Development of a fine-resolution atmosphere-wave-ocean coupled forecasting model for the South China Sea and its adjacent seas

查看全文 作　　者：Junchuan [1,2]Sun;Zexun [1,2]Wei;Tengfei [1,2]Xu;Meng [1,2]Sun;Kun [1,2]Liu;Yongzeng [1,2]Yang;Li [3]Chen;Hong [3]Zhao;Xunqiang [1,2]Yin;Weizhong [4]Feng;Zhiyuan [5]Zhang;Yonggang [1,2]Wang

机构地区：[1]Key Laboratory of Marine Science and Numerical Modeling,First Institute of Oceanography,Ministry of Natural Resources;[2]Laboratory for Regional Oceanography and Numerical Modeling,Qingdao National Laboratory for Marine Science and Technology;[3]National Marine Environmental Forecasting Center,Ministry of Natural Resources;[4]South China Sea Marine Prediction Center,Ministry of Natural Resources;[5]Hydro-Meteorological Center of Navy,PLA

出　　处：《Acta Oceanologica Sinica》索引2019年第38卷第4期,共13页

基　　金：The National Key Research and Development Program of China under contract No.2017YFC1404201;the NSFCShandong Joint Fund for Marine Science Research Centers under contract No.U1606405;the SOA Program on Global Change and AirSea Interactions under contract Nos GASI-IPOVAI-03 and GASI-IPOVAI-02;the National Natural Science Foundation of China under contract Nos 41606040,41876029,41776016,41706035 and 41606036 摘　　要：A 72-h fine-resolution atmosphere-wave-ocean coupled forecasting system was developed for the South China Sea and its adjacent seas. The forecasting model domain covers from from 15°S to 45°N in latitude and 99°E to135°E in longitude including the Bohai Sea, the Yellow Sea, the East China Sea, the South China Sea and the Indonesian seas. To get precise initial conditions for the coupled forecasting model, the forecasting system conducts a 24-h hindcast simulation with data assimilation before forecasting. The Ensemble Adjustment Kalman Filter(EAKF) data assimilation method was adopted for the wave model MASNUM with assimilating Jason-2 significant wave height(SWH) data. The EAKF data assimilation method was also introduced to the ROMS model with assimilating sea surface temperature(SST), mean absolute dynamic topography(MADT) and Argo profiles data. To improve simulation of the structure of temperature and salinity, the vertical mixing scheme of the ocean model was improved by considering the surface wave induced vertical mixing and internal wave induced vertical mixing. The wave and current models were integrated from January 2014 to October 2015 driven by the ECMWF reanalysis 6 hourly mean dataset with data assimilation. Then the coupled atmosphere-wave-ocean forecasting system was carried out 14 months operational running since November 2015. The forecasting outputs include atmospheric forecast products, wave forecast products and ocean forecast products. A series of observation data are used to evaluate the coupled forecasting results, including the wind, SHW, ocean temperature and velocity.The forecasting results are in good agreement with observation data. The prediction practice for more than one year indicates that the coupled forecasting system performs stably and predict relatively accurate, which can support the shipping safety, the fisheries and the oil exploitation. 关键词：South China Sea COAWST MODEL MASNUM MODEL atmosphere-wave-ocean forecasting system data ASSIMILATION

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Development of a fine-resolution atmosphere-wave-ocean coupled forecasting model for the South China Sea and its adjacent seas

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