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

机译:一种基于ECMWF?EPS构建欧洲暴风雨事件集的方法

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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.
机译:根据欧洲中距离天气预报中心(ECMWF)集合预报系统(EPS)的地面风向预报,估计当前气候条件下的欧洲暴风雨性质。尽管EPS旨在提供从观测到的天气状态开始的可能天气变化范围的预测信息,但我们在气候环境中使用了它的存档。它提供了对观测到的风暴事件的大量修改,并且包括实际上未发生的风暴。因此,有可能创建大量的暴风雨事件样本,这些样本完全来自物理上一致的模型,其整体分布表示覆盖期的可行替代暴风雨实现。本文表明,EPS中的大量可识别事件可用于减少针对冬季风暴的广泛研究领域中的不确定性。在本研究中,使用基于瞬时10μm风速的第98个百分位数的局部超出量的算法来识别和跟踪暴风雨,并与风暴的严重程度相关联。在消除了由于操作系统重大修改而导致的数据集不均匀性之后,计算了风暴严重性,风暴大小和风暴持续时间的分布。均质EPS风暴数据集的总体主要属性与ERA-Interim的风暴非常吻合数据集,使其适合于这些极端事件的气候调查。提出了EPS在气候背景下的证明效益。它清楚地表明最大风暴强度和风场大小随风暴持续时间呈线性增加。对于长期事件,无法从sparseERA-Interim样本中识别出这种关系,因为分析中的事件数不足以表示这些特征。

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