Assimilation of sea surface temperature in the Northwest Pacific Ocean and its marginal seas using the ensemble Kalman filter

Abstract

Satellite-borne sea surface temperature (SST) data were assimilated with the ensemble Kalman filter (EnKF) in a Northwest Pacific Ocean circulation model to examine the effect of data assimilation. The model domain included the northwestern part of the Pacific Ocean and its marginal seas, such as the Yellow Sea and East/Japan Sea. The performance of the data assimilation was evaluated by comparing the simulated ocean state with that observed. Spatially averaged root-mean-squared errors in the SST and sea surface height (SSH) decreased by 0.44 °C and 4 cm, respectively, by the assimilation. The results of the numerical experiments substantiated the effectiveness of the SST assimilation via the EnKF for all marginal seas, as well as the Kuroshio region. The benefit of the data assimilation depended on the characteristics of each marginal sea. The variation of the SST in the East/Japan Sea and the Kuroshio extension (KE) region were improved 34% and those in the Yellow Sea 12.5%. The variation of the SSH was improved approximately 36% in the KE region. This large improvement was achieved in the deep-water regions because assimilation of SST data corrected the separation point of the western boundary currents, such as the Kuroshio and the East Korea Warm Current, and the associated horizontal surface currents. The SST assimilation via the EnKF also improved the subsurface temperature profiles. The effectiveness of SST assimilation was seasonally dependent, with the improvement being relatively larger in winter than in summer, which was related to the seasonal variation of the vertical mixing and stratification in the ocean surface layer.