A four-year eddy-permitting assimilation of altimetric and sea-surface temperature data in the South Atlantic Ocean

Sea-surface temperature (SST) and sea-surface height (SSH) data are assimilated with a reduced-order sequential filter every 10 days over four years (1993-1996) in a 1/3-degree resolution South Atlantic primitive equation model. At every assimilation step, the misfit between observations and their model counterparts is evaluated and projected onto the dominant 10 multivariate, full-depth local modes of variability diagnosed from a free model run (without assimilation). Satellite observations are used to perform a sequential update of all model variables according to their "natural" correlations with the surface variables. In this paper, we perform a validation of both the mean state and the eddy flow. Over the four years of assimilation, the forecast-data RMS misfit is decreased (i) by 55% on SSH; (ii) by 40% on SST; (iii) by about 20% on temperature in the upper 700 m with regard to independent, synoptic XBT data; (iv) as deep as 3500 m on the time-averaged temperature distribution compared to a recent climatology. These statistical estimates of the assimilation performance were complemented by a more original oceanographic investigation that revealed a significant improvement in the mean circulation (in particular in the Confluence region and in the deep ocean), the position of the main fronts, the averaged level and basin-scale distribution of SSH variance, the detailed evolution of individual mesoscale structures, the vertical distribution of the eddy kinetic energy, and the salinity field. These results would further be improved by the assimilation of in-situ data below sharp thermoclines that tend to decorrelate subsurface dynamics from the observed surface