Fine-Scale Sea Level Anomaly Reconstruction Constrained by SWOT-Derived Decorrelation Scales

Abstract. The Surface Water and Ocean Topography (SWOT) mission reveals fine-scale ocean variability at wavelengths below 100 km. However, most oceanographic applications of satellite altimetry rely on gridded sea level anomaly (SLA) products derived from along-track observations, whose representation of fine-scale variability is strongly influenced by covariance assumptions. Here, we use SWOT-derived spatial and temporal decorrelation scales as observational constraints on the prior covariance structure for reconstructing fine-scale SLA variability. Autocorrelation functions derived from SWOT observations are used to quantify the global spatial and temporal decorrelation characteristics of SLA, and the resulting decorrelation scales are incorporated into an optimal interpolation framework to improve fine-scale SLA reconstruction. In two subpolar regions, the SWOT-informed mapping resolves SLA variability down to wavelengths of approximately 55 km and improves the representation of geostrophic velocity, strain, relative vorticity, Okubo–Weiss parameter, and eddy kinetic energy. In the Irminger Sea, the reconstructed fields reveal an earlier wintertime enhancement of fine-scale eddy kinetic energy that is attenuated in existing gridded products. These results demonstrate that SWOT observations can enhance SLA mapping not only by providing additional measurements, but also by constraining the covariance structure underlying the reconstruction of SLA variability.