{"title":"Prediction of an enigmatic tsunami in October 2023 at Kii Peninsula, Japan","authors":"Yuchen Wang , Kentaro Imai , Yutaka Hayashi , Hiroki Horikawa","doi":"10.1016/j.oceaneng.2024.119623","DOIUrl":null,"url":null,"abstract":"<div><div>On October 8, 2023, a tsunami was observed along the Pacific coast of Japan, but its cause was complicated. We applied tsunami data assimilation, a forecast method that does not consider the source, to predict coastal tsunami waveforms in the Kii Peninsula. We assimilated offshore observations recorded by pressure gauges (DONET) and reconstructed the wavefield before the tsunami arrived at the coast. The waveforms at Kumano, Kushimoto, and Shirahama were accurately forecasted at least 20 min before the tsunami arrival, indicating that data assimilation is applicable for tsunami early warning. Quantitative analysis showed that the score and accuracy index generally increased since 21:00 (UTC). Meanwhile, we investigated the tsunami decay process for tsunami warning cancellation by analysing the moving root mean squared (MRMS) amplitude. As data assimilation progressed, the prediction of tsunami later phase became increasingly accurate, and the errors between observed and predicted MRMS amplitudes decreased. Overall, the tsunami later phase was satisfactorily predicted at approximately 22:00 at coastal tide gauges. Hence, data assimilation approach contributes to a comprehensive tsunami early warning process, from the issuance to cancellation.</div></div>","PeriodicalId":19403,"journal":{"name":"Ocean Engineering","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocean Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0029801824029615","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
On October 8, 2023, a tsunami was observed along the Pacific coast of Japan, but its cause was complicated. We applied tsunami data assimilation, a forecast method that does not consider the source, to predict coastal tsunami waveforms in the Kii Peninsula. We assimilated offshore observations recorded by pressure gauges (DONET) and reconstructed the wavefield before the tsunami arrived at the coast. The waveforms at Kumano, Kushimoto, and Shirahama were accurately forecasted at least 20 min before the tsunami arrival, indicating that data assimilation is applicable for tsunami early warning. Quantitative analysis showed that the score and accuracy index generally increased since 21:00 (UTC). Meanwhile, we investigated the tsunami decay process for tsunami warning cancellation by analysing the moving root mean squared (MRMS) amplitude. As data assimilation progressed, the prediction of tsunami later phase became increasingly accurate, and the errors between observed and predicted MRMS amplitudes decreased. Overall, the tsunami later phase was satisfactorily predicted at approximately 22:00 at coastal tide gauges. Hence, data assimilation approach contributes to a comprehensive tsunami early warning process, from the issuance to cancellation.
期刊介绍:
Ocean Engineering provides a medium for the publication of original research and development work in the field of ocean engineering. Ocean Engineering seeks papers in the following topics.