Articles | Volume 21, issue 6
https://doi.org/10.5194/os-21-3265-2025
https://doi.org/10.5194/os-21-3265-2025
Research article
 | 
02 Dec 2025
Research article |  | 02 Dec 2025

Enhancing coastal winds and surface ocean currents with deep learning for short-term wave forecasting

Manuel García-León, José María García-Valdecasas, Lotfi Aouf, Alice Dalphinet, Juan Asensio, Stefania Angela Ciliberti, Breogán Gómez, Víctor Aquino, Roland Aznar, and Marcos Sotillo

Related authors

Buoy measurements of strong waves in ice amplitude modulation: a signature of the impact of sea ice closedness on waves in ice attenuation
Jean Rabault, Trygve Halsne, Ana Carrasco, Anton Korosov, Joey Voermans, Patrik Bohlinger, Jens Boldingh Debernard, Malte Müller, Øyvind Breivik, Takehiko Nose, Gaute Hope, Fabrice Collard, Sylvain Herlédan, Tsubasa Kodaira, Nick Hughes, Qin Zhang, Kai Håkon Christensen, Alexander Babanin, Lars Willas Dreyer, Cyril Palerme, Lotfi Aouf, Konstantinos Christakos, Atle Jensen, Johannes Röhrs, Aleksey Marchenko, Graig Sutherland, Trygve Kvåle Løken, and Takuji Waseda
The Cryosphere, 19, 6229–6260, https://doi.org/10.5194/tc-19-6229-2025,https://doi.org/10.5194/tc-19-6229-2025, 2025
Short summary
Towards a Multi-Product Methodology for Calculating the Ocean Monitoring Indicator of SST Extremes in the IBI Region
Álvaro de Pascual Collar, Axel Alonso Valle, Alex Gallardo, Marta de Alfonso Alonso-Muñoyerro, Begoña Pérez Gómez, Stefania Ciliberti, and Marcos G. Sotillo
State Planet Discuss., https://doi.org/10.5194/sp-2025-16,https://doi.org/10.5194/sp-2025-16, 2025
Preprint under review for SP
Short summary
Investigating metamodeling capability to predict sea levels and marine flooding maps for early-warning systems: application on the Arcachon Lagoon (France)
Sophie Lecacheux, Jeremy Rohmer, Eva Membrado, Rodrigo Pedreros, Andrea Filippini, Déborah Idier, Servane Gueben-Vénière, Denis Paradis, Alice Dalphinet, and David Ayache
EGUsphere, https://doi.org/10.5194/egusphere-2024-3615,https://doi.org/10.5194/egusphere-2024-3615, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Crafting the Future: Machine learning for ocean forecasting
Patrick Heimbach, Fearghal O'Donncha, Timothy A. Smith, Jose Maria Garcia-Valdecasas, Alain Arnaud, and Liying Wan
State Planet, 5-opsr, 22, https://doi.org/10.5194/sp-5-opsr-22-2025,https://doi.org/10.5194/sp-5-opsr-22-2025, 2025
Short summary
An introduction to operational chains in ocean forecasting
Liying Wan, Marcos Garcia Sotillo, Mike Bell, Yann Drillet, Roland Aznar, and Stefania Ciliberti
State Planet, 5-opsr, 15, https://doi.org/10.5194/sp-5-opsr-15-2025,https://doi.org/10.5194/sp-5-opsr-15-2025, 2025
Short summary

Cited articles

Alday, M., Accensi, M., Ardhuin, F., and Dodet, G.: A global wave parameter database for geophysical applications. Part 3: improved forcing and spectral resolution, Ocean Modelling, 166, 101848, https://doi.org/10.1016/j.ocemod.2021.101848, 2021. 
Aouf, L. and Lefèvre, J. M.: On the impact of the assimilation of SARAL/AltiKa wave data in the operational wave model MFWAM, Marine Geodesy, 38, 381–395, 2015. 
Aouf, L., Lefèvre, J. M., and Hauser, D.: Assimilation of directional wave spectra in the wave model WAM: An impact study from synthetic observations in preparation for the SWIMSAT satellite mission, Journal of Atmospheric and Oceanic Technology, 23, 448–463, 2006. 
Ardhuin, F., Rogers, E., Babanin, A. V., Filipot, J. F., Magne, R., Roland, A., Van Der Westhuysen, A., Queffeulou, P., Lefevre, J. M., Aouf, L., and Collard, F.: Semiempirical dissipation source functions for ocean waves. Part I: Definition, calibration, and validation, Journal of Physical Oceanography, 40, 1917–1941, 2010. 
Ardhuin, F., Roland, A., Dumas, F., Bennis, A. C., Sentchev, A., Forget, P., Wolf, J., Girard, F., Osuna, P., and Benoit, M.: Numerical wave modeling in conditions with strong currents: Dissipation, refraction, and relative wind, Journal of Physical Oceanography, 42, 2101–2120, 2012. 
Download
Short summary
Accurate short-term wave forecasts are key for coastal activities. These forecasts rely on wind and currents as forcing, which in this work were both enhanced using neural networks (NNs) trained with satellite and radar data. Tested at three European sites, the NN-corrected winds were 35 % more accurate, and currents also improved. This led to improved IBI (Iberian–Biscay–Ireland) wave model predictions of wave height and period by 10 % and 17 %, respectively; even correcting under extreme events.
Share