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.