The present invention belongs to the field of measured marine environment data assimilation, and specifically relates to an ensemble Kalman filter localization method. The present invention comprises: preprocessing measured atmospheric and marine environment data; for each piece of observation data, calculating a priori observation ensemble member of the observation data; calculating the average and variance of an observed priori ensemble; calculating an average observation increment of an ensemble; calculating a perturbed observation increment of each ensemble; projecting an average observation increment of the ensemble onto the ensemble average with a mode state; projecting the perturbed observation increment of each ensemble onto a corresponding ensemble perturbation with the mode state; and obtaining an ensemble member analysis field. According to the method provided by the present invention, the traditional localization method for ensemble Kalman filter is improved, different spatial scales represented by the ensemble average and ensemble perturbation are effectively considered, and the assimilation accuracy of ensemble Kalman filter is significantly improved.