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Research on data assimilation and features analysis of storm surge in the Shanghai offshore areas
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Jun Ding1, Xin Lü2, *, Yaqian Yao1, Xin Meng1, Xuemin Jiang1, Xuyun Wu1, Jianzhong Ge3
Haiyang Xuebao | 2021, 43(3) : 135 - 145
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Haiyang Xuebao | 2021, 43(3): 135-145
• Article •
Research on data assimilation and features analysis of storm surge in the Shanghai offshore areas
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Jun Ding1, Xin Lü2, *, Yaqian Yao1, Xin Meng1, Xuemin Jiang1, Xuyun Wu1, Jianzhong Ge3
Affiliations
  • 1Shanghai Ocean Monitoring and Forecasting Center, Shanghai 200062, China
  • 2East China Sea Forecasting Center, State Oceanic Administration, Shanghai 200136, China
  • 3State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
Published: 2021-03-25 doi: 10.12284/hyxb2021049
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Storm surge is a complex ocean phenomenon which is sensitive to many factors and has attracted much attention. In this paper, based on covariance localization method of ensemble Kalman filter(EnKF), the storm surge data of different sources, different error and different spatial and temporal resolution calculated by tide gauge stations and FVCOM model were assimilated and fused for the first time. Taking the storm surge process of typhoon 201810 landing in Shanghai for example, the optimal solution of 72-hourly storm surge in the Shanghai offshore areas was obtained and verified, the setting range of set sample number and Schur radius were given. The results show that the root mean square error of storm surge calculated by the observed stations and the model is 0.20 m, while calculated by the observed stations and assimilation is 0.07 m, which is improved by 65%, the root mean square error calculated by independent observation and assimilation is 0.09 m, the ratio of set dispersion to root mean square error is 0.90, the assimilation effect is better and credible. The assimilated storm water increment field can clearly and accurately depict the characteristics of double peaks storm surge, typhone eye surge and frontal surge which can be better used for the research of storm surge, correction of numerical simulation and marine disaster prevention.

storm tide  /  storm surge  /  data assimilation  /  EnKF  /  marine disaster  /  Shanghai offshore areas
Jun Ding, Xin Lü, Yaqian Yao, Xin Meng, Xuemin Jiang, Xuyun Wu, Jianzhong Ge. Research on data assimilation and features analysis of storm surge in the Shanghai offshore areas[J]. Haiyang Xuebao, 2021 , 43 (3) : 135 -145 . DOI: 10.12284/hyxb2021049
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Article Info
doi: 10.12284/hyxb2021049
  • Receive Date：2020-01-07
  • Online Date：2026-02-26
  • Published：2021-03-25
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  • Received：2020-01-07
  • Revised：2020-05-01
Funding
Affiliations
    1Shanghai Ocean Monitoring and Forecasting Center, Shanghai 200062, China
    2East China Sea Forecasting Center, State Oceanic Administration, Shanghai 200136, China
    3State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
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