Assimilating Along-Track Altimetric Observations through Local Hydrostatic Adjustment in a Global Ocean Variational Assimilation System

Abstract

A global ocean three-dimensional variational data assimilation system was developed with the aim of assimilating along-track sea level anomaly observations, along with in situ observations from bathythermographs and conventional sea stations. All the available altimetric data within the period October 1992–January 2006 were used in this study. The sea level corrections were covariated with vertical profiles of temperature and salinity according to the bivariate definition of the background-error vertical covariances. Sea level anomaly observational error variance was carefully defined as a sum of instrumental, representativeness, observation operator, and mean dynamic topography error variances. The mean dynamic topography was computed from the model long-term mean sea surface height and adjusted through an optimal interpolation scheme to account for observation minus first-guess biases. Results show that the assimilation of sea level anomaly observations improves the model sea surface height skill scores as well as the subsurface temperature and salinity fields. Furthermore, the estimate of the tropical and subtropical surface circulation is clearly improved after assimilating altimetric data. Nonnegligible impacts of the mean dynamic topography used have also been found: compared to a gravimeter-based mean dynamic topography the use of the mean dynamic topography discussed in this paper improves both the consistency with sea level anomaly observations and the verification skill scores of temperature and salinity in the tropical regions. Furthermore, the use of a mean dynamic topography computed from the model long-term sea surface height mean without observation adjustments results in worsened verification skill scores and highlights the benefits of the current approach for deriving the mean dynamic topography.