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 acc...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~C, 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.展开更多
The Antarctic marginal ice zone(MIZ)is the transition region between open water and consolidated pack ice,which is defined as an area with 15%-80%sea ice concentration.The MIZ represents the outer circle of Antarctic ...The Antarctic marginal ice zone(MIZ)is the transition region between open water and consolidated pack ice,which is defined as an area with 15%-80%sea ice concentration.The MIZ represents the outer circle of Antarctic sea ice and the biological activity circle of Antarctic organisms,which provides a direct indication of the extent of Antarctic sea ice.In this study,the joint total variation and nonnegative constrained least square algorithm are applied to retrieve the Antarctic MIZ extent based on passive microwave data sets from 1989 to 2019.The spatial and temporal variations of the Antarctic MIZ extent and five regions are analyzed.The results show that the Antarctic MIZ extent follows a strong monthly variation pattern,decreasing from November to February and increasing from March to October.The annual MIZ extent is largest in the Weddell Sea and smallest in the Western Pacific Ocean.The edge of the sea ice begins to form a closed ring in May,which eventually closes near the Antarctic Peninsula.The ring width variation is large in summer,but generally stabilizes between 350 and 370 km in winter.The average latitude of the Antarctic MIZ is relatively stable in summer,but changes substantially in winter with a difference of approximately 3°.In October,the lowest mean latitude of the MIZ can reach 64.35°S.The sea surface pressure,2-m temperature,and 10-m wind speed are negatively correlated with the MIZ extent variation,among which the second-order partial correlation coefficient of the sea surface pressure and MIZ extent is−0.8773 in the Western Pacific Ocean.展开更多
基金The Ocean Public Welfare Industry Research Special of China under contract No.201105009the Fundamental Research Funds for Central Universities of China under contract No.2013B20714+1 种基金the National Natural Science Foundation of China under contract Nos 41222038 and 41206023the National Basic Research Program of China(973 Program)under contract No.2011CB403606
文摘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~C, 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.
基金This study was supported by the National Natural Science Foundation of China(Grant no.41941010)the National Key Research and Development Program of China(Grant no.2018YFC1406102)the Funds for the Distinguished Young Scientists of Hubei Province(China)(Grant no.2019CFA057).
文摘The Antarctic marginal ice zone(MIZ)is the transition region between open water and consolidated pack ice,which is defined as an area with 15%-80%sea ice concentration.The MIZ represents the outer circle of Antarctic sea ice and the biological activity circle of Antarctic organisms,which provides a direct indication of the extent of Antarctic sea ice.In this study,the joint total variation and nonnegative constrained least square algorithm are applied to retrieve the Antarctic MIZ extent based on passive microwave data sets from 1989 to 2019.The spatial and temporal variations of the Antarctic MIZ extent and five regions are analyzed.The results show that the Antarctic MIZ extent follows a strong monthly variation pattern,decreasing from November to February and increasing from March to October.The annual MIZ extent is largest in the Weddell Sea and smallest in the Western Pacific Ocean.The edge of the sea ice begins to form a closed ring in May,which eventually closes near the Antarctic Peninsula.The ring width variation is large in summer,but generally stabilizes between 350 and 370 km in winter.The average latitude of the Antarctic MIZ is relatively stable in summer,but changes substantially in winter with a difference of approximately 3°.In October,the lowest mean latitude of the MIZ can reach 64.35°S.The sea surface pressure,2-m temperature,and 10-m wind speed are negatively correlated with the MIZ extent variation,among which the second-order partial correlation coefficient of the sea surface pressure and MIZ extent is−0.8773 in the Western Pacific Ocean.
