Articles | Volume 17, issue 2
https://doi.org/10.5194/tc-17-617-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-617-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Feb 2023
Research article |
| 08 Feb 2023
| 08 Feb 2023
Arctic sea ice mass balance in a new coupled ice–ocean model using a brittle rheology framework
Guillaume Boutin
CORRESPONDING AUTHOR
Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
Einar Ólason
Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
Pierre Rampal
CNRS, Institut de Géophysique de l'Environnement, Grenoble 38058, France
Heather Regan
Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
Camille Lique
Univ. Brest, CNRS, IRD, Ifremer, Laboratoire d’Océanographie Physique et Spatiale, IUEM, Brest 29280, France
Claude Talandier
Univ. Brest, CNRS, IRD, Ifremer, Laboratoire d’Océanographie Physique et Spatiale, IUEM, Brest 29280, France
Laurent Brodeau
CNRS, Institut de Géophysique de l'Environnement, Grenoble 38058, France
Robert Ricker
NORCE Norwegian Research Centre, Tromsø, Norway
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Cited
16 citations as recorded by crossref.
- Lead fractions from SAR-derived sea ice divergence during MOSAiC L. von Albedyll et al. https://doi.org/10.5194/tc-18-1259-2024
- Modeling the contribution of leads to sea spray aerosol in the high Arctic R. Lapere et al. https://doi.org/10.5194/acp-24-12107-2024
- Tuning parameters of a sea ice model using machine learning A. Korosov et al. https://doi.org/10.5194/gmd-18-885-2025
- The Stepwise Reduction of Multiyear Sea Ice Area in the Arctic Ocean Since 1980 D. Babb et al. https://doi.org/10.1029/2023JC020157
- Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology Y. Chen et al. https://doi.org/10.5194/tc-18-2381-2024
- Four-dimensional variational data assimilation with a sea-ice thickness emulator C. Durand et al. https://doi.org/10.5194/tc-19-5613-2025
- Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic L. Brodeau et al. https://doi.org/10.5194/gmd-17-6051-2024
- Development and Evaluation of an Ice-Embedded Irradiance Profiler for Seasonally Measuring Solar Irradiance Distribution Within Sea Ice H. Huang et al. https://doi.org/10.1109/JOE.2025.3617904
- Comparing heterogeneity of sea-ice models with viscous-plastic and Maxwell elasto-brittle rheology M. Bourgett et al. https://doi.org/10.1017/aog.2024.40
- The biogenic sulfur cycle in the coupled ocean–sea ice–atmosphere system S. Ishino et al. https://doi.org/10.1525/elementa.2025.00067
- Methane pumping by rapidly refreezing lead ice in the ice-covered Arctic Ocean E. Damm et al. https://doi.org/10.3389/feart.2024.1338246
- Modeling Antarctic Sea Ice Variability Using a Brittle Rheology R. Santana et al. https://doi.org/10.1029/2024MS004584
- Data-driven surrogate modeling of high-resolution sea-ice thickness in the Arctic C. Durand et al. https://doi.org/10.5194/tc-18-1791-2024
- Oceanography, biogeochemical cycles, and biodiversity in the Central Arctic Ocean: Current state of knowledge and research directions for the Tara Polaris expeditions M. Geoffroy et al. https://doi.org/10.1525/elementa.2025.00027
- Modelling the evolution of Arctic multiyear sea ice over 2000–2018 H. Regan et al. https://doi.org/10.5194/tc-17-1873-2023
- Cloud-Tolerant Multiwidth Arctic Sea-Ice Lead Detection Using FY-3D MERSI-II 250-m TIR Data L. Zhang et al. https://doi.org/10.1109/TGRS.2025.3631915
16 citations as recorded by crossref.
- Lead fractions from SAR-derived sea ice divergence during MOSAiC L. von Albedyll et al. https://doi.org/10.5194/tc-18-1259-2024
- Modeling the contribution of leads to sea spray aerosol in the high Arctic R. Lapere et al. https://doi.org/10.5194/acp-24-12107-2024
- Tuning parameters of a sea ice model using machine learning A. Korosov et al. https://doi.org/10.5194/gmd-18-885-2025
- The Stepwise Reduction of Multiyear Sea Ice Area in the Arctic Ocean Since 1980 D. Babb et al. https://doi.org/10.1029/2023JC020157
- Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology Y. Chen et al. https://doi.org/10.5194/tc-18-2381-2024
- Four-dimensional variational data assimilation with a sea-ice thickness emulator C. Durand et al. https://doi.org/10.5194/tc-19-5613-2025
- Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic L. Brodeau et al. https://doi.org/10.5194/gmd-17-6051-2024
- Development and Evaluation of an Ice-Embedded Irradiance Profiler for Seasonally Measuring Solar Irradiance Distribution Within Sea Ice H. Huang et al. https://doi.org/10.1109/JOE.2025.3617904
- Comparing heterogeneity of sea-ice models with viscous-plastic and Maxwell elasto-brittle rheology M. Bourgett et al. https://doi.org/10.1017/aog.2024.40
- The biogenic sulfur cycle in the coupled ocean–sea ice–atmosphere system S. Ishino et al. https://doi.org/10.1525/elementa.2025.00067
- Methane pumping by rapidly refreezing lead ice in the ice-covered Arctic Ocean E. Damm et al. https://doi.org/10.3389/feart.2024.1338246
- Modeling Antarctic Sea Ice Variability Using a Brittle Rheology R. Santana et al. https://doi.org/10.1029/2024MS004584
- Data-driven surrogate modeling of high-resolution sea-ice thickness in the Arctic C. Durand et al. https://doi.org/10.5194/tc-18-1791-2024
- Oceanography, biogeochemical cycles, and biodiversity in the Central Arctic Ocean: Current state of knowledge and research directions for the Tara Polaris expeditions M. Geoffroy et al. https://doi.org/10.1525/elementa.2025.00027
- Modelling the evolution of Arctic multiyear sea ice over 2000–2018 H. Regan et al. https://doi.org/10.5194/tc-17-1873-2023
- Cloud-Tolerant Multiwidth Arctic Sea-Ice Lead Detection Using FY-3D MERSI-II 250-m TIR Data L. Zhang et al. https://doi.org/10.1109/TGRS.2025.3631915
Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads...
