We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have adopted the local ensemble transformation Kalman filter algorithm based on 20 members' ensemble simulations of the parallelized Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36A degrees. By assimilating satellite sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability.