南海北部集合卡曼滤波同化SST试验

doi:10.11978/j.issn.1009-5470.2010.05.010

Abstract

Abstract:

An ensemble Kalman filter (EnKF) scheme is applied to assimilate sea surface temperature (SST) in the northern South China Sea (SCS) using the Princeton Ocean Model (POM). The assimilation model has a horizontal resolution of 5km and a vertical resolution of 20 layers. Lateral boundary conditions are provided by a larger domain SCS model. A square root filter is applied to avoid perturbations induced by observations. Localization is used in the assimilation system to remove pseudo correlations and to add rank of ensemble. The Global High-Resolution Sea Surface Temperature (GHRSST) in June and July 2008 is assimilated in this study. To validate the assimilation results, hydrographic data from the Northern South China Sea Coastal Oceanographic Process Experiment (SCOPE) cruises are used. The results show that the assimilated SST can effectively improve the temperature distribution not only at surface but also in the subsurface. After the SST assimilation, upwelling in this region is strengthened and mixed layer is deepened. At the same time, because the EnKF is a multivariable assimilation scheme, salinity and currents are also corrected by assimilating SST.

Key words: ensemble Kalman filter, assimilation, northern South China Sea, SST

SHU Ye-qiang,SUI Dan-dan,WANG Wei-wen,XIAO Xian-jun. SST assimilation experiment in the northern South China Sea using ensemble Kalman filter[J].Journal of Tropical Oceanography, 2010, 29(5): 10-16.

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SST assimilation experiment in the northern South China Sea using ensemble Kalman filter

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