Regional Wave Analysis in the East China Sea Based on the SWAN Model
High-precision wave data serve as a foundation for investigating the wave characteristics of the East China Sea (ECS) and wave energy development. Based on the simulating waves nearshore (SWAN) model, this study uses the ERA5 (ECMWF Reanalysis v5) reanalysis wind field data and ETOPO1 bathymetric da...
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MDPI AG
2025-06-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/6/1196 |
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| author | Songnan Ma Fuwu Ji Qunhui Yang Zhinan Mi Wenhui Cao |
| author_facet | Songnan Ma Fuwu Ji Qunhui Yang Zhinan Mi Wenhui Cao |
| author_sort | Songnan Ma |
| collection | DOAJ |
| description | High-precision wave data serve as a foundation for investigating the wave characteristics of the East China Sea (ECS) and wave energy development. Based on the simulating waves nearshore (SWAN) model, this study uses the ERA5 (ECMWF Reanalysis v5) reanalysis wind field data and ETOPO1 bathymetric data to perform high-precision simulations at a resolution of 0.05° × 0.05° for the waves in the area of 25–35° N and 120–130° E in the ECS from 2009 to 2023. The simulation results indicate that the application of the whitecapping dissipation parameter Komen and the bottom friction parameter Collins yields an average RMSE of 0.374 m and 0.369 m when compared to satellite-measured data, demonstrating its superior suitability for wave simulation in shallow waters such as the ESC over the other whitecapping dissipation parameter, Westhuysen, and the other two bottom friction parameters, Jonswap and Madsen, in the SWAN model. The monthly average significant wave height (SWH) ranges from 0 to 3 m, exhibiting a trend that it is more important in autumn and winter than in spring and summer and gradually increases from the northwest to the southeast. Due to the influence of the Kuroshio current, topography, and events such as typhoons, areas with significant wave heights are found in the northwest of the Ryukyu Islands and north of the Taiwan Strait. The wave energy flux density in most areas of the ECS is >2 kW/m, particularly in the north of the Ryukyu Islands, where the annual average value remains above 8 kW/m. Because of the influence of climate events such as El Niño and extreme heatwaves, the wave energy flux density decreased significantly in some years (a 21% decrease in 2015). The coefficient of variation of wave energy in the East China Sea exhibits pronounced regional heterogeneity, which can be categorized into four distinct patterns: high mean wave energy with high variation coefficient, high mean wave energy with low variation coefficient, low mean wave energy with high variation coefficient, and low mean wave energy with low variation coefficient. This classification fundamentally reflects the intrinsic differences in dynamic environments across various maritime regions. These high-precision numerical simulation results provide methodological and theoretical support for exploring the spatiotemporal variation laws of waves in the ECS region, the development and utilization of wave resources, and marine engineering construction. |
| format | Article |
| id | doaj-art-c280ba18b7af4afe907ef4eea178ea3f |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-c280ba18b7af4afe907ef4eea178ea3f2025-08-20T03:27:17ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-06-01136119610.3390/jmse13061196Regional Wave Analysis in the East China Sea Based on the SWAN ModelSongnan Ma0Fuwu Ji1Qunhui Yang2Zhinan Mi3Wenhui Cao4State Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, ChinaState Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, ChinaState Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, ChinaSchool of Mechanical Engineering, Tongji University, Shanghai 200092, ChinaState Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, ChinaHigh-precision wave data serve as a foundation for investigating the wave characteristics of the East China Sea (ECS) and wave energy development. Based on the simulating waves nearshore (SWAN) model, this study uses the ERA5 (ECMWF Reanalysis v5) reanalysis wind field data and ETOPO1 bathymetric data to perform high-precision simulations at a resolution of 0.05° × 0.05° for the waves in the area of 25–35° N and 120–130° E in the ECS from 2009 to 2023. The simulation results indicate that the application of the whitecapping dissipation parameter Komen and the bottom friction parameter Collins yields an average RMSE of 0.374 m and 0.369 m when compared to satellite-measured data, demonstrating its superior suitability for wave simulation in shallow waters such as the ESC over the other whitecapping dissipation parameter, Westhuysen, and the other two bottom friction parameters, Jonswap and Madsen, in the SWAN model. The monthly average significant wave height (SWH) ranges from 0 to 3 m, exhibiting a trend that it is more important in autumn and winter than in spring and summer and gradually increases from the northwest to the southeast. Due to the influence of the Kuroshio current, topography, and events such as typhoons, areas with significant wave heights are found in the northwest of the Ryukyu Islands and north of the Taiwan Strait. The wave energy flux density in most areas of the ECS is >2 kW/m, particularly in the north of the Ryukyu Islands, where the annual average value remains above 8 kW/m. Because of the influence of climate events such as El Niño and extreme heatwaves, the wave energy flux density decreased significantly in some years (a 21% decrease in 2015). The coefficient of variation of wave energy in the East China Sea exhibits pronounced regional heterogeneity, which can be categorized into four distinct patterns: high mean wave energy with high variation coefficient, high mean wave energy with low variation coefficient, low mean wave energy with high variation coefficient, and low mean wave energy with low variation coefficient. This classification fundamentally reflects the intrinsic differences in dynamic environments across various maritime regions. These high-precision numerical simulation results provide methodological and theoretical support for exploring the spatiotemporal variation laws of waves in the ECS region, the development and utilization of wave resources, and marine engineering construction.https://www.mdpi.com/2077-1312/13/6/1196SWAN modelEast China Seawave parameterswave energywave spectrum analysis |
| spellingShingle | Songnan Ma Fuwu Ji Qunhui Yang Zhinan Mi Wenhui Cao Regional Wave Analysis in the East China Sea Based on the SWAN Model Journal of Marine Science and Engineering SWAN model East China Sea wave parameters wave energy wave spectrum analysis |
| title | Regional Wave Analysis in the East China Sea Based on the SWAN Model |
| title_full | Regional Wave Analysis in the East China Sea Based on the SWAN Model |
| title_fullStr | Regional Wave Analysis in the East China Sea Based on the SWAN Model |
| title_full_unstemmed | Regional Wave Analysis in the East China Sea Based on the SWAN Model |
| title_short | Regional Wave Analysis in the East China Sea Based on the SWAN Model |
| title_sort | regional wave analysis in the east china sea based on the swan model |
| topic | SWAN model East China Sea wave parameters wave energy wave spectrum analysis |
| url | https://www.mdpi.com/2077-1312/13/6/1196 |
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