Articles | Volume 21, issue 6
https://doi.org/10.5194/os-21-3265-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-21-3265-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Enhancing coastal winds and surface ocean currents with deep learning for short-term wave forecasting
Manuel García-León
CORRESPONDING AUTHOR
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
José María García-Valdecasas
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
Lotfi Aouf
Meteo-France, Departement Marine et Oceanographie, Toulouse, 31100, France
Alice Dalphinet
Meteo-France, Departement Marine et Oceanographie, Toulouse, 31100, France
Juan Asensio
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
Stefania Angela Ciliberti
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
Breogán Gómez
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
Víctor Aquino
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
Roland Aznar
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
Marcos Sotillo
Nologin Oceanic Weather Systems SLU, Santiago de Compostela, 15705, Spain
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The Cryosphere, 19, 6229–6260, https://doi.org/10.5194/tc-19-6229-2025, https://doi.org/10.5194/tc-19-6229-2025, 2025
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We observe strongly modulated waves-in-ice significant wave height using buoys deployed East of Svalbard. We show that these observations likely cannot be explained by wave-current interaction or tide-induced modulation alone. We also demonstrate a strong correlation between the waves height modulation, and the rate of sea ice convergence. Therefore, our data suggest that the rate of sea ice convergence and divergence may modulate wave in ice energy dissipation.
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
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This study improves the way extreme sea surface temperature events are monitored in the Iberia–Biscay–Ireland region. We tested new data sources and combined information from different models and satellites to provide more consistent results and to include estimates of uncertainty. The findings show that these methods make the indicator more reliable and useful for understanding marine heat events and for supporting decisions related to climate and ocean management.
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).
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This study comparer three data-driven methodologies to overcome the computational burden of numerical simulations for early warning purpose. They are all based on the statistical analysis of pre-calculated databases, to downscale total sea levels and predict marine flooding maps from offshore metocean forecasts. Conclusions highlight the relevance of metamodel-based approaches for fast prediction and the added value of precalculated databases during the prepardness phase.
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
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Operational ocean prediction relies on computationally expensive numerical models and complex workflows, known as data assimilation, in which models are fit to observations to produce optimal initial conditions for prediction. Machine learning has the potential to vastly accelerate ocean prediction, improve uncertainty quantification through massive surrogate model-based ensembles, and render simulations more accurate through better model calibration. We review the developments and challenges.
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
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Operating the ocean value chain requires the implementation of steps that must work systematically and automatically to generate ocean predictions and deliver this information. The paper illustrates the main challenges foreseen by operational chains in integrating complex numerical frameworks from the global to coastal scale and discusses existing tools that facilitate orchestration, including examples of existing systems and their capacity to provide high-quality and timely ocean forecasts.
Jennifer Veitch, Enrique Alvarez-Fanjul, Arthur Capet, Stefania Ciliberti, Mauro Cirano, Emanuela Clementi, Fraser Davidson, Ghada el Serafy, Guilherme Franz, Patrick Hogan, Sudheer Joseph, Svitlana Liubartseva, Yasumasa Miyazawa, Heather Regan, and Katerina Spanoudaki
State Planet, 5-opsr, 6, https://doi.org/10.5194/sp-5-opsr-6-2025, https://doi.org/10.5194/sp-5-opsr-6-2025, 2025
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Ocean forecast systems provide information about a future state of the ocean. This information is provided in the form of decision support tools, or downstream applications, that can be accessed by various stakeholders to support livelihoods, coastal resilience and the good governance of the marine environment. This paper provides an overview of the various downstream applications of ocean forecast systems that are utilized around the world.
