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Modelling the spatial extent and severity of extreme European windstorms

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  • Paul Sharkey
  • Jonathan A. Tawn
  • Simon J. Brown

Abstract

Windstorms are a primary natural hazard affecting Europe that are commonly linked to substantial property and infrastructural damage and are responsible for the largest spatially aggregated financial losses. Such extreme winds are typically generated by extratropical cyclone systems originating in the North Atlantic and passing over Europe. Previous statistical studies tend to model extreme winds at a given set of sites, corresponding to inference in an Eulerian framework. Such inference cannot incorporate knowledge of the life cycle and progression of extratropical cyclones across the region and is forced to make restrictive assumptions about the extremal dependence structure. We take an entirely different approach which overcomes these limitations by working in a Lagrangian framework. Specifically, we model the development of windstorms over time, preserving the physical characteristics linking the windstorm and the cyclone track, the path of local vorticity maxima, and make a key finding that the spatial extent of extratropical windstorms becomes more localized as its magnitude increases irrespective of the location of the storm track. Our model allows simulation of synthetic windstorm events to derive the joint distributional features over any set of sites giving physically consistent extrapolations to rarer events. From such simulations improved estimates of this hazard can be achieved in terms of both intensity and area affected.

Suggested Citation

  • Paul Sharkey & Jonathan A. Tawn & Simon J. Brown, 2020. "Modelling the spatial extent and severity of extreme European windstorms," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(2), pages 223-250, April.
  • Handle: RePEc:bla:jorssc:v:69:y:2020:i:2:p:223-250
    DOI: 10.1111/rssc.12391
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    Cited by:

    1. Raphaël de Fondeville & Anthony C. Davison, 2022. "Functional peaks‐over‐threshold analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1392-1422, September.

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