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观测到的极端 rogue 波的产生机制与预测

Generation mechanism and prediction of an observed extreme rogue wave.

作者信息

Gemmrich Johannes, Cicon Leah

机构信息

Physics and Astronomy, University of Victoria, Victoria, BC, Canada.

School of Earth and Ocean Sciences, University of Victoria, Victoria, BC, Canada.

出版信息

Sci Rep. 2022 Feb 2;12(1):1718. doi: 10.1038/s41598-022-05671-4.

Abstract

Rogue waves are individual ocean surface waves with crest height [Formula: see text] or trough-to-crest height H that are large compared to the significant wave height [Formula: see text] of the underlying sea state: [Formula: see text] or [Formula: see text]. The physics of rogue wave generation and the potential of predicting the rogue wave risk are open questions. Only a few rogue waves in high sea states have been observed directly, but they can pose a danger to marine operations, onshore and offshore structures, and beachgoers. Here we report on a 17.6m high rogue wave in coastal waters with [Formula: see text] and [Formula: see text] which are likely the largest normalized heights ever recorded. Simulations of random superposition of Stokes waves in intermediate water depth show good agreement with the observation. Non-linear wave modulational instability, a well known cause for rogue waves in laboratory settings, did not contribute significantly to the rogue wave generation. A parameter obtained from a routine spectral wave forecast provides a practical risk prediction for rogue waves. These results confirm that probabilistic prediction of oceanic rogue waves based on random superposition of steep waves are possible and should replace predictions based on modulational instability.

摘要

异常波是单个海洋表面波,其波峰高度[公式:见正文]或波谷到波峰高度H与潜在海况的有效波高[公式:见正文]相比很大:[公式:见正文]或[公式:见正文]。异常波产生的物理机制以及预测异常波风险的可能性仍是未解决的问题。在公海状态下,只有少数异常波被直接观测到,但它们会对海上作业、近海和陆上结构以及海滩游客构成危险。在此,我们报告了沿海水域中一个17.6米高的异常波,其[公式:见正文]和[公式:见正文],这可能是有记录以来最大的归一化高度。在中等水深条件下对斯托克斯波随机叠加的模拟与观测结果吻合良好。非线性波调制不稳定性是实验室环境中异常波产生的一个众所周知的原因,但对该异常波的产生贡献不大。从常规谱波预报中获得的一个参数为异常波提供了实际的风险预测。这些结果证实,基于陡波随机叠加的海洋异常波概率预测是可行的,并且应该取代基于调制不稳定性的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2f6/8811055/911e1e0cc48d/41598_2022_5671_Fig1_HTML.jpg

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