Blending data from SWOT KaRIn science phase and 30 years of nadir altimetry to improve Mean Sea Surface models.

Mean Sea Surface (MSS) is a crucial information to get an accurate Sea Level Anomaly (SLA). This study introduces an advanced MSS model, developed by combining data from the Surface Water and Ocean Topography (SWOT) mission Ka-band Radar Interferometer (KaRIn) with over 30 years of nadir altimetry observations. SWOT KaRIn provides two groundbreaking advantages: unmatched precision for resolving small-scale ocean features and two-dimensional measurements that offer a complete view of ocean surface structures, in contrast to the one-dimensional cross-sectional data from nadir altimeters. By integrating SWOT’s exceptional spatial resolution with the long-term temporal stability of nadir altimetry, this new MSS model delivers a more accurate and comprehensive representation of sea surface topography. The model is constructed using a gridded draft MSS based on state-of-the-art MSS to represent large-scale features, which is then refined using two wavelength-specific approaches. The first leverages the mean profile from SWOT KaRIn’s science phase. The second incorporates the static component of the Sea Surface Height (SSH) signal derived through the Multiscale Inversion of Ocean Surface Topography (MIOST) method. Compared to state-of-the-art MSS model, this new MSS reveals previously undetected seamounts, reduces geodetic residuals in SWOT KaRIn Sea Level Anomaly (SLA) signals, and improves overall accuracy.