This study focuses on an accurate estimation of ocean circulation viaassimilation of satellite measurements of ocean dynamical topographyinto the global finite-element ocean model (FEOM). The dynamicaltopography data are derived from a complex analysis of multi-mission altimetry datacombined with a referenced earth geoid. The assimilation is split intotwo parts. First, the mean dynamic topography is adjusted. To this endan adiabatic pressure correction method is used which reduces model divergence from the real evolution.Second, a sequential assimilation technique is applied to improve therepresentation of thermodynamical processes by assimilating the timevarying dynamic topography. A method is used according to which thetemperature and salinity are updated following the verticalstructure of the first baroclinic mode. It is shown that themethod leads to a partially successful assimilation approach reducingthe rms difference between the model and data from 16 cm to 2 cm.This improvement of the mean state is accompanied bysignificant improvement of temporal variability in our analysis.However, it remains suboptimal, showing a tendency in the forecast phaseof returning toward a free run without data assimilation. Both themean difference and standard deviation of the difference between the forecastand observation data are reduced as the result of assimilation.
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