Altimetry Data Assimilation Into a Numerical Model of Ocean Dynamics in the South Atlantic

Abstract—The data assimilation (DA) of satellite observations of the ocean level from the Archiving Validating and Interpolating Satellite Observations (AVISO) into the IWM model (G.I. Marchuk Institute of Computational Mathematics) of the Russian Academy of Sciences is considered. An original DA method is used that generalizes the well-known Kalman algorithm, called by the authors the Generalized Kalman filter (GKF). Various fields of model characteristics are constructed and analyzed in the South Atlantic region, in particular, level fields, ocean surface temperature (OST) and current velocity fields on the surface. Their spatiotemporal variability is studied before and after the assimilation of observational data. The spatiotemporal variability of the model and observed level and temperature of the ocean surface in the South Atlantic is also compared. The similarities and differences of these fields are analyzed. The comparisons with other models confirm the adequateness of the ocean field simulation with the help of the DA method.