Cross-country risk quantification of extreme wildfires in Mediterranean Europe (Online)

Date: Thursday 05 December 2024, 2.00PM - 3.00PM
Location: Online
Section Group Meeting
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We estimate the country-level risk of extreme wildfires defined by burned area (BA) for Mediterranean Europe and carry out a cross-country comparison. To this end, we avail of the European Forest Fire Information System (EFFIS) geospatial data from 2006 to 2019 to perform an extreme value analysis. More specifically, we apply a point process characterization of wildfire extremes using maximum likelihood estimation. By modelling covariates, we also evaluate potential trends and correlations with commonly known factors that drive or affect wildfire occurrence, such as the Fire Weather Index as a proxy for meteorological conditions, population density, land cover type, and seasonality. We find that the highest risk of extreme wildfires is in Portugal (PT), followed by Greece (GR), Spain (ES), and Italy (IT) with a 10-year BA return level of 50'338 ha, 33'242 ha, 25'165 ha, and 8'966 ha, respectively. Coupling our results with existing estimates of the monetary impact of large wildfires suggests expected losses of 162–439 million € (PT), 81–219 million € (ES), 41–290 million € (GR), and 18–78 million € (IT) for such 10-year return period events.
 
Dr Sarah Meier is a Postdoctoral Research Fellow at the University of Exeter, working on the Dragon Capital Research Programme in Biodiversity Economics. Her research centers on empirical climate and environmental economics, with an emphasis on extreme weather events, natural hazards, and biodiversity. She is particularly interested in the intersection of economics and climate science, as it enables her to uncover causal relationships between human behavior and the natural environment. Sarah completed her PhD at the University of Birmingham, where her thesis examined the economic impacts of wildfires by integrating geospatial climate data with economic datasets and employing econometric methods for causal analysis.
 
 
Contact Jia Shao for Finance Section 
 
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