{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:41:49Z","timestamp":1772822509171,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,12]],"date-time":"2018-04-12T00:00:00Z","timestamp":1523491200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The aim of this study is to assess the capacity of the Surface Water Ocean Topography (SWOT) satellite to resolve fine scale oceanic surface features in the western Mediterranean. Using as input the Sea Surface Height (SSH) fields from a high-resolution Ocean General Circulation Model (OGCM), the SWOT Simulator for Ocean Science generates SWOT-like outputs along a swath and the nadir following the orbit ground tracks. Given the characteristic temporal and spatial scales of fine scale features in the region, we examine temporal and spatial resolution of the SWOT outputs by comparing them with the original model data which are interpolated onto the SWOT grid. To further assess the satellite\u2019s performance, we derive the absolute geostrophic velocity and relative vorticity. We find that instrument noise and geophysical error mask the whole signal of the pseudo-SWOT derived dynamical variables. We therefore address the impact of removal of satellite noise from the pseudo-SWOT data using a Laplacian diffusion filter, and then focus on the spatial scales that are resolved within a swath after this filtering. To investigate sensitivity to different filtering parameters, we calculate spatial spectra and root mean square errors. Our numerical experiments show that noise patterns dominate the spectral content of the pseudo-SWOT fields at wavelengths below 60 km. Application of the Laplacian diffusion filter allows recovery of the spectral signature within a swath down to the 40\u201360 km wavelength range. Consequently, with the help of this filter, we are able to improve the observation of fine scale oceanic features in pseudo-SWOT data, and in the estimation of associated derived variables such as velocity and vorticity.<\/jats:p>","DOI":"10.3390\/rs10040599","type":"journal-article","created":{"date-parts":[[2018,4,12]],"date-time":"2018-04-12T12:19:27Z","timestamp":1523535567000},"page":"599","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["SWOT Spatial Scales in the Western Mediterranean Sea Derived from Pseudo-Observations and an Ad Hoc Filtering"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5878-4501","authenticated-orcid":false,"given":"Laura","family":"G\u00f3mez-Navarro","sequence":"first","affiliation":[{"name":"Institut Mediterrani d\u2019Estudis Avan\u00e7ats (IMEDEA) (CSIC-UIB), 07190 Esporles, Illes Balears, Spain"},{"name":"Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronan","family":"Fablet","sequence":"additional","affiliation":[{"name":"Institut Mines-T\u00e9l\u00e9com, Telecom-Bretagne, UMR 6285 labSTICC, 29238 Brest, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2283-6285","authenticated-orcid":false,"given":"Evan","family":"Mason","sequence":"additional","affiliation":[{"name":"Institut Mediterrani d\u2019Estudis Avan\u00e7ats (IMEDEA) (CSIC-UIB), 07190 Esporles, Illes Balears, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ananda","family":"Pascual","sequence":"additional","affiliation":[{"name":"Institut Mediterrani d\u2019Estudis Avan\u00e7ats (IMEDEA) (CSIC-UIB), 07190 Esporles, Illes Balears, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baptiste","family":"Mourre","sequence":"additional","affiliation":[{"name":"Balearic Islands Coastal Observing and Forecasting System (SOCIB), 07121 Palma de Mallorca, Illes Balears, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emmanuel","family":"Cosme","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6882-2938","authenticated-orcid":false,"given":"Julien","family":"Le Sommer","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,12]]},"reference":[{"key":"ref_1","unstructured":"Alsdorf, D., Mognard, N., and Lettenmaier, D. (2011, January 5\u20139). Remote Sensing of Surface Water and Recent Developments in the SWOT Mission. Proceedings of the Session H21J-06, AGU Fall Meeting, San Francisco, CA, USA."},{"key":"ref_2","unstructured":"Fu, L.L., and Morrow, R. (2016, January 23\u201327). A next generation altimeter for mapping the sea surface variability: Opportunities and challenges. 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