Generalized Kalman Filter and Ensemble Optimal Interpolation, their comparison and application to the Hybrid Coordinate Ocean modelстатья
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Аннотация:In this paper, we consider a recently developed data assimilation method, the Generalized Kal-man Filter (GKF), which is a generalization of the widely-used Ensemble Optimal Interpolation (EnOI) method. Both methods are applied for modeling the Atlantic Ocean circulation using the known Hybrid Coordinate Ocean Model. The along-track altimetry data taken from the Archiv-ing, Validating and Interpolating Satellite Oceanography Data (AVISO) were used for data as-similation and other data from independent archives of observations; particularly, the tempera-ture and salinity data from the Pilot Research Array in the Tropical Atlantic were used for inde-pendent comparison. Several numerical experiments were performed with their results discussed and analyzed. It is shown that values of the ocean state variables obtained in the calculations us-ing the GKF method are closer to the observations in terms of standard metrics in comparison with the calculations using the standard data assimilation method EnOI. Furthermore, the GKF method requires less computational effort compared to the EnOI method.