从WAVEWATCH III®模式对东北太平洋异常浪的概率预测

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Leah Cicon, Johannes Gemmrich, Benoit Pouliot, Natacha Bernier
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引用次数: 0

摘要

流氓波是随机的、个别的海洋表面波,与背景海况相比,它们不成比例地大。它们给海员和近海建筑带来了相当大的风险,特别是在大海中遇到时。目前的异常浪预报是基于本杰明·费尔指数(BFI)量化的非线性过程。然而,越来越多的证据表明,BFI在真实海洋中的预测能力有限,而异常浪主要是由带宽控制的线性叠加产生的。最近的研究表明,带宽参数波峰波谷相关系数r与异常波概率的单变量相关性最高。通过对东北太平洋公海和沿海浮标的分析,我们证实了这一结果,并证明r对异常浪概率的预测能力最高。这项工作进一步表明,波谷相关性可以通过区域WAVEWATCHIII®波浪模型以中等精度预测。这一结果提出了一种新的基于r的经验异常浪风险评估概率预测方法。利用r与异常波概率之间的半对数拟合,生成异常波概率预报。提出了2021年10月21日至22日一次大风暴的异常浪概率预报样本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A probabilistic prediction of rogue waves from a WAVEWATCH III® model for the Northeast Pacific
Abstract Rogue waves are stochastic, individual ocean surface waves that are disproportionately large compared to the background sea state. They present considerable risk to mariners and offshore structures especially when encountered in large seas. Current rogue wave forecasts are based on nonlinear processes quantified by the Benjamin Feir Index (BFI). However, there is increasing evidence that the BFI has limited predictive power in the real ocean and that rogue waves are largely generated by bandwidth controlled linear superposition. Recent studies have shown that the bandwidth parameter crest-trough correlation, r shows the highest univariate correlation with rogue wave probability. We corroborate this result and demonstrate that r has the highest predictive power for rogue wave probability from the analysis of open ocean and coastal buoys in the Northeast Pacific. This work further demonstrates that crest-trough correlation can be forecast by a regional WAVEWATCHIII ® wave model with moderate accuracy. This result leads to the proposal of a novel empirical rogue wave risk assessment probability forecast based on r . Semi-logarithmic fits between r and rogue wave probability were applied to generate the rogue wave probability forecast. A sample rogue wave probability forecast is presented for a large storm October 21-22, 2021.
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来源期刊
Weather and Forecasting
Weather and Forecasting 地学-气象与大气科学
CiteScore
5.20
自引率
17.20%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.
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