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WAVE SPECTRA PARTITIONING AND IDENTIFICATION OF WIND SEA AND SWELL EVENTS

机译:波谱划分和风浪和涌浪识别

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Wave spectra often exhibit several peaks due to the coexistence of wind sea generated by local wind conditions and swells originating from distant weather systems. For an accurate description of sea states, those spectra can be partitioned and the partitions can be interpreted physically as representing independent wave systems. Furthermore, partitions can be associated in time to track the evolutions of wave systems originating from the same meteorological event (storm, depression, etc). This paper proposes a new method to identify temporal sequences of wave systems parameters, consistent with respect to the meteorological events that are the sources of the phenomena. This method, as many conventional partitioning ones, is based on the watershed algorithm which is however directly applied in our case to the whole time-history of wave spectra. Using appropriate criteria, the identified events are classified into swell or wind sea events. Field data from West Africa are used to illustrate the method and the results are compared with those of conventional software. Hindcast data from the Iroise Sea are also used to validate the proposed method and the results show a good identification of wave systems events with a good correlation between wind sea events and wind characteristics.
机译:由于局部风况和来自遥远的天气系统的涌浪共同产生的风海并存,因此波谱通常会出现几个峰值。为了准确描述海况,可以对那些光谱进行分区,并且可以将分区从物理上解释为代表独立的波浪系统。此外,可以及时关联分区,以跟踪源自同一气象事件(风暴,低压等)的波浪系统的演变。本文提出了一种新的方法来识别波浪系统参数的时间序列,这与作为现象源的气象事件是一致的。与许多传统的分区方法一样,该方法基于分水岭算法,但是在本例中直接应用于整个波谱的时间历史。使用适当的标准,将识别出的事件分类为海浪或风浪事件。西非的现场数据用于说明该方法,并将结果与​​常规软件进行比较。来自艾洛瓦海(Iroise Sea)的后播数据也被用于验证所提出的方法,结果表明,对风波系统事件的识别良好,并且在风海事件和风特征之间具有良好的相关性。

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