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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-4751</article-id>
<title-group>
<article-title>Composite Detection of Continental Shelf Fronts from Sea Surface Temperature and Altimetry: Assessing the Added Value of SWOT KaRIn</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Juhl</surname>
<given-names>Marie-Christin</given-names>
<ext-link>https://orcid.org/0009-0003-7642-7668</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Passaro</surname>
<given-names>Marcello</given-names>
<ext-link>https://orcid.org/0000-0002-3372-3948</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Dettermering</surname>
<given-names>Denise</given-names>
<ext-link>https://orcid.org/0000-0002-8940-4639</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hart-Davis</surname>
<given-names>Michael G.</given-names>
<ext-link>https://orcid.org/0000-0001-9342-0335</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Saraceno</surname>
<given-names>Martin</given-names>
<ext-link>https://orcid.org/0000-0002-5657-4420</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Deutsches Geodätisches Forschungsinstitut (DGFI-TUM), Technical University Munich, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Centro de Investigaciones del Mar y la Atmosfera (CIMA/CONICET-UBA)</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (DCAO, FCEN-UBA)</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI/CNRS-IRD-CONICET-UBA)</addr-line>
</aff>
<pub-date pub-type="epub">
<day>13</day>
<month>08</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>32</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Marie-Christin Juhl et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4751/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4751/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4751/egusphere-2026-4751.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4751/egusphere-2026-4751.pdf</self-uri>
<abstract>
<p>We present a composite front detection approach that uses horizontal gradients in Absolute Dynamic Topography (ADT) and Sea Surface Temperature (SST) to identify oceanic frontal structures on the Southwestern Continental Atlantic Shelf, a region characterized by strong mesoscale variability and multiple front types. SST fields are derived from the OSTIA satellite product, while four ADT datasets are compared: SWOT MIOST, CMEMS, OK-STv2, and GLORYS12v1. A joint front probability metric is introduced to quantify the co-occurrence of SST- and ADT-derived frontal signatures and to evaluate consistency and differences across products. The method is applied to assess the spatial and seasonal variability of major regional fronts, including the Shelf-Break Front, the San Mat&amp;iacute;as Front, and the Magellan Plume Front. The ADT datasets showed significant differences in their ability to co-detect continental shelf fronts. The Shelf-Break Front was consistently represented across all datasets, with maximum joint front probabilities occurring in austral summer (DJF) and exceeding 96 % between 35 and 45&amp;deg; S. In contrast, the seasonal and coastal San Mat&amp;iacute;as Front exhibited stronger dataset dependence, with the highest joint probabilities obtained using SWOT MIOST ADT (73.63 %), followed by CMEMS (54.95 %), OK-STv2 (41.86 %), and GLORYS12v1 (35.16 %). In the mid-shelf region (38&amp;ndash;41&amp;deg; S), elevated joint frontal probabilities indicate that ADT and SST products, particularly altimetry-based datasets, capture a persistent Mid-Shelf Front. The Magellan Plume Front showed strong joint signatures, most pronounced in SWOT MIOST (97.85 %), followed by CMEMS (80.65 %), OK-STv2 (72.83 %), and GLORYS12v1 (51.09 %), with a distinct coastal plume structure during austral winter (JJA). The approach could be further evaluated using ADT from SWOT KaRIn L3 data during SWOT&apos;s Cal/val phase, potentially enabling improved detectability through the sharper ADT gradients provided. Overall, the results show that combining SST- and ADT-based gradient detection enhances the characterization of frontal dynamics. The intercomparison further demonstrates that SWOT KaRIn&amp;ndash;enhanced gridded altimetry (SWOT MIOST) substantially improves the detection of coastal and seasonal fronts compared with conventional ADT products.</p>
</abstract>
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