Multi-Source Satellite Altimetry for Monitoring Storm Wave Footprints in the English Channel’s Coastal Areas

Climate wave data, derived from significant wave height (SWH) altimetry, provide accurate information towards nearshore and coastal areas. Their use is crucial to enhance our capabilities of observing, understanding, and forecasting storm waves, even in complex coastal basins. In this study, SWOT nadir data were combined with nine existing altimeters for assessing waves and monitoring their evolution during storms in the English Channel, near UK–French coasts. Validation against wave buoys and numerical models shows high accuracy, with correlations around 95%, decreasing to 85% when buoy track offsets > 50 km, producing the largest errors. The multi-source approach enables depth-resolved monitoring, with SWH mapping revealing ~20–25% modulation in the Channel and ~36% dissipation near the Seine Bay during storms. Spectral analysis of multi-source altimeter-derived merged observations improve time-sampling, resolving high-frequency variability from monthly to daily scales and capturing ~75% of storms. Most storm wave features along altimetry tracks are resolved, with CFOSAT mapping nearshore areas and SWOT capturing coastal zones, both achieving ~80% variance. This temporal and spatial monitoring would be further enhanced with SWOT’s 2D wide swath. This finding provides a complementary, comprehensive understanding of coastal waves and offers valuable input for data assimilation, to improve storm wave estimates in coastal basins.

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Publication Details

Journal
Remote Sensing
Published
2025-09-22
DOI
https://doi.org/10.3390/rs17183262
Citations
1
Primary Topic
Tropical and Extratropical Cyclones Research
Type
article
Field-Weighted Citation Impact
1.30

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article

Multi-Source Satellite Altimetry for Monitoring Storm Wave Footprints in the English Channel’s Coastal Areas

Edward Salameh, Imen Turki, Ángel David Gutiérrez Barceló, Carlos Lopez Solano et al.
1 citations
Remote Sensing
Tropical and Extratropical Cyclones Research
1.30
article

Multi-Source Satellite Altimetry for Monitoring Storm Wave Footprints in the English Channel’s Coastal Areas

Edward Salameh, Imen Turki, Ángel David Gutiérrez Barceló, Carlos Lopez Solano, Lotfi Aouf, Frédéric Frappart, Md. Saiful Islam, Aurélien Carbonnière, Mateo Domingues
article en
1 citations

Abstract

Climate wave data, derived from significant wave height (SWH) altimetry, provide accurate information towards nearshore and coastal areas. Their use is crucial to enhance our capabilities of observing, understanding, and forecasting storm waves, even in complex coastal basins. In this study, SWOT nadir data were combined with nine existing altimeters for assessing waves and monitoring their evolution during storms in the English Channel, near UK–French coasts. Validation against wave buoys and numerical models shows high accuracy, with correlations around 95%, decreasing to 85% when buoy track offsets > 50 km, producing the largest errors. The multi-source approach enables depth-resolved monitoring, with SWH mapping revealing ~20–25% modulation in the Channel and ~36% dissipation near the Seine Bay during storms. Spectral analysis of multi-source altimeter-derived merged observations improve time-sampling, resolving high-frequency variability from monthly to daily scales and capturing ~75% of storms. Most storm wave features along altimetry tracks are resolved, with CFOSAT mapping nearshore areas and SWOT capturing coastal zones, both achieving ~80% variance. This temporal and spatial monitoring would be further enhanced with SWOT’s 2D wide swath. This finding provides a complementary, comprehensive understanding of coastal waves and offers valuable input for data assimilation, to improve storm wave estimates in coastal basins.

Remote SensingVol. 17(18)
Centre National de la Recherche Scientifique (FR), University of California, Santa Cruz (US), Centre National d'Études Spatiales (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Biologie du Fruit et Pathologie (FR), Santé et Agroécologie du Vignoble (FR), Normandie Université (FR), Météo-France (FR), Unité mixte de recherche Œnologie (FR), Université de Rouen Normandie (FR)
Agence Nationale de la Recherche, Centre National d’Etudes Spatiales
Openalex Percentile: Top 18%
Tropical and Extratropical Cyclones Research
1.30
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