Abstract

The wind stress drag coefficient plays an important role in storm surge models. This study reveals the influences of wind stress drag coefficients, which are given in form of formulas and inverted by the data assimilation method, on the storm surge levels in the Bohai Sea, Yellow Sea, and East China Sea during Typhoon 7008. In the process of data assimilation, the drag coefficient is based on the linear expression Cd = (a + b × U10) × 10−3 (generally speaking, a and b are empirical parameters determined by observed data). The results showed that the performance of the data assimilation method was far superior to those of drag coefficient formulas. Additionally, the simulated storm surge levels obviously changed in the neighborhood of typhoon eye. Furthermore, the effect of initial values of a and b in the Cd expression on the storm surge levels was also investigated when employing the data assimilation method. The results indicated that the simulation of storm surge level was the closest to the observation when a and b were simultaneously equal to zero, whereas the simulations had slight differences when the initial values of a and b were separately equal to the drag coefficients from the work of Smith, Wu, and Geernaert et al.. Therefore, we should choose appropriate initial values for a and b by using the data assimilation method. As a whole, the data assimilation method is much better than drag coefficient parameterization formulas in the simulation of storm surges.

Highlights

  • Storm surges are anomalous changes of sea water level induced by typhoons or tropical cyclones

  • We evaluated the effect of different initial values of a and b in the Cd expression on the storm surge model when employing the data assimilation method

  • The drag coefficients calculated by the five Cd formulas from Equations (11)–(15) and the data assimilation method are compared

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Summary

Introduction

Storm surges are anomalous changes of sea water level induced by typhoons or tropical cyclones. The southeast coastal regions in China often suffer from tropical cyclones of the Northwestern Pacific Ocean. Such substantial destructive typhoons are able to cause severe economic loss and threaten life safety in the low-lying areas along the coast, especially in areas where typhoons pass through [1,2,3,4,5,6]. (CCMPV2) combined with the parametric typhoon model had the best overall performance. Based on a coupled wave-circulation model, Hisao et al computed significant wave heights by introducing a combination of wind field datasets and super Typhoon Nepartak (2016), and they investigated the model’s performance under varying spatial and temporal resolutions [6]. In 2020, the economic loss caused by storm surge disasters accounted for

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