the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 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.
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Status: final response (author comments only)
- RC1: 'Comment on sp-2025-17', Anonymous Referee #1, 28 Nov 2025
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RC2: 'Comment on sp-2025-17', Anonymous Referee #2, 22 Apr 2026
This manuscript offers a crucial comparison between a traditional altimetry product, and an innovative one that includes SWOT in the west Mediterranean Sea. It provides interesting findings and, most importantly, it includes the results into a broader policy and environmental perspective.
Although I find the study very relevant and important for the community, I think the demonstrations of some important points were slightly overlooked. Also, I advise to read again carefully the entire manuscript because sentences are sometimes unclear and the points could better illustrated.
General:
- The introduction presents some very interesting points and generally the relevance of the study. I feel that many of the ideas are repeated multiple times in different paragraphs, which makes the whole message scattered and less powerful. I suggest keeping the same information, revising the structure of the introduction. Often sentences begin with “this variability” or “this impact”… and it is unclear what the words “this” or “its” are referring to
- In general, it should be better clarified how the authors separate the contribution of SWOT and of the interpolation methodology to the overall better performance of the MIOST-K product
- The study should quantify some basic differences between the three products, such as spatial and temporal resolution. This information is the minimum to start understanding the impact of SWOT in the dataset
Specific:
- 33 : "Mesoscale eddies are key drivers of this variability” unclear. What variability are you referring to?
- 42: “To evaluate this impact” unclear what impact you are referring to. Please rephrase
- 67 “high environmental interest areas” phrasing not clear
- 68-72: meaning is clear but the sentence is very convoluted. Please rephrase
- 81-85 and l.86-91 present some common concepts like the importance of the work for marine operations, spatial planning etc. I feel they could be compacted in one single paragraph so the information is less dispersed.
- 94: Is there a reason why the table is shown so early in the paper? It could be presented at the end of the mothods section, so the reader know what it is about
- 125: “and further details can be found in Mason et al. (2014)”. Further details about the contours? At least a basic explanation of the two contours, an why they are interested in them, should be provided
- 126: why does SLA provide more reliable eddy identification compared to ADT? Please add a brief justification
- 124-127 present a series of disconnected sentences. Please rephrace to add some logical transitions between the sentences
- 132: sentence somewhat confusing. Maybe some commas are missing
- 140: impact of the eddy characteristics on what?
- Fig 1: The explanation of this figure should be clearer.
- You insert panel A to show that the average circulation over the 20 is well represented by the shorter time averages. Panel A is used as kind of a reference of the mean circulation. Correct?
- Panel B and C represent an average over 17 months. You say that the differences between the two arise in the small scales and in the characteristics of the mesoscale structure. What characteristics are you referring to? Can you either point at something in the Figures, or quantify the differences in terms of energy at different scales, average size of the structures, speed… Just from the image it is not possible to understand what you mean.
- You say “already giving us a first insight that at the mesoscale the circulation will be impacted by the inclusion of the new SWOT observations.”. Two remarks on this:
- What you show is an average. How can you be sure that the impact of SWOT will be clearly visible in a 17-month average? If we don’t know what are the day-to-day differences is hard to judge
- How can you be sure that the differences are given by the fact that we include SWOT and not in the intrinsic differences of the two methods? (DUACS vs MIOST)
- 172: please quantify the “high temporal variability” in terms of mean, std of the two cases, and correlation between the two time series. Both for cyclonic and anticyclonic eddies
- Why is the difference in the eddy count larger for anticyclonic eddies?
- 187: please quantify in the text the most important EKE values, so the reader can easily compare the two products
- 189: “This may be due to enhanced signal capture”: is this a hypothesis or is it verified? What could be the other reasons why the EKE behaves this way?
- 190-194: the EKE analysis feels like a central point in the study. Especially because of the impact that it might have for climate applications. It would be beneficial to close this paragraph by adding how, in view of what the references you mention have found, your results could impact the understanding of the ocean’s carbon and heat sink in this region
- If the objective is to show the importance of the EKE for monitoring studies and environmental planning, having a mid to long term view is fundamental. What is the difference in the strongest EKE occurrence between the two products over the available time series? How could that difference impact the spatial planning for aquaculture, or the planning of safer marine routes? This work, between Figure 3 and the discussion, mentions that the physics and policies could be connected, but it does not provide a tangible example. Without an example we cannot really demonstrate why this innovative product is crucial for future studies.
- Fig4 explanation: How do you explain the variability between eddies with the same product? Why are the eddy dynamics so different? This is important to know because it shows the reliability of the product. If we expected the eddies to behave the same in the three cases, and retain the same number of particles, then there would be an issue with the product. The paragraph explaining this figure goes too fast
- 259-261: How is it possible that this study does not aim to compare the datasets? In the introduction, lines 61 to 63 state exactly the opposite. In general, this sentence is very vague and should be rephrased
Citation: https://doi.org/10.5194/sp-2025-17-RC2
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- 1
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: