| 06 Oct 2025
New insights on mesoscale activity in the western Mediterranean Sea
Abstract. Mesoscale ocean variability plays a crucial role in regional circulation, heat transport, and the distribution of tracers such as nutrients, biological material, and pollutants. Mesoscale eddies are key drivers of this variability, and their observation (particularly of small-scale and coastal structures) has been limited by the resolution of conventional altimetry products. The Surface Water and Ocean Topography (SWOT) mission provides unprecedented high-resolution sea surface height data, offering new opportunities to refine mesoscale observations and improve our understanding of their impact on surface ocean dynamics. In this study, we assess the potential of a new product that incorporates SWOT wide-swath data and its improvements with respect to the current Copernicus Marine Environment Monitoring Service (CMEMS) satellite sea-level-derived velocity product. We analyze the eddy field in the western Mediterranean region, important for many different socio-economic activities like tourism, maritime transport, and fisheries and aquaculture. We identify differences not only in the number of eddies, but on their characteristics: size, intensity and associated kinetic energy. This is relevant for defining optimum marine traffic routes, but also for operational activities such as marine pollution management. To evaluate this impact, we analyse the retention capacity of Algerian Eddies, which in the past have been found relevant in the transport of marine debris between the North African coast and the Balearic Islands. Our findings evaluate how well SWOT-enhanced data affects the representation of mesoscale eddies and their velocity structures, showing important implications for ocean monitoring, climate studies, and marine ecosystem management.
In this study, the authors compare eddy detections from the classical DUACS altimetric product with detections obtained from a newly released product (MIOST-K) that incorporates SWOT KaRIn data. They demonstrate that assimilating SWOT data improves eddy detection and show that this enhancement has important implications for estimating eddy kinetic energy (EKE) and for assessing the particle export/retention that eddies may induce. In my opinion, the manuscript is of great interest and is generally well presented. The value of the study is twofold:
I have a remark that I would like the authors to address before the manuscript can be accepted for publication. This comment is intended to improve the quality of the paper and do not call into question the validity of the findings. I therefore recommend a major revision to allow the authors to address the following points thoroughly. Please note that, as English is not my native language, I have not corrected spelling or grammar.
Main remarks:
The goal of this study is to assess the improvement in eddy characterization obtained by including SWOT measurements in a gridded product. The authors make a convincing case overall, but in my opinion they overlook a crucial aspect of the comparison: Did SWOT actually sample the eddies they are analyzing?
As the authors know, SWOT provides 2D measurements of eddy structure, which is valuable for understanding their dynamics and estimating EKE. However, the manuscript never indicates whether the eddies under study were indeed sampled by SWOT.
For example, in Fig. 3C, the authors present the EKE field for a specific date. Where did SWOT pass on that day? According to “whereisswot.onrender.com” SWOT sampled the western part of the basin between approximately Valencia and Oran. Thus, for this particular case, SWOT did help resolve structures around ~38°N, 1°E. However, the increased detection of small structures on the eastern part of the basin can only result from SWOT passes on other days and is therefore, to some extent, an interpolation artifact.
I strongly encourage the authors to explicitly account for the actual sampling of eddies by SWOT. This could be done, for example, by overlaying SWOT ground tracks or including raw SWOT measurements (e.g., from the L3_LR_SSH product). The authors could also flag eddies that were directly sampled by SWOT and evaluate whether the improvements in detection/EKE/advection arise from genuine observations or from the interpolation procedure used in the gridding process.
Minor remarks: