Mapping altimetry in the forthcoming SWOT era by back-and-forth nudging the quasi-geostrophic dynamics

For 20 years, ocean surface topography maps, essential for understanding the ocean circulation, have been built by statistically interpolating sea surface height (SSH) data provided by along-track nadir altimeters.  The space-time distribution of observed data limits the resolution of the maps to approximately 150 km and 20 days in wavelength. The launch of the next-generation SWOT altimetry mission in 2021 opens the way to high resolution maps thanks to an unprecedented kilometric resolution over a swath wide of 120 km. However, new advanced mapping techniques that involve information on ocean dynamics should be explored to take advantage of the high spatial resolution of SWOT. In this study, a data assimilation algorithm, the back and forth nudging (BFN), is implemented with a one and half layer quasi geostrophic model (QG) to dynamically interpolate the altimetric data.  We test the QG/BFN system to dynamically map SSH with synthetic but realistically distributed altimetric observations in the framework of Observing System Simulation Experiments (OSSE). The study focuses on two regions of the North-Atlantic ocean, presenting different dynamics and characterized by different temporal samplings of SWOT.

A systematic comparison with the traditional objective mapping technique demonstrates that the QG/BFN brings a significant improvement of the quality of the maps using only conventional nadir altimeter data. This outperformance of the QG/BFN is further increased when SWOT is added in the altimetric dataset. Our method is particularly effective for reconstructing non-linear surface dynamics at small mesoscales (40-100 km) that are smoothed out by conventional methods based on optimal mapping.