Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method
In the storm surge model, the wind drag coefficient <i>C<sub>d</sub></i> is a critical parameter that has a great influence on the forecast of the storm surge level. In the present study, the effect of various wind drag coefficient parameterizations on the storm surge level i...
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| Format: | Article |
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MDPI AG
2022-12-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/14/1/38 |
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| author | Junli Xu Kai Ma Yuling Nie Chuanyu Liu Xin Bi Wenqi Shi Xianqing Lv |
| author_facet | Junli Xu Kai Ma Yuling Nie Chuanyu Liu Xin Bi Wenqi Shi Xianqing Lv |
| author_sort | Junli Xu |
| collection | DOAJ |
| description | In the storm surge model, the wind drag coefficient <i>C<sub>d</sub></i> is a critical parameter that has a great influence on the forecast of the storm surge level. In the present study, the effect of various wind drag coefficient parameterizations on the storm surge level is investigated in the Bohai Sea, Yellow Sea and East China Sea for Typhoons 7203 and 7303. Firstly, the impacts of initial values of <i>a</i> and <i>b</i> in the linear expression <i>C<sub>d</sub></i> = (<i>a</i> + <i>b</i> × <i>U</i><sub>10</sub>) × 10<sup>−3</sup> on the pure storm surge model are evaluated based on the data assimilation method. Results indicate that when <i>a</i> and <i>b</i> (i.e., the wind drag coefficients given by Smith, Wu, Geernaert et al. and Mel et al.) are non-zeros, the performance of the model has little difference, and the result from Wu is slightly better. However, they are superior to the performance of the model adopting zero initial values. Then, we discuss the influences of diverse ways of calculating wind drag coefficients, which are inverted by data assimilation method (including both linear and constant <i>C<sub>d</sub></i>) and given in the form of linear formulas, on simulating pure storm surge level. They show that the data assimilation-based coefficients greatly exceed those of the ordinary coefficient formulas. Moreover, the wind drag coefficient in the linear form is a little better than that in constant form when the data assimilation method is used. Finally, the assessment of the impact of astronomical tides on the storm surge level is conducted, and the simulation demonstrates that the storm surge model, which has the combination of four constituents (<i>M</i><sub>2</sub>, <i>S</i><sub>2</sub>, <i>K</i><sub>1</sub>, <i>O</i><sub>1</sub>) and wind drag coefficient inverted by the data assimilation method with the linear <i>C<sub>d</sub></i>, exhibits the best performance. |
| first_indexed | 2024-03-09T13:39:38Z |
| format | Article |
| id | doaj.art-b005c5ec8bc44c8e933208076bf01659 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-09T13:39:38Z |
| publishDate | 2022-12-01 |
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| series | Atmosphere |
| spelling | doaj.art-b005c5ec8bc44c8e933208076bf016592023-11-30T21:08:30ZengMDPI AGAtmosphere2073-44332022-12-011413810.3390/atmos14010038Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation MethodJunli Xu0Kai Ma1Yuling Nie2Chuanyu Liu3Xin Bi4Wenqi Shi5Xianqing Lv6School of Mathematics and Physics, Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao Innovation Center of Artificial Intelligence Ocean Technology, Qingdao University of Science and Technology, Qingdao 266100, ChinaSchool of Mathematics and Physics, Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao Innovation Center of Artificial Intelligence Ocean Technology, Qingdao University of Science and Technology, Qingdao 266100, ChinaSchool of Mathematics and Physics, Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao Innovation Center of Artificial Intelligence Ocean Technology, Qingdao University of Science and Technology, Qingdao 266100, ChinaCAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences (IOCAS), Qingdao 266071, ChinaSchool of Mathematics and Physics, Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao Innovation Center of Artificial Intelligence Ocean Technology, Qingdao University of Science and Technology, Qingdao 266100, ChinaNational Marine Environment Monitoring Center, Ministry of Ecology and Environment, Dalian 116023, ChinaPhysical Oceanography Laboratory, Qingdao Collaborative Innovation Center of Marine Science and Technology (CIMST), Ocean University of China, Qingdao 266100, ChinaIn the storm surge model, the wind drag coefficient <i>C<sub>d</sub></i> is a critical parameter that has a great influence on the forecast of the storm surge level. In the present study, the effect of various wind drag coefficient parameterizations on the storm surge level is investigated in the Bohai Sea, Yellow Sea and East China Sea for Typhoons 7203 and 7303. Firstly, the impacts of initial values of <i>a</i> and <i>b</i> in the linear expression <i>C<sub>d</sub></i> = (<i>a</i> + <i>b</i> × <i>U</i><sub>10</sub>) × 10<sup>−3</sup> on the pure storm surge model are evaluated based on the data assimilation method. Results indicate that when <i>a</i> and <i>b</i> (i.e., the wind drag coefficients given by Smith, Wu, Geernaert et al. and Mel et al.) are non-zeros, the performance of the model has little difference, and the result from Wu is slightly better. However, they are superior to the performance of the model adopting zero initial values. Then, we discuss the influences of diverse ways of calculating wind drag coefficients, which are inverted by data assimilation method (including both linear and constant <i>C<sub>d</sub></i>) and given in the form of linear formulas, on simulating pure storm surge level. They show that the data assimilation-based coefficients greatly exceed those of the ordinary coefficient formulas. Moreover, the wind drag coefficient in the linear form is a little better than that in constant form when the data assimilation method is used. Finally, the assessment of the impact of astronomical tides on the storm surge level is conducted, and the simulation demonstrates that the storm surge model, which has the combination of four constituents (<i>M</i><sub>2</sub>, <i>S</i><sub>2</sub>, <i>K</i><sub>1</sub>, <i>O</i><sub>1</sub>) and wind drag coefficient inverted by the data assimilation method with the linear <i>C<sub>d</sub></i>, exhibits the best performance.https://www.mdpi.com/2073-4433/14/1/38storm surgeastronomical tidewind drag coefficientdata assimilation methodlinear expression |
| spellingShingle | Junli Xu Kai Ma Yuling Nie Chuanyu Liu Xin Bi Wenqi Shi Xianqing Lv Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method Atmosphere storm surge astronomical tide wind drag coefficient data assimilation method linear expression |
| title | Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method |
| title_full | Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method |
| title_fullStr | Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method |
| title_full_unstemmed | Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method |
| title_short | Numerical Study on Storm Surge Level Including Astronomical Tide Effect Using Data Assimilation Method |
| title_sort | numerical study on storm surge level including astronomical tide effect using data assimilation method |
| topic | storm surge astronomical tide wind drag coefficient data assimilation method linear expression |
| url | https://www.mdpi.com/2073-4433/14/1/38 |
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