Articles | Volume 22, issue 1
https://doi.org/10.5194/os-22-241-2026
© Author(s) 2026. 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-22-241-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A robust minimization-based framework for cyclogeostrophic ocean surface current retrieval
Vadim Bertrand
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, Grenoble, 38000, France
Julien Le Sommer
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, Grenoble, 38000, France
Victor Vianna Zaia De Almeida
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, Grenoble, 38000, France
Adeline Samson
Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, 38000, France
Emmanuel Cosme
Univ. Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, Grenoble, 38000, France
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Mikhail Popov, Jean-Michel Brankart, Arthur Capet, Emmanuel Cosme, and Pierre Brasseur
Ocean Sci., 20, 155–180, https://doi.org/10.5194/os-20-155-2024, https://doi.org/10.5194/os-20-155-2024, 2024
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This study contributes to the development of methods to estimate targeted ocean ecosystem indicators, including their uncertainty, in the framework of the Copernicus Marine Service. A simplified approach is introduced to perform a 4D ensemble analysis and forecast, directly targeting selected biogeochemical variables and indicators (phenology, trophic efficiency, downward flux of organic matter). Care is taken to present the methods and discuss the reliability of the solution proposed.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Florian Le Guillou, Lucile Gaultier, Maxime Ballarotta, Sammy Metref, Clément Ubelmann, Emmanuel Cosme, and Marie-Helène Rio
Ocean Sci., 19, 1517–1527, https://doi.org/10.5194/os-19-1517-2023, https://doi.org/10.5194/os-19-1517-2023, 2023
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Altimetry provides sea surface height (SSH) data along one-dimensional tracks. For many applications, the tracks are interpolated in space and time to provide gridded SSH maps. The operational SSH gridded products filter out the small-scale signals measured on the tracks. This paper evaluates the performances of a recently implemented dynamical method to retrieve the small-scale signals from real SSH data. We show a net improvement in the quality of SSH maps when compared to independent data.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
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The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Sammy Metref, Emmanuel Cosme, Matthieu Le Lay, and Joël Gailhard
Hydrol. Earth Syst. Sci., 27, 2283–2299, https://doi.org/10.5194/hess-27-2283-2023, https://doi.org/10.5194/hess-27-2283-2023, 2023
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Predicting the seasonal streamflow supply of water in a mountainous basin is critical to anticipating the operation of hydroelectric dams and avoiding hydrology-related hazard. This quantity partly depends on the snowpack accumulated during winter. The study addresses this prediction problem using information from streamflow data and both direct and indirect snow measurements. In this study, the prediction is improved by integrating the data information into a basin-scale hydrological model.
Stephanie Leroux, Jean-Michel Brankart, Aurélie Albert, Laurent Brodeau, Jean-Marc Molines, Quentin Jamet, Julien Le Sommer, Thierry Penduff, and Pierre Brasseur
Ocean Sci., 18, 1619–1644, https://doi.org/10.5194/os-18-1619-2022, https://doi.org/10.5194/os-18-1619-2022, 2022
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The goal of the study is to evaluate the predictability of the ocean circulation
at a kilometric scale, in order to anticipate the requirements of the future operational forecasting systems. For that purpose, ensemble experiments have been performed with a regional model for the Western Mediterranean (at 1/60° horizontal resolution). From these ensemble experiments, we show that it is possible to compute targeted predictability scores, which depend on initial and model uncertainties.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
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Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, https://doi.org/10.5194/gmd-14-1595-2021, 2021
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In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
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Short summary
Understanding ocean surface currents is essential for navigation and environmental monitoring. Traditionally, currents are estimated from satellite sea surface height using a simplified balance. We developed a new method that goes beyond this approximation, providing more accurate currents estimates. Using a model simulation, satellite observations, and drifters data, we show that these corrections become increasingly important at finer spatial scales, especially in energetic regions.
Understanding ocean surface currents is essential for navigation and environmental monitoring....