NHESS Natural Hazards and Earth System Sciences NHESS Nat. Hazards Earth Syst. Sci. 1684-9981 Copernicus Publications Göttingen, Germany 10.5194/nhess-12-1769-2012 The spatial structure of European wind storms as characterized by bivariate extreme-value Copulas Bonazzi A. 1 Cusack S. 1 Mitas C. 1 Jewson S. 1 Risk Management Solutions, Peninsular House, 30 Monument Street, London, UK 29 05 2012 12 5 1769 1782 Copyright: © 2012 A. Bonazzi et al. 2012 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://nhess.copernicus.org/articles/12/1769/2012/nhess-12-1769-2012.html The full text article is available as a PDF file from https://nhess.copernicus.org/articles/12/1769/2012/nhess-12-1769-2012.pdf

The winds associated with extra-tropical cyclones are amongst the costliest natural perils in Europe. Re/insurance companies typically have insured exposure at multiple locations and hence the losses they incur from any individual storm crucially depend on that storm's spatial structure. Motivated by this, this study investigates the spatial structure of the most extreme windstorms in Europe. The data consists of a carefully constructed set of 135 of the most damaging storms in the period 1972–2010. Extreme value copulas are applied to this data to investigate the spatial dependencies of gusts. <br><br> The copula method is used to investigate three aspects of windstorms. First, spatial maps of expected hazard damage between large cities and their surrounding areas are presented. Second, we demonstrate a practical application of the copula method to benchmark catalogues of artificial storms for use in the re/insurance sector. Third, the copula-based method is used to investigate the sensitivity of spatially aggregated damage to climate variability. The copula method allows changes to be expressed in terms of storm frequency, local intensity, and storm spatial structure and gives a more detailed view of how climate variability may affect multi-location risk in Europe.

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