Observations of sea surface height (SSH) from SWOT have demonstrated remarkable potential for resolving mesoscale and submesoscale ocean features, which are crucial for assessing vertical velocities, a key variable for understanding the transport of heat, carbon, and nutrients between the ocean surface and interior. In the mesoscale-energetic region south of Tasmania, we evaluate the contributions of larger mesoscales (>100km), observable with traditional nadir-looking altimetry, and smaller scales (<100km) uniquely resolved by SWOT. Metrics such as surface geostrophic velocity, strain rate, relative vorticity, and the Okubo-Weiss parameter are derived from MIOST gridded maps and SWOT data, further partitioned into large (>100km) and small (<100km) scale components. While larger scales predominantly influence geostrophic velocity, smaller scales contribute significantly to current stretching and straining, with hotspots showing up to threefold stronger strain and tenfold stronger vorticity than larger scales. These fine scales reveal dynamic phenomena, such as the front jumping near the Macquarie Ridge, obscured in conventional low-resolution products. Initial validation of SWOT’s small-scale observations is performed using high-frequency (~8km) temperature sampling collected between Tasmania and Antarctica in December 2023 during a SURVOSTRAL campaign. SWOT surface structures align with subsurface horizontal temperature gradients. Vertical velocities (w) down to 1000 m, reconstructed using effective surface Quasi-Geostrophic (eSQG) theory, show that SWOT-derived w exhibits twice the RMS compared to nadir altimetry, underscoring SWOT’s capacity to resolve energetic meso- and submesoscale ocean dynamics. Further work is needed to fully harness SWOT’s high-resolution data in gridded products, as current smoothing limits the retention of valuable small-scale information.

Here, the use of an hybrid methodology, VarDyn, combining minimal physically-based constraints with a variational scheme, is demonstrated to improve mapping capabilities of sea surface height (SSH) and temperature (SST). Synthesizing multi-modal satellite observations, VarDyn improves the accuracy of SSH and SST maps compared to operational products, both in terms of RMSE and effective spatial resolution. Expected, most improvements occur in high energetic ocean regions. Still, the accuracy of SSH maps also slightly improves in low energetic regions, which is a clear improvement compared to other methods. VarDyn SSH fields and associated geostrophic velocities further reveal strong agreements with newly available high-resolution instantaneous SWOT estimates. Remarkably, the assimilation of SST especially benefits SSH reconstruction when only 2 altimeters are available. The VarDyn method thus opens robust means to refine climate SSH records, jointly assimilating SSH from 2 altimeters and SST from microwave sensors.

During the past 25 years, altimetric observations of the ocean surface from space have been mapped to provide two dimensional sea surface height (SSH) fields which are crucial for scientific research and operational applications. The SSH fields can be reconstructed from conventional altimetric data using temporal and spatial interpolation. For instance, the standard DUACS products are created with an optimal interpolation method which is effective for both low temporal and low spatial resolution. However, the upcoming next-generation SWOT mission will provide very high spatial resolution but with low temporal resolution. The present paper makes the case that this temporal-spatial discrepancy induces the need for new advanced mapping techniques involving information on the ocean dynamics. An algorithm is introduced, dubbed the BFN-QG, that uses a simple data assimilation method, the back-and-forth nudging, to interpolate altimetric data while respecting quasigeostrophic dynamics. The BFN-QG is tested in an observing system simulation experiments and compared to the DUACS products. The experiments consider as reference the high-resolution numerical model simulation NATL60 from which are produced realistic data: four conventional altimetric nadirs and SWOT data. In a combined nadirs and SWOT scenario, the BFN-QG substantially improves the mapping by reducing the root-mean-square errors and increasing the spectral effective resolution by 40km. Also, the BFN-QG method can be adapted to combine large-scale corrections from nadirs data and small-scale corrections from SWOT data so as to reduce the impact of SWOT correlated noises and still provide accurate SSH maps.