Modelling extreme European windstorm return levels

Abstract: Windstorms are the most damaging natural hazard across western Europe. Risk modellers are limited by the observational data record to only ∼ 60 years of comprehensive reanalysis data that are dominated by considerable inter-annual variability. This makes estimating return periods of rare events difficult and sensitive to the choice of the historical period used. This poster presents a novel statistical method for estimating wind gusts across Europe based on observed windstorm footprints. A good description of extreme wind speeds is obtained by assuming that gust speed peaks over threshold are distributed exponentially, i.e. a generalised Pareto distribution having a zero shape parameter. The North Atlantic Oscillation (NAO) is particularly important for modulating lower return levels, with a less detectable influence on rarer extremes. Our method presents a framework for assessing high-return-period events across a range of hazards without the additional complexities of a full catastrophe model.

Biography: I am a Research Fellow at the University of Exeter and funded by the WTW Research Network. My research focusses on understanding historical variability and future trends of European windstorms using novel statistical techniques. I am also the RMetS Science Engagement Fellow for the Insurance Sector. This role involves driving engagement between academia and the insurance sector, providing resources, understanding collaboration, and increasing awareness of research being undertaken by both sectors.