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Automated classification of the atmospheric circulation patterns that drive regional wave climates

机译：自动分类驱动区域波浪气候的大气环流模式

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摘要

Wave climates are fundamental drivers of coastal vulnerability; changing trends in wave heights, periods and directions can severely impact a coastline. In a diverse storm environment, the changes in these parameters are difficult to detect and quantify. Since wave climates are linked to atmospheric circulation patterns, an automated and objective classification scheme was developed to explore links between synoptic-scale circulation patterns and wave climate variables, specifically wave heights. The algorithm uses a set of objective functions based on wave heights to guide the classification and find atmospheric classes with strong links to wave behaviour. Spatially distributed fuzzy numbers define the classes and are used to detect locally high- and lowpressure anomalies. Classes are derived through a process of simulated annealing. The optimized classification focuses on extreme wave events. The east coast of South Africa was used as a case study. The results show that three dominant patterns drive extreme wave events. The circulation patterns exhibit some seasonality with one pattern present throughout the year. Some 50-80% of the extreme wave events are explained by these three patterns. It is evident that strong lowpressure anomalies east of the country drive a wind towards the KwaZulu-Natal coastline which results in extreme wave conditions. We conclude that the methodology can be used to link circulation patterns to wave heights within a diverse storm environment. The circulation patterns agree with qualitative observations of wave climate drivers. There are applications to the assessment of coastal vulnerability and the management of coastlines worldwide.
机译：波浪气候是沿海脆弱性的根本驱动因素;波浪高度，周期和方向的变化趋势会严重影响海岸线。在多样化的风暴环境中，很难检测和量化这些参数的变化。由于海浪气候与大气环流模式相关，因此开发了一种自动客观的分类方案，以探索天气尺度环流模式与海浪气候变量（特别是海浪高度）之间的联系。该算法使用一组基于波高的目标函数来指导分类，并找到与波行为密切相关的大气类别。空间分布的模糊数定义了这些类别，并用于检测局部的高压和低压异常。类是通过模拟退火过程得出的。优化的分类集中在极端波浪事件上。以南非东海岸为例。结果表明，三个主导模式驱动了极端波浪事件。流通模式表现出一定的季节性，并且全年都存在一种模式。这三种模式解释了大约50-80％的极端波浪事件。显然，该国东部的强烈低压异常将风吹向夸祖鲁-纳塔尔省海岸线，这导致了极端波浪条件。我们得出结论，该方法可用于将环流模式与多种风暴环境中的波高相关联。环流模式与波浪气候驱动器的定性观测结果一致。在评估沿海地区的脆弱性和管理全球范围的海岸线方面都有应用。

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