Wide-swath altimetric satellite data assimilation with structured-error detrending

2 For decades now, satellite altimetric observations have been successfully integrated in numerical 3 oceanographic models using data assimilation (DA). So far, sea surface height (SSH) data 4 were provided by one-dimensional nadir altimeters. The next generation Surface Water and 5 Ocean Topography (SWOT) satellite altimeter will provide two-dimensional wide-swath altimetric 6 information with an unprecedented high resolution. This new type of SSH data is expected to 7 strongly improve altimetric assimilation. However, the SWOT data is also expected to be affected 8 by spatially structured errors and, hence, can not be assimilated as easily as nadir altimeters. The 9 present paper proposes to embed a state-of-the-art error detrending method for the SWOT data 10 into an ensemble-based DA scheme. This new detrended-DA scheme is implemented and tested 11 in a simple SSH reconstruction problem using artificial SWOT data and a quasi-geostrophic 12 model. The results show that, in an energetic large scale region and when the region is intensely 13 observed, the detrended-DA – in comparison to the classical DA – reduces the root-mean-square14 error (RMSE) of the reconstruction in SSH, relative vorticity and surface currents and slightly 15 improves the relative error spectrum and spectral coherence of the SSH signal at mesoscale 16 (100-200km). In a less energetic region, the detrended-DA reduces on average by more than 17 50% the RMSE in SSH therefore allowing a significantly more accurate reconstruction of SSH at 18 mesoscale in terms of relative error spectrum, spectral coherence and power spectral density. 19