CoAuthors

Lee-Lueng Fu (JPL, United States); Bruce cornuelle (scripps, USA); patrice klein (ifremer, France)

From simulated ocean altimetry data, we implement the use of a non-linear dynamic propagator to perform three-dimensional (time and 2-d space) interpolation of mesoscale Sea Surface Height (SSH). Based on the same dynamic framework as presented in in Ubelmann et al., 2015, we develop here an inverse approach allowing to process any altimetry data unevenly sampled in time and space into high-level gridded altimetry maps. The inverse approach, similar to the standard objective mapping, contains some correction terms to the innovation vectors to account for non-linearities and the covariances through a Green’s function approach. From the Observing System Simulation Experiments carried out, simulating a typical 3-satellite constellation over the Gulf-Stream region, we show that this dynamic interpolation method can significantly reduce mapping errors compared to the standard linear objective analysis such as used by AVISO gridding. Beyond the prospects of improving the present and past mesoscale altimetry reconstructions, we will also discuss the potential benefits of the method for the future high-resolution measurements from SWOT.