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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 4 | Copyright
Nat. Hazards Earth Syst. Sci., 16, 901-913, 2016
https://doi.org/10.5194/nhess-16-901-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Apr 2016

Research article | 06 Apr 2016

The observed clustering of damaging extratropical cyclones in Europe

Stephen Cusack Stephen Cusack
  • Risk Management Solutions, Peninsular House, 30 Monument Street, London, EC3R 8NB, UK

Abstract. The clustering of severe European windstorms on annual timescales has substantial impacts on the (re-)insurance industry. Our knowledge of the risk is limited by large uncertainties in estimates of clustering from typical historical storm data sets covering the past few decades. Eight storm data sets are gathered for analysis in this study in order to reduce these uncertainties. Six of the data sets contain more than 100 years of severe storm information to reduce sampling errors, and observational errors are reduced by the diversity of information sources and analysis methods between storm data sets. All storm severity measures used in this study reflect damage, to suit (re-)insurance applications.

The shortest storm data set of 42 years provides indications of stronger clustering with severity, particularly for regions off the main storm track in central Europe and France. However, clustering estimates have very large sampling and observational errors, exemplified by large changes in estimates in central Europe upon removal of one stormy season, 1989/1990. The extended storm records place 1989/1990 into a much longer historical context to produce more robust estimates of clustering. All the extended storm data sets show increased clustering between more severe storms from return periods (RPs) of 0.5 years to the longest measured RPs of about 20 years. Further, they contain signs of stronger clustering off the main storm track, and weaker clustering for smaller-sized areas, though these signals are more uncertain as they are drawn from smaller data samples. These new ultra-long storm data sets provide new information on clustering to improve our management of this risk.

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Short summary
Clusters of severe windstorms threaten solvency in the (re-)insurance industry. Risk management is made highly uncertain due to so few clusters of severe storms in the past few decades. This research brought together a wide variety of historical storm damage information spanning the past few centuries in Europe to increase our knowledge of clustering of damaging storms. Clustering was found to increase with more severe storms, with weaker signs of more clustering off the main storm track.
Clusters of severe windstorms threaten solvency in the (re-)insurance industry. Risk management...
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