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Abstract/Summary
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<jats:p>Abstract. For over 25 years, satellite altimetry has provided invaluable information about the ocean dynamics at many scales. In particular, gridded sea surface height (SSH) maps allow us to estimate the mesoscale geostrophic circulation in the ocean. However, conventional interpolation techniques rely on static optimal interpolation schemes, hence limiting the estimation of non-linear dynamics at scales not well sampled by altimetry (i.e., below 150–200 km at mid-latitudes). To overcome this limitation in the resolution of small-scale SSH structures (and thus small-scale geostrophic currents), a back-and-forth nudging algorithm combined with a quasi-geostrophic model, a technique called BFN-QG, has been successfully applied on simulated SSH data in observing system simulation experiments (OSSEs). The result is a significant reduction in interpolation error and an improvement in the space–time resolutions of the experimental gridded product compared to those of operational products. In this study, we propose that the BFN-QG be applied to real altimetric SSH data in a highly turbulent region spanning a part of the Agulhas Current. The performances are evaluated within observing system experiments (OSEs) that use independent data (such as independent SSH, sea surface temperature and drifter data) as ground truth. By comparing the mapping performances to the ones obtained with operational products, we show that the BFN-QG improves the mapping of short, energetic mesoscale structures and associated geostrophic currents both in space and time. In particular, the BFN-QG improves (i) the spatial effective resolution of the SSH maps by a factor of 20 %, (ii) the zonal and (especially) the meridional geostrophic currents, and (iii) the prediction of Lagrangian transport for lead times up to 10 d. Unlike the results obtained in the OSSEs, the OSEs reveal more contrasting performances in low-variability regions, which are discussed in the paper.
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Hinweis
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