Marco Rivera (Institute of Geodesy and Geoinformation, University of Bonn, Germany); Md Jamal Uddin Khan (LEGOS/UT/IRD, Toulouse, France); Jiaming Chen (Institute of Geodesy and Geoinformation, University of Bonn, Germany); Christopher Buchhaupt (CISESS/UMD, College Park, Maryland, United States); Luciana Fenoglio (Institute of Geodesy and Geoinformation, University of Bonn, Germany); Jürgen Kusche (Institute of Geodesy and Geoinformation, University of Bonn, Germany)

Although traditional satellite altimetry has significantly advanced our knowledge of global sea level variability, it faces major challenges in nearshore and estuarine zones due to land contamination and coarse spatial resolution. The Surface Water and Ocean Topography (SWOT) mission brings a unique opportunity to observe the coastal region and the land-ocean continuum with an unprecedented spatial resolution. However, its quality, consistency, and capabilities in this complex zone requires thorough evaluation. We are exploring these questions in the framework of two related projects – CONWEST-DYCO2, and COSWOT.

The project CONWEST-DYCO2 continues project CONWEST-DYCO in the Elbe estuary and Baltic Sea and extends the analysis to two other regions i.e. the waters around Indonesia and the Bay of Bengal. The central hypothesis is that hydrodynamic processes of the river-to-ocean continuum and of the mesoscale in coastal zone are today at best resolved and understood by combining SWOT and SAR-satellite altimetry observations. The main objective is to evaluate the contribution of SWOT to analyze coastal processes. Our focus is on small scale processes in the transition zone from land to sea, that is in estuaries and in coastal zone.

In the COSWOT project funded by DFG, we evaluate the scientific usability of SWOT satellite altimetry in coastal zones, focusing on small-scale processes in land-sea transition areas and estuaries, as well as on the coastal water cycle and related extreme events. For this purpose, various data products of SWOT are processed, compared and merged with measurements from other altimeter missions. In addition, the merged data products are to be compared with in-situ and with regional modeling results. Altogether the project covers three regions- the Baltic Sea, Indonesian waters, and the Bay of Bengal. In this poster we focus on the contrasting hydrodynamic settings of the micro-tidal Baltic Sea and the macro-tidal Bay of Bengal. Comparing SWOT’s performance across these two distinct regimes is expected to reveal its strengths and limitations, demonstrating its potential to monitor coastal and estuarine hydrodynamics more accurately in data-scarce areas under varying tidal conditions.

This study evaluates the capabilities of the SWOT observations during its science phase to estimate coastal sea level, river discharge, water level in rivers and longitudinal water surface gradient from upstream to downstream in the estuarine zones. The comparison approach is first developed and validated in the Baltic Sea, leveraging its dense network of in-situ observations, including tide gauges and discharge records. This validated framework is then adapted for the Bay of Bengal, where limited in-situ data and complex tidal dynamics require methodological adjustments and dedicated corrections. The Baltic Sea enables direct validation with abundant ground-truth data, while the Bay of Bengal requires model-based tidal corrections to reduce errors in the distributed products. Both high- and low-resolution SWOT products are systematically compared and merged with established along-track altimetry missions (Jason-3, Sentinel-3A/B, and Sentinel-6A) from Hydroweb-next, CMEMS, RADS and FFSAR database. Beyond estuarine conditions, the study also investigates the potential of Sea Surface Height (SSH) derived from low-resolution (LR_L3_v2.0.1) and high-resolution pixel-clouds (L2_HR_PIXC) SWOT products to reveal fine-scale nearshore processes in both regions.

In the Baltic Sea, we applied Optimal Interpolation (OI) to map more accurate and reliable sea level anomaly (SLA) fields, with multiple along-track satellite altimetry datasets, considering SWOT science phase (2023-08-11 to 2024-09-26). Preliminary results show that adding SWOT synthetic along-track data to traditional altimetry sources significantly improved their performance when validating against in situ tide gauge measurements in the central Baltic, such as at Visby and Landsort Norra. For instance, using RADS alone resulted in a correlation of 0.793, a standard deviation of 0.097 m, and a bias of -0.006 m at Visby; after adding SWOT, the correlation improved to 0.808, with a standard deviation of 0.094 m and a bias of -0.007 m. By further utilizing the combination of FFSAR, CMEMS, and SWOT, the correlation at Visby further improved to 0.812, with a standard deviation of 0.093 m and a bias of -0.011 m. However, OI still smooths out finer SLA variability and has some limitations when extrapolating into data-sparse areas. Currently, we are exploring strategies to address these shortcomings, which will enable us to apply this enhanced OI approach to more complex and data-poor coastal regimes, such as the Bay of Bengal.