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Abstract

We consider a method for assimilating the observation data based on the theory of Kalman filtration with the use of phase representation for the evolution of error covariation. The method is used together with the known hydrodynamical model of the ocean circulation-the Hamburg Ocean Primitive Equation (HOPE)developed at the Max Plank Institute for Meteorology (Hamburg, Germany). As observation information, we used the database of the TOGA-TAO experiment. For the experiment, we chose 1997, when one of the strongest El Nino events ever known was observed. The use of the assimilation method results in the essential correction of the model condition of the ocean. The corrected model fields are more reliable and closer to the observed ones than in the reference experiment without assimilation. It was shown that the data assimilation enhances the role of advection, whereas, in the reference experiment, diffusion, which is overestimated in the model, dominates. In addition, the assimilation method corrects both directly observed quantities such as temperature and the other calculated parameters of the model (velocity, heat fluxes, and so on). We concluded that the assimilation method could be used for developing an operative system for monitoring the ocean conditions