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首页> 外文期刊>Estuarine Coastal and Shelf Science >Data-driven analysis of joint coastal extremes near a large non-tidal estuary in North Europe
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Data-driven analysis of joint coastal extremes near a large non-tidal estuary in North Europe

机译：数据驱动的北欧大型非潮汐河口附近沿海联合极端事件分析

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The Vistula river estuary, located in the Gulf of Gdansk, is the largest river mouth in the entire Baltic Sea catchment area. Thus, the assessment of the likelihood of flood events for this region has become a pressing issue. Such analyses should include the worst scenario of joint coastal extremes due to simultaneous high levels of water in the river and sea. The simultaneously recorded daily water levels in the river and sea in the 1961—1989 period have made it possible to employ data-intensive signal processing techniques to address this problem by: (1) identification of the physical background of patterns embedded in both series with the Singular Spectrum Analysis (SSA) and (2) assessment of the degree of coupling between pairs of patterns from both series that are deemed most likely to trigger a joint extreme; this is done with the Canonical Correlation Analysis (CCA). For the Vistula estuary it was found that although the annual cycles encompass the largest portions of variances of both signals, they cannot be held responsible for joint extremes due to a considerable phase shift between them. However, both signals are often disturbed by random deviations from this basic behavior and these deviations emerged as separate patterns. Their magnitudes are to some extent correlated with the growth of water level in the sea and river and therefore they could be assumed to act as a pair of potential drivers of joint extremes. The degree of their coupling was found to be generally low with maximums in November, February and/or March, which indicates the low likelihood of a great flood event due to the combined effect of high sea and river water level. The results are also believed to be at least partly representative of other estuaries in North Europe, where annual cycles in seawater and water in (large) rivers are similar, e.g. Scheldt, Rijn, Elbe.
机译：位于格但斯克海湾的维斯杜拉河河口是整个波罗的海集水区最大的河口。因此，对该地区洪水事件可能性的评估已成为紧迫的问题。由于河流和海洋中同时存在大量水位，因此此类分析应包括最极端的沿海联合极端情况。同时记录的1961-1989年期间河流和海洋中的每日水位，使得可以使用数据密集型信号处理技术来解决此问题，方法是：（1）识别嵌入在两个序列中的图案的物理背景奇异频谱分析（SSA）和（2）评估两个系列中被认为最有可能触发联合极端的模式对之间的耦合程度；这是通过规范相关分析（CCA）完成的。对于维斯杜拉河口，人们发现，尽管年度周期包含了两个信号方差的最大部分，但由于它们之间存在相当大的相移，因此它们不能对共同的极端情况负责。但是，这两种信号通常都受到与该基本行为的随机偏差的干扰，并且这些偏差以单独的模式出现。它们的大小在一定程度上与海洋和河流中水位的增长相关，因此可以假定它们是共同极端的潜在驱动因素。发现它们的耦合程度通常较低，在11月，2月和/或3月达到最大值，这表明由于高海水和河流水位的共同作用，发生洪灾的可能性很小。还认为结果至少部分地代表了北欧的其他河口，那里的海水和（大）河流中的水的年循环是相似的，例如。 Scheldt，Rijn，易北河。

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