Articles | Volume 18, issue 15
https://doi.org/10.5194/gmd-18-4789-2025
© Author(s) 2025. 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/gmd-18-4789-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Aug 2025
Development and technical paper |
| 04 Aug 2025
| 04 Aug 2025
Correction of sea surface biases in the NEMO ocean general circulation model using neural networks
National Research Council of Italy (CNR), Institute of Marine Sciences (ISMAR), Rome, Italy
National Research Center for High Performance Computing, Big Data and Quantum Computing (ICSC), Italy
Sergey Frolov
National Oceanic and Atmospheric Administration (NOAA), Physical Sciences Laboratory (PSL), Boulder, CO, USA
Laura Slivinski
National Oceanic and Atmospheric Administration (NOAA), Physical Sciences Laboratory (PSL), Boulder, CO, USA
Chunxue Yang
National Research Council of Italy (CNR), Institute of Marine Sciences (ISMAR), Rome, Italy
National Research Center for High Performance Computing, Big Data and Quantum Computing (ICSC), Italy
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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.
Yushi Morioka, Doroteaciro Iovino, Andrea Cipollone, Andrea Storto, Takeshi Doi, Masami Nonaka, and Swadhin K. Behera
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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.
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
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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.
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EGUsphere, https://doi.org/10.5194/egusphere-2026-2257, https://doi.org/10.5194/egusphere-2026-2257, 2026
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We studied how well ocean models represent ocean features by comparing them with satellite data. The high resolution model GLORYS12V1 matches observations better than GLORYS2V4, especially for strong features, but it also detects more weak ones, increasing false detections. Satellite data from DUACS and SWOT MIOST Science improve the evaluation and help compare models and observations. These results show that higher detail is important to better understand ocean dynamics.
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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.
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.
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.
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.
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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.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
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Yushi Morioka, Doroteaciro Iovino, Andrea Cipollone, Andrea Storto, Takeshi Doi, Masami Nonaka, and Swadhin K. Behera
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This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
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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
Short summary
Short summary
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
Short summary
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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.
Rhidian Huw Thomas, Gilbert P. Compo, Steve George, Gabriele C. Hegerl, Andrew Schurer, Theodore G. Shepherd, Laura C. Slivinski, Vikki Thompson, and Ed Hawkins
EGUsphere, https://doi.org/10.5194/egusphere-2026-2548, https://doi.org/10.5194/egusphere-2026-2548, 2026
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We explore how our day-to-day experience of the weather may change in a warmer world. We compare weather model experiments that share the same weather patterns, but have different levels of CO2 and ocean surface warming. In the warmer experiments, the biggest temperature changes occur on the coldest and hottest days. Daily swings in rainfall become larger, and we see fewer drizzly days and more days with heavy rain. This illustrates the impact of climate change on our day-to-day weather.
Paolo Mauriello, Gregory C. Smith, Andrea Storto, and Chunxue Yang
EGUsphere, https://doi.org/10.5194/egusphere-2026-2257, https://doi.org/10.5194/egusphere-2026-2257, 2026
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We studied how well ocean models represent ocean features by comparing them with satellite data. The high resolution model GLORYS12V1 matches observations better than GLORYS2V4, especially for strong features, but it also detects more weak ones, increasing false detections. Satellite data from DUACS and SWOT MIOST Science improve the evaluation and help compare models and observations. These results show that higher detail is important to better understand ocean dynamics.
Andrea Storto, Vincenzo de Toma, and Chunxue Yang
EGUsphere, https://doi.org/10.5194/egusphere-2026-1549, https://doi.org/10.5194/egusphere-2026-1549, 2026
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Tim Trent, Marc Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
Atmos. Chem. Phys., 24, 9667–9695, https://doi.org/10.5194/acp-24-9667-2024, https://doi.org/10.5194/acp-24-9667-2024, 2024
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Short summary
In a warmer future, water vapour will spend more time in the atmosphere, changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 and 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends and differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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).
Ed Hawkins, Philip Brohan, Samantha N. Burgess, Stephen Burt, Gilbert P. Compo, Suzanne L. Gray, Ivan D. Haigh, Hans Hersbach, Kiki Kuijjer, Oscar Martínez-Alvarado, Chesley McColl, Andrew P. Schurer, Laura Slivinski, and Joanne Williams
Nat. Hazards Earth Syst. Sci., 23, 1465–1482, https://doi.org/10.5194/nhess-23-1465-2023, https://doi.org/10.5194/nhess-23-1465-2023, 2023
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We examine a severe windstorm that occurred in February 1903 and caused significant damage in the UK and Ireland. Using newly digitized weather observations from the time of the storm, combined with a modern weather forecast model, allows us to determine why this storm caused so much damage. We demonstrate that the event is one of the most severe windstorms to affect this region since detailed records began. The approach establishes a new tool to improve assessments of risk from extreme weather.
Stefan Brönnimann, Peter Stucki, Jörg Franke, Veronika Valler, Yuri Brugnara, Ralf Hand, Laura C. Slivinski, Gilbert P. Compo, Prashant D. Sardeshmukh, Michel Lang, and Bettina Schaefli
Clim. Past, 18, 919–933, https://doi.org/10.5194/cp-18-919-2022, https://doi.org/10.5194/cp-18-919-2022, 2022
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Floods in Europe vary on time scales of several decades. Flood-rich and flood-poor periods alternate. Recently floods have again become more frequent. Long time series of peak stream flow, precipitation, and atmospheric variables reveal that until around 1980, these changes were mostly due to changes in atmospheric circulation. However, in recent decades the role of increasing atmospheric moisture due to climate warming has become more important and is now the main driver of flood changes.
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Short summary
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.
Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical...
Special issue