The Surface Water and Ocean Topography (SWOT) mission has substantially enhanced the two-dimensional observing capability of sea surface height through wide-swath altimetry. However, transforming high-resolution and irregularly sampled observations into dynamically consistent gridded Level-4 products remains a major challenge for mesoscale ocean reconstruction. This study evaluates the capability and applicability of SWOT-constrained multi-altimeter assimilation for reconstructing mesoscale surface dynamics in Indian Ocean regions with contrasting dynamical backgrounds.
We implement a one-and-a-half-layer quasi-geostrophic Back-and-Forth Nudging (QG-BFN) framework that assimilates SWOT KaRIn observations together with multiple conventional nadir altimeter datasets to produce high-resolution sea surface height and geostrophic velocity fields. Experiments are conducted over representative Indian Ocean regions under different dynamical regimes and seasonal conditions, with SWOT Level-3 observations and the SWOT-informed MIOST Level-4 product used as references for dynamical diagnostics.
The results show that reconstruction performance is strongly regime dependent. In regions dominated by quasi-geostrophic balance, QG-BFN better preserves mesoscale SSH gradients and relative-vorticity-related structures than MIOST, producing more coherent energetic eddies and spectral energy distributions closer to SWOT along-track observations. This advantage is most evident in the western Australian–southeastern Indian Ocean mesoscale-active region, where extended experiments suggest stronger eddy kinetic energy, larger Rossby-number amplitudes, and more active offshore eddy propagation in July–August than in January–February. These findings indicate that QG-BFN provides an effective dynamically constrained framework for SWOT-based Level-4 reconstruction, although its performance remains scale selective and regime dependent.