Articles | Volume 22, issue 5
https://doi.org/10.5194/os-22-2863-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-22-2863-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantitative evaluation of mesoscale eddies in the North Atlantic using satellite altimetry and ocean reanalyses
Institute of Marine Sciences, National Research Council of Italy, Rome, Italy
Department of Physics “E.R. Caianiello”, University of Salerno, Fisciano, Italy
Gregory C. Smith
Meteorological Research Division, Environment and Climate Change Canada (ECCC), Dorval, Canada
Andrea Storto
Institute of Marine Sciences, National Research Council of Italy, Rome, Italy
Chunxue Yang
Institute of Marine Sciences, National Research Council of Italy, Rome, Italy
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Susanna Winkelbauer, Gaël Forget, Michael Mayer, Romain Bourdalle-Badie, Andrea Cipollone, Leopold Haimberger, Keith Haines, Satoshi Osafune, Yuanyuan Song, Andrea Storto, Chunxue Yang, and Hao Zuo
EGUsphere, https://doi.org/10.5194/egusphere-2026-5435, https://doi.org/10.5194/egusphere-2026-5435, 2026
This preprint is open for discussion and under review for Ocean Science (OS).
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Ocean currents carry vast amounts of heat through the Atlantic and strongly influence climate. We compared estimates from 17 global ocean reanalyses with observations to assess how well they reproduce this heat transport and its changes over time. Most reanalyses capture the main patterns and variations, but important differences remain. The reanalyses also suggest a decrease in northward heat transport since the early 1990s, although its magnitude remains uncertain.
Andrea Storto, Vincenzo de Toma, and Chunxue Yang
Ocean Sci., 22, 2809–2834, https://doi.org/10.5194/os-22-2809-2026, https://doi.org/10.5194/os-22-2809-2026, 2026
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The Mediterranean region is one of the fastest-warming areas on Earth, and understanding its changes is thus crucial. We produced a new reconstruction of the Mediterranean climate for the 1993–2024 period, using a modelling system that combines weather, ocean, and hydrology information with observations. This new reanalysis offers a clearer picture of how the region has been warming, drying, and changing over the past 30 years, supporting better studies of extreme events and climate impacts.
Yushi Morioka, Doroteaciro Iovino, Andrea Cipollone, Andrea Storto, Takeshi Doi, Masami Nonaka, and Swadhin K. Behera
EGUsphere, https://doi.org/10.5194/egusphere-2026-5070, https://doi.org/10.5194/egusphere-2026-5070, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Arctic sea ice has been shrinking for the last four decades. As global warming continues, predicting summer sea ice is becoming more important. Here we create a seasonal forecast system using the SINTEX-F3 model. Results show that summer sea ice in the Barents-Kara Sea is best predicted when accurate sea ice and snow conditions are provided from spring. It is found that initial sea ice thickness acts as a memory for the climate system, enabling accurate summer sea ice prediction from spring.
Kristian Strommen, Michael Mayer, Andrea Storto, Jonas Spaeth, and Steffen Tietsche
Weather Clim. Dynam., 7, 1593–1618, https://doi.org/10.5194/wcd-7-1593-2026, https://doi.org/10.5194/wcd-7-1593-2026, 2026
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Numerical weather forecasts of sea ice are unreliable, exhibiting an overly narrow range of plausible sea ice evolutions. Stochastic perturbations introduce randomness to the forecast in order to alleviate this by representing uncertainties in the representation of sea ice physics. We show that including such perturbations in a forecast model improves the reliability of sea ice forecasts, and furthermore results in improved seasonal forecasts of the northern European winter circulation.
Alejandro Blazquez, Benoit Meyssignac, Robin Fraudeau, Michael Ablain, Jonathan Bamber, Antonio Bonaduce, Marie Bouih, Anny Cazenave, Thorben Döhne, Ines Dussaillant, Ramiro Ferrari, Martin Horwath, Nicolas Kolodziejczyk, Hugo Lecomte, Stephanie Leroux, William Llovel, Daniele Melini, Erwan Oulhen, Thierry Penduff, Roshin P. Raj, Giorgio Spada, Marius Schlaak, Papasarafianou Stamatia, Andrea Storto, Chunxue Yang, and Sarah Connors
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-627, https://doi.org/10.5194/essd-2026-627, 2026
Preprint under review for ESSD
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Closing the sea‑level budget on annual and longer time scales is a cornerstone of physical oceanography because sea‑level rise is one of the best indicators of climate change, and a closed budget shows we have identified and quantified all major drivers. We examined it from 1993 to 2022, finding an accelerated rise that matched ice melt and warm water until 2015. Afterwards an unexplained gap appears. Better deep‑ocean observations and refined gravity processing are needed to close the budget.
Louis Kern, Thomas Vaujour, Julia Pfeffer, Andrea Storto, Camille Szczypta, Gilles Garric, Claire Sirere, Gilles Larnicol, Chunxue Yang, Romain Bourdalle-Badie, and Stéphanie Guinehut
EGUsphere, https://doi.org/10.5194/egusphere-2025-6351, https://doi.org/10.5194/egusphere-2025-6351, 2026
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Freshwater fluxes, despite their importance, are often poorly represented in ocean models. The impact of river discharge is evaluated from the Water Mass Balance approach, combining gravimetry and atmospheric reanalyses data. These estimates are assessed against river gauges, highlighting good agreement over South American rivers. Compared to climatological data, when used as inputs for ocean model simulations, this technique improves salinity and upper ocean circulation representation.
