典型文献
Assimilating satellite SST/SSH and in-situ T/S profiles with the Localized Weighted Ensemble Kalman Filter
文献摘要：
The Localized Weighted Ensemble Kalman Filter (LWEnKF) is a new nonlinear/non-Gaussian data assimilation(DA) method that can effectively alleviate the filter degradation problem faced by particle filtering, and it has great prospects for applications in geophysical models. In terms of operational applications, along-track sea surface height (AT-SSH), swath sea surface temperature (S-SST) and in-situ temperature and salinity (T/S) profiles are assimilated using the LWEnKF in the northern South China Sea (SCS). To adapt to the vertical S-coordinates of the Regional Ocean Modelling System (ROMS), a vertical localization radius function is designed for T/S profiles assimilation using the LWEnKF. The results show that the LWEnKF outperforms the local particle filter (LPF) due to the introduction of the Ensemble Kalman Filter (EnKF) as a proposal density; the RMSEs of SSH and SST from the LWEnKF are comparable to the EnKF, but the RMSEs of T/S profiles reduce significantly by approximately 55％ for the T profile and 35％ for the S profile (relative to the EnKF). As a result, the LWEnKF makes more reasonable predictions of the internal ocean temperature field. In addition, the three-dimensional structures of nonlinear mesoscale eddies are better characterized when using the LWEnKF.
文献关键词：
中图分类号：
作者姓名：
Meng Shen;Yan Chen;Pinqiang Wang;Weimin Zhang
作者机构：
College of Meteorology and Oceanology,National University of Defense Technology,Changsha 410073,China;Laboratory of Software Engineering for Complex Systems,Changsha 410073,China
文献出处：
引用格式：
[1]Meng Shen;Yan Chen;Pinqiang Wang;Weimin Zhang-.Assimilating satellite SST/SSH and in-situ T/S profiles with the Localized Weighted Ensemble Kalman Filter)[J].海洋学报（英文版）,2022(02):26-40
A类：
Assimilating,LWEnKF
B类：
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AB值：
0.53183
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