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OPEN ACCESS ATLAS OF GLOBAL SPECTRAL WAVE CONDITIONS BASED ON PARTITIONING

机译:基于分区的全球光谱波条件的开放访问图集

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An open access atlas of wave spectral characteristics at global scale is presented (GLOSWAC). This atlas is based on a recently developed technique for deriving spectral statistics, following the concept of partitioning. This development has been possible due to the parallel release of the wave spectra variable from the ERA-Interim archive of the European Centre for Medium-Range Weather Forecast (ECMWF). Although wave spectra are commonly available nowadays for wave analysis and forecasting, standard integral wave parameters are still in dominant use, both in practical and scientific applications. Although integrated parameters can give a good account of the wave spectral distribution in unimodal cases, they are subject to serious shortcomings when the sea state is bimodal or multi-modal. This issue can be easily tackled with the use of partitioning approaches. Spectral partitioning allows identifying the different wave components with different meteorological origin present in the spectrum. These components can be represented by their integrated parameters, which are much more meaningful than the averaged ones for the whole spectrum. Apart from the increased consistency, this method allows to summarize spectral information, offering the possibility to develop wave spectral statistics. Based on a statistical descriptor, the Probability Distribution of Spectral Partitions (PDS), which is the main outcome from GLOSWAC, the local long-term wave systems can be identified and characterized. In addition, several other spectral parameters are computed and distributed in a web format. For illustration, an arbitrary reference location is used here to guide the interpretation and the use of the information derived.
机译:提出了全球范围内波谱特征的开放获取地图集(GLOSWAC)。该图集基于一种最新的技术,该技术遵循分区的概念来推导频谱统计信息。由于来自欧洲中距离天气预报中心(ECMWF)的ERA-临时文件的波谱变量的并行发布,因此这种发展之所以成为可能。尽管如今可以普遍使用波谱进行波分析和预测,但是无论是在实际应用还是在科学应用中,标准积分波参数仍占主导地位。尽管综合参数可以很好地说明单峰情况下的波谱分布,但是当海态为双峰或多峰时,它们会遭受严重的缺陷。使用分区方法可以轻松解决此问题。频谱划分允许识别频谱中存在的具有不同气象起源的不同波分量。这些分量可以用它们的综合参数来表示,这些参数比整个频谱的平均值要有意义得多。除了提高一致性外,此方法还可以汇总频谱信息,从而提供发展波谱统计数据的可能性。根据统计描述符(频谱分区的概率分布(PDS))(这是GLOSWAC的主要结果),可以识别和表征本地长期波浪系统。另外,还以网络格式计算并分配了其他几个光谱参数。为了说明起见,此处使用任意参考位置来指导所导出信息的解释和使用。

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