Mauro Cirano, Enrique Alvarez-Fanjul, Arthur Capet, Stefania Ciliberti, Emanuela Clementi, Boris Dewitte, Matias Dinápoli, Ghada El Serafy, Patrick Hogan, Sudheer Joseph, Yasumasa Miyazawa, Ivonne Montes, Diego A. Narvaez, Heather Regan, Claudia G. Simionato, Gregory C. Smith, Joanna Staneva, Clemente A. S. Tanajura, Pramod Thupaki, Claudia Urbano-Latorre, Jennifer Veitch, and Jorge Zavala Hidalgo
State Planet, 5-opsr, 5, https://doi.org/10.5194/sp-5-opsr-5-2025, https://doi.org/10.5194/sp-5-opsr-5-2025, 2025
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Operational ocean forecasting systems (OOFSs) are crucial for human activities, environmental monitoring, and policymaking. An assessment across eight key regions highlights strengths and gaps, particularly in coastal and biogeochemical forecasting. AI offers improvements, but collaboration, knowledge sharing, and initiatives like the OceanPrediction Decade Collaborative Centre (DCC) are key to enhancing accuracy, accessibility, and global forecasting capabilities.
Marcos Garcia Sotillo, Marie Drevillon, and Fabrice Hernandez
State Planet, 5-opsr, 16, https://doi.org/10.5194/sp-5-opsr-16-2025, https://doi.org/10.5194/sp-5-opsr-16-2025, 2025
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Operational forecasting systems require best practices for assessing the quality of ocean products. The authors discuss the role of the observing network in performing validation of ocean models, identifying current gaps but also emphasizing the need of new metrics. An analysis on the level of maturity of validation processes from global to regional systems is provided. A rich variety of approaches exists. An example is provided of how the Copernicus Marine Service organizes product quality information.
Stefania Ciliberti and Gianpaolo Coro
State Planet, 5-opsr, 24, https://doi.org/10.5194/sp-5-opsr-24-2025, https://doi.org/10.5194/sp-5-opsr-24-2025, 2025
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This review explores how cloud computing technology and its foundational concepts can enhance operational forecasting with scalable, flexible, and measurable resources. It highlights its benefits for the ocean value chain in support of ocean data management, forecasting system infrastructure, data analysis, visualization of ocean forecasts, dissemination, and outreach, showcasing real-world initiatives from the weather and ocean community.
Yann Drillet, Matthew Martin, Yosuke Fujii, Eric Chassignet, and Stefania Ciliberti
State Planet, 5-opsr, 2, https://doi.org/10.5194/sp-5-opsr-2-2025, https://doi.org/10.5194/sp-5-opsr-2-2025, 2025
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This article describes the various stages of research and development that have been carried out over the last few decades to produce an operational reference service for global ocean monitoring and forecasting.
Fabrice Hernandez, Marcos Garcia Sotillo, and Angélique Melet
State Planet, 5-opsr, 17, https://doi.org/10.5194/sp-5-opsr-17-2025, https://doi.org/10.5194/sp-5-opsr-17-2025, 2025
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An historical review over the last 3 decades on intercomparison projects of ocean numerical reanalysis or forecast is first proposed. From this, main issues and lessons learned are discussed in order to propose an overview of best practices and key considerations to facilitate intercomparison activities in operational oceanography.
Michael J. Bell, Andreas Schiller, and Stefania Ciliberti
State Planet, 5-opsr, 10, https://doi.org/10.5194/sp-5-opsr-10-2025, https://doi.org/10.5194/sp-5-opsr-10-2025, 2025
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We provide an introduction to physical ocean models, at elementary and intermediate levels, describing the properties they represent, the principles and equations they use to evolve these properties, the physical phenomena they simulate, and the wider context and prospects for their further development. We also outline, at a more technical level, the methods and approximations that they use and the difficulties that limit their accuracy or reliability.
Alisée A. Chaigneau, Angélique Melet, Aurore Voldoire, Maialen Irazoqui Apecechea, Guillaume Reffray, Stéphane Law-Chune, and Lotfi Aouf
Nat. Hazards Earth Syst. Sci., 24, 4031–4048, https://doi.org/10.5194/nhess-24-4031-2024, https://doi.org/10.5194/nhess-24-4031-2024, 2024
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Climate-change-induced sea level rise increases the frequency of extreme sea levels. We analyze projected changes in extreme sea levels for western European coasts produced with high-resolution models (∼ 6 km). Unlike commonly used coarse-scale global climate models, this approach allows us to simulate key processes driving coastal sea level variations, such as long-term sea level rise, tides, storm surges induced by low atmospheric surface pressure and winds, waves, and their interactions.
