Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

JI Qiyan; ZHU Xueming; WANG Hui; LIU Guimei; GAO Shan; JI Xuanliang; XU Qing

doi:10.1007/s13131-015-0691-y

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Article Navigation > Acta Oceanologica Sinica > 2015 > 34(7): 54-64

JI Qiyan, ZHU Xueming, WANG Hui, LIU Guimei, GAO Shan, JI Xuanliang, XU Qing. Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica, 2015, 34(7): 54-64. doi: 10.1007/s13131-015-0691-y

Citation:

JI Qiyan, ZHU Xueming, WANG Hui, LIU Guimei, GAO Shan, JI Xuanliang, XU Qing. Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica, 2015, 34(7): 54-64. doi: 10.1007/s13131-015-0691-y

Citation:

JI Qiyan, ZHU Xueming, WANG Hui, LIU Guimei, GAO Shan, JI Xuanliang, XU Qing. Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica, 2015, 34(7): 54-64. doi: 10.1007/s13131-015-0691-y

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Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

doi: 10.1007/s13131-015-0691-y

1.
Key Laboratory of Ministry of Education for Coastal Disaster and Defence, Hohai University, Nanjing 210098, China
2.
Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China
3.
Key Laboratory of Ministry of Education for Coastal Disaster and Defence, Hohai University, Nanjing 210098, China;Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China

Received Date: 2015-01-23
Rev Recd Date: 2015-02-28

Abstract

Abstract

The prediction of sea surface temperature (SST) is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea (BYECS). One is based on a surface net heat flux correction, named as Qcorrection (QC), which nudges the flux correction to the model equation; the other is ensemble optimal interpolation (EnOI), which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis (OSTIA) system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error (RMSE) of the four experiments is 1.74, 1.16, 1.30 and 0.91℃, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively. Although both two methods are effective in assimilating the SST, the EnOI shows more advantages than the QC, and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.
- sea surface temperature,
- data assimilation,
- ensemble optimal interpolation,
- quick correction,
- Bohai Sea

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