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The properties of European windstorms under present climate conditions areestimated on the basis of surface wind forecasts from the European Centre forMedium-Range Weather Forecast (ECMWF) Ensemble Prediction System (EPS). Whilethe EPS is designed to provide forecast information of the range of possibleweather developments starting from the observed state of weather, we use itsarchive in a climatological context. It provides a large number ofmodifications of observed storm events and includes storms that did notoccur in reality. Thus it is possible to create a large sample of stormevents, which entirely originate from a physically consistent model, whoseensemble spread represents feasible alternative storm realizations of thecovered period. This paper shows that the huge amount of identifiable eventsin the EPS is applicable to reduce uncertainties in a wide range of fields ofresearch focusing on winter storms. Windstorms are identified and tracked inthis study over their lifetime using an algorithm based on the localexceedance of the 98th percentile of instantaneous 10 m wind speed, which isassociated with a storm severity measure. After removing inhomogeneities inthe data set arising from major modifications of the operational system, thedistributions of storm severity, storm size, and storm duration are computed.The overall principal properties of the homogenized EPS storm data set are ingood agreement with storms from the ERA-Interim data set, making it suitablefor climatological investigations of these extreme events. A demonstratedbenefit in the climatological context by the EPS is presented. It givesclear evidence of a linear increase of maximum storm intensity and wind fieldsize with storm duration. This relation is not recognizable from a sparseERA-Interim sample for long-lasting events, as the number of events in thereanalysis is not sufficient to represent these characteristics

An approach to build an event set of European windstorms based on ECMWF EPS