Álvaro de Pascual Collar, Roland Aznar, Bruno Levier, and Marcos García Sotillo
State Planet, 4-osr8, 5, https://doi.org/10.5194/sp-4-osr8-5-2024, https://doi.org/10.5194/sp-4-osr8-5-2024, 2024
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The Iberia–Biscay–Ireland region in the North Atlantic has diverse ocean currents impacting upper and deeper layers. These currents are vital for heat transport, species dispersion, and sediment and pollutant movement. Monitoring them is crucial for informed decision-making in ocean-related activities, including the blue economy sector. This study introduces an indicator to track these currents, covering main ones like the Azores, Canary, Portugal, and poleward slope currents.
Alice Laloue, Malek Ghantous, Yannice Faugère, Alice Dalphinet, and Lotfi Aouf
State Planet, 4-osr8, 6, https://doi.org/10.5194/sp-4-osr8-6-2024, https://doi.org/10.5194/sp-4-osr8-6-2024, 2024
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Satellite altimetry shows that daily mean significant wave heights (SWHs) and extreme SWHs have increased in the Southern Ocean, the South Atlantic, and the southern Indian Ocean over the last 2 decades. In winter in the North Atlantic, SWH has increased north of 45°N and decreased south of 45°N. SWHs likely to be exceeded every 100 years have also increased in the North Atlantic and the eastern tropical Pacific. However, this study also revealed the need for longer and more consistent series.
Álvaro de Pascual-Collar, Roland Aznar, Bruno Levier, and Marcos García-Sotillo
State Planet, 1-osr7, 9, https://doi.org/10.5194/sp-1-osr7-9-2023, https://doi.org/10.5194/sp-1-osr7-9-2023, 2023
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The article comprises the analysis of the ocean heat content in the northeastern Atlantic Iberian–Biscay–Ireland (IBI) region. The variability of ocean heat content is studied, and results are linked with the variability of the main water masses found in the region. Results show how the coupled interannual variability of water masses accounts for an important part of the total ocean heat content variability in the region.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Alisée A. Chaigneau, Stéphane Law-Chune, Angélique Melet, Aurore Voldoire, Guillaume Reffray, and Lotfi Aouf
Ocean Sci., 19, 1123–1143, https://doi.org/10.5194/os-19-1123-2023, https://doi.org/10.5194/os-19-1123-2023, 2023
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Wind waves and swells are major drivers of coastal environment changes and can drive coastal marine hazards such as coastal flooding. In this paper, by using numerical modeling along the European Atlantic coastline, we assess how present and future wave characteristics are impacted by sea level changes. For example, at the end of the century under the SSP5-8.5 climate change scenario, extreme significant wave heights are higher by up to +40 % due to the effect of tides and mean sea level rise.
Marzieh H. Derkani, Alberto Alberello, Filippo Nelli, Luke G. Bennetts, Katrin G. Hessner, Keith MacHutchon, Konny Reichert, Lotfi Aouf, Salman Khan, and Alessandro Toffoli
Earth Syst. Sci. Data, 13, 1189–1209, https://doi.org/10.5194/essd-13-1189-2021, https://doi.org/10.5194/essd-13-1189-2021, 2021
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The Southern Ocean has a profound impact on the Earth's climate system. Its strong winds, intense currents, and fierce waves are critical components of the air–sea interface. The scarcity of observations in this remote region hampers the comprehension of fundamental physics, the accuracy of satellite sensors, and the capabilities of prediction models. To fill this gap, a unique data set of simultaneous observations of winds, surface currents, and ocean waves in the Southern Ocean is presented.
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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.
Accurate short-term wave forecasts are key for coastal activities. These forecasts rely on wind...