دورية أكاديمية
أعرض في EDS

Assessment and Integration of ERA5 Reanalysis and Fujita−Takahashi Models for Storm Surge Prediction in the East China Sea

التفاصيل البيبلوغرافية
العنوان: Assessment and Integration of ERA5 Reanalysis and Fujita−Takahashi Models for Storm Surge Prediction in the East China Sea
المؤلفون: Fanjun Chen, Zongyu Li, Kaixuan Ding, Zhilin Sun, Hanyu Zhou
المصدر: Applied Sciences, Vol 13, Iss 19, p 10658 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: storm surge, water level, simulation, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: With global climate warming, the frequency and intensity of typhoons are increasing, highlighting the significance of studying storm surges for coastal engineering disaster mitigation. In this study, we assessed the predictive capabilities of the new ERA5 reanalysis model and the traditional Fujita−Takahashi model for storm surges. We found that the traditional Fujita−Takahashi model, utilizing a prelandfall typhoon wind field, exhibited higher accuracy in storm surge predictions, while the ERA5 reanalysis model, employing a postlandfall wind field, demonstrated superior performance. By considering the strengths and weaknesses of both wind field models and analyzing the impact of Typhoon In-fa (2021) on the East China Sea, we determined the influence of this typhoon on storm surge heights along the eastern coastal region. These research findings provide valuable insights for the development of effective protection strategies, offering valuable references for coastal resilience planning.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/13/19/10658; https://doaj.org/toc/2076-3417
DOI: 10.3390/app131910658
URL الوصول: https://doaj.org/article/27da4187ee3d4a06a09a2f86aeec661a
رقم الأكسشن: edsdoj.27da4187ee3d4a06a09a2f86aeec661a
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app131910658