Climate System Analysis Group, University of Cape Town, Rondebosch, Cape Town, South Africa
  • 6School of Energy, Construction and Environment, Coventry University, Coventry, UK

In recent years, the occurrence of a series devastating wildfire events around the world has raised considerable public concern about how climate change is altering meteorological conditions conducive to such events. The relative scarcity of wildfire attribution studies, coupled with the limited observational record, has added to the difficulty of developing reliable collective conclusions for future forest management strategies. Recent work has discussed the uncertainties and sensitivities associated with the choice of meteorological indicator to represent fire weather and the validation of climate model ensemble in the context of extreme event attribution, but the value of linking the attribution of recent record-breaking wildfire events with future risk assessment has not yet been fully explored.

Here, using an established probabilistic framework based on extreme value theory, we present the findings of attribution analysis applied to a series of recent high-impact wildfire. In each case, fire weather extremes, represented by annual maxima of the Canadian Fire Weather Index (FWI), are fitted to an extreme value distribution and scaled to the global mean surface temperature. Probability ratios are used to quantify the influence of rising global temperatures on the changing frequency of FWI extremes for past, present and future climates. We demonstrate the value of the application of a common methodological framework in combining results from different case studies as part of a collective attribution approach for multiple extreme across several world’s fire-prone regions. Further analysis of future risks will provide robust recommendations to reduce and address the hazards posed by wildfires and to improve post-disaster resilience.

How to cite: Liu, Z., Eden, J., Dieppois, B., Drobyshev, I., Conradie, S., Gallo, C., and Blackett, M.: Collective attribution and future risk assessment of recent high-impact wildfire events , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14441,, 2023.