Alexis Barge, Julien Le Sommer, Andrea Storto, and Sophie Valcke
EGUsphere, https://doi.org/10.5194/egusphere-2026-854, https://doi.org/10.5194/egusphere-2026-854, 2026
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Scientists use programs, called Earth System Models, to study and predict climate. These models are based on physical theories but can be completed with AI tools. However, combining these tools with traditional models is difficult due to their different nature. Our research introduces a new method that connects these AI tools with existing climate models. We tested this method by integrating it with an ocean model. This work should help scientists explore new ways of making climate predictions.
Zhe Song, Anny Cazenave, William Llovel, Andrea Storto, and Marie Bouih
EGUsphere, https://doi.org/10.5194/egusphere-2026-802, https://doi.org/10.5194/egusphere-2026-802, 2026
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The objective of this study is to understand why the North Atlantic sea level budget is not closed over the Argo and Gravity Recovery and Climate Experiment (GRACE) era. We show that using an ocean reanalysis for the ocean mass component instead of GRACE, and accounting for deep ocean warming allows closure of the North Atlantic sea level budget within data uncertainties.
Haohao Zhang, Andrea Storto, Xuezhi Bai, and Chunxue Yang
The Cryosphere, 19, 6807–6826, https://doi.org/10.5194/tc-19-6807-2025, https://doi.org/10.5194/tc-19-6807-2025, 2025
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Using a 1D coupled ice-ocean model, we quantified the effects of meltwater and ice-albedo feedback independently. The meltwater reduces melting by 19 % through thermal isolation, while ice-albedo feedback increases melting by 41 %, with nonlinear coupling between them. In winter, meltwater protects ice in weakly stratified areas by blocking Atlantic heat. Our study provides new insights into the relative importance of different components in the Arctic ice-ocean system.
Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang
Geosci. Model Dev., 18, 4789–4804, https://doi.org/10.5194/gmd-18-4789-2025, https://doi.org/10.5194/gmd-18-4789-2025, 2025
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Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
Marie Bouih, Anne Barnoud, Chunxue Yang, Andrea Storto, Alejandro Blazquez, William Llovel, Robin Fraudeau, and Anny Cazenave
Ocean Sci., 21, 1425–1440, https://doi.org/10.5194/os-21-1425-2025, https://doi.org/10.5194/os-21-1425-2025, 2025
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Present-day sea level rise is not uniform regionally. For better understanding of regional sea level variations, a classical approach is to compare the observed sea level trend patterns with those of the sum of the contributions. If the regional sea level trend budget is not closed, this allows the detection of errors in the observing systems. Our study shows that the trend budget is not closed in the North Atlantic Ocean and identifies errors in Argo-based salinity data as the main suspect.
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.
Andrea Storto, Giulia Chierici, Julia Pfeffer, Anne Barnoud, Romain Bourdalle-Badie, Alejandro Blazquez, Davide Cavaliere, Noémie Lalau, Benjamin Coupry, Marie Drevillon, Sebastien Fourest, Gilles Larnicol, and Chunxue Yang
State Planet, 4-osr8, 12, https://doi.org/10.5194/sp-4-osr8-12-2024, https://doi.org/10.5194/sp-4-osr8-12-2024, 2024
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The variability in the manometric sea level (i.e. the sea level mass component) in three ocean basins is investigated in this study using three different methods (reanalyses, gravimetry, and altimetry in combination with in situ observations). We identify the emerging long-term signals, the consistency of the datasets, and the influence of large-scale climate modes on the regional manometric sea level variations at both seasonal and interannual timescales.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Adrienne Tivy, Joey Angnatok, François Roy, Gregory Smith, Frédéric Dupont, and Adrian K. Turner
The Cryosphere, 18, 1685–1708, https://doi.org/10.5194/tc-18-1685-2024, https://doi.org/10.5194/tc-18-1685-2024, 2024
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We use a sea ice model to reproduce ice growth observations from two buoys deployed on coastal sea ice and analyze the improvements brought by new physics that represent the presence of saline liquid water in the ice interior. We find that the new physics with default parameters degrade the model performance, with overly rapid ice growth and overly early snow flooding on top of the ice. The performance is largely improved by simple modifications to the ice growth and snow-flooding algorithms.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, https://doi.org/10.5194/gmd-16-4811-2023, 2023
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Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Jean-Philippe Paquin, François Roy, Gregory C. Smith, Sarah MacDermid, Ji Lei, Frédéric Dupont, Youyu Lu, Stephanne Taylor, Simon St-Onge-Drouin, Hauke Blanken, Michael Dunphy, and Nancy Soontiens
EGUsphere, https://doi.org/10.5194/egusphere-2023-42, https://doi.org/10.5194/egusphere-2023-42, 2023
Preprint withdrawn
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This paper present the Coastal Ice-Ocean Prediction System implemented operationally at Environment and climate change Canada. The objective is to enhance the numerical guidance in coastal areas to support electronic navigation and response to environmental emergencies in the aquatic environment. Model evaluation against observations shows improvements for most surface ocean variables in the coastal system compared to current coarser-resolution operational systems.
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Short summary
This article evaluates two ocean reanalyses with spatial resolutions of 1/4° and 1/12° by comparing them with two satellite observation products, both at 1/8° resolution. The results show the added value of higher model resolution for representing mesoscale eddies and highlight the value of wide-swath satellite altimetry for model verification in the North Atlantic.
This article evaluates two ocean reanalyses with spatial resolutions of 1/4° and 1/12° by...
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