Unraveling storm wave populations in the UAE with multivariate and clustering analysis

利用多元和聚类分析揭示阿联酋风暴浪的分布情况

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Abstract

Wind waves are surface waves generated by the transfer of energy and momentum from the wind to water. Understanding wind fields is essential for determining wave characteristics, as the wave field develops over hours to days under continuous wind forcing. The Arabian Gulf, a region of global significance, is influenced by multiple winds systems due to its unique geography. The UAE, situated in the southern Arabian Gulf with a coastline spanning 1,318 km and territorial waters covering approximately 27,624 km(2), is particularly susceptible to wave storms originating from multiple directions. This study aimed to identify the wave storms effectively present in the UAE territorial waters by using advanced multivariate and clustering analysis techniques. The research leveraged 45 years (1979–2023) of hourly hindcast wind and wave data from the ECMWF ERA5 database, at 27 locations across the UAE territorial waters. Three primary storm wave populations, Shamal, Kaus, and Sohaili were identified, each associated with distinct wind-driven directional sectors. Agglomerative hierarchical clustering revealed six unique wave clusters among the 27 locations, each exhibiting unique wave patterns. The UAE extensive coastline along Abu Dhabi, Dubai, Sharjah, Ajman, Umm Al Quwain, and Ras Al Khaimah aligned with specific clusters, and experienced the same wave characteristics as that cluster. Valuable insights into understanding the varying wave patterns in the UAE were given and various practical applications were discussed.

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