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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构建欧洲风暴事件集的方法

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The properties of European windstorms under present climate conditions are estimated on the basis of surface wind forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF) Ensemble Prediction System (EPS). While the EPS is designed to provide forecast information of the range of possible weather developments starting from the observed state of weather, we use its archive in a climatological context. It provides a large number of modifications of observed storm events and includes storms that did not occur in reality. Thus it is possible to create a large sample of storm events, which entirely originate from a physically consistent model, whose ensemble spread represents feasible alternative storm realizations of the covered period. This paper shows that the huge amount of identifiable events in the EPS is applicable to reduce uncertainties in a wide range of fields of research focusing on winter storms. Windstorms are identified and tracked in this study over their lifetime using an algorithm based on the local exceedance of the 98th percentile of instantaneous 10m wind speed, which is associated with a storm severity measure. After removing inhomogeneities in the data set arising from major modifications of the operational system, the distributions of storm severity, storm size, and storm duration are computed. The overall principal properties of the homogenized EPS storm data set are in good agreement with storms from the ERA-Interim data set, making it suitable for climatological investigations of these extreme events. A demonstrated benefit in the climatological context by the EPS is presented. It gives clear evidence of a linear increase of maximum storm intensity and wind field size with storm duration. This relation is not recognizable from a sparse ERA-Interim sample for long-lasting events, as the number of events in the reanalysis is not sufficient to represent these characteristics.
机译:在当前气候条件下,欧洲风暴的特性是根据欧洲中距离天气预报中心(ECMWF)集合预报系统(EPS)的地面风向预报来估算的。虽然EPS旨在提供从观测到的天气状况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其存档。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,有可能创建大量风暴事件样本,这些样本完全来自物理上一致的模型,该模型的整体分布表示覆盖期的可行替代风暴实现。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。在这项研究中,使用基于基于瞬时10m风速的98%局部超出范围的算法来识别和跟踪风暴的方法,该算法与风暴严重性度量相关联。在消除由于操作系统的重大修改而导致的数据集中的不均匀性之后,将计算风暴严重性,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数据集的风暴非常吻合,使其适合于这些极端事件的气候调查。介绍了EPS在气候方面的优势。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,无法从稀疏的ERA-Interim样本中识别出这种关系,因为重新分析中的事件数量不足以表示这些特征。

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