Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-1101-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-1101-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
24 Feb 2021
Development and technical paper |
| 24 Feb 2021
| 24 Feb 2021
A fully coupled Arctic sea-ice–ocean–atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results
Shihe Ren
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Qizhen Sun
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing, China
L. Bruno Tremblay
Department of Atmospheric and Oceanic Sciences, McGill University,
Montreal, Canada
Bo Lin
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Xiaoping Mai
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Fu Zhao
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Ming Li
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Na Liu
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Zhikun Chen
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
Yunfei Zhang
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, China
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Cited
10 citations as recorded by crossref.
- Impact of the Novaya Zemlya Bora on the Ocean-Atmosphere Heat Exchange and Ocean Circulation: A Case-Study with the Coupled Model A. Shestakova & A. Debolskiy 10.3390/atmos13071108
- A deep learning-based bias correction model for Arctic sea ice concentration towards MITgcm S. Yuan et al. 10.1016/j.ocemod.2024.102326
- Subseasonal-to-seasonal prediction of arctic sea ice Using a Fully Coupled dynamical ensemble forecast system A. Liu et al. 10.1016/j.atmosres.2023.107014
- CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0 X. Yu et al. 10.5194/gmd-16-6285-2023
- A Global Coupled Atmosphere-Wave Model System Based on C-Coupler2. Part I: Model Description W. Peng et al. 10.1088/1742-6596/2718/1/012025
- C-Coupler3.0: an integrated coupler infrastructure for Earth system modelling L. Liu et al. 10.5194/gmd-16-2833-2023
- Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts F. Zhao et al. 10.5194/gmd-17-6867-2024
- Conservation of heat and mass in P-SKRIPS version 1: the coupled atmosphere–ice–ocean model of the Ross Sea A. Malyarenko et al. 10.5194/gmd-16-3355-2023
- Evaluation of the ArcIOPS sea ice forecasts during 2021–2023 X. Liang et al. 10.3389/feart.2024.1477626
- Polar Sea Ice Identification and Classification Based on HY-2A/SCAT Data R. Xu et al. 10.1007/s11802-022-4903-8
10 citations as recorded by crossref.
- Impact of the Novaya Zemlya Bora on the Ocean-Atmosphere Heat Exchange and Ocean Circulation: A Case-Study with the Coupled Model A. Shestakova & A. Debolskiy 10.3390/atmos13071108
- A deep learning-based bias correction model for Arctic sea ice concentration towards MITgcm S. Yuan et al. 10.1016/j.ocemod.2024.102326
- Subseasonal-to-seasonal prediction of arctic sea ice Using a Fully Coupled dynamical ensemble forecast system A. Liu et al. 10.1016/j.atmosres.2023.107014
- CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0 X. Yu et al. 10.5194/gmd-16-6285-2023
- A Global Coupled Atmosphere-Wave Model System Based on C-Coupler2. Part I: Model Description W. Peng et al. 10.1088/1742-6596/2718/1/012025
- C-Coupler3.0: an integrated coupler infrastructure for Earth system modelling L. Liu et al. 10.5194/gmd-16-2833-2023
- Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts F. Zhao et al. 10.5194/gmd-17-6867-2024
- Conservation of heat and mass in P-SKRIPS version 1: the coupled atmosphere–ice–ocean model of the Ross Sea A. Malyarenko et al. 10.5194/gmd-16-3355-2023
- Evaluation of the ArcIOPS sea ice forecasts during 2021–2023 X. Liang et al. 10.3389/feart.2024.1477626
- Polar Sea Ice Identification and Classification Based on HY-2A/SCAT Data R. Xu et al. 10.1007/s11802-022-4903-8
Latest update: 17 Nov 2024
Short summary
Sea ice plays a crucial role in global energy and water budgets. To get a better simulation of sea ice, we coupled a sea ice model with an atmospheric and ocean model to form a fully coupled system. The sea ice simulation results of this coupled system demonstrated that a two-way coupled model has better performance in terms of sea ice, especially in summer. This indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution.
Sea ice plays a crucial role in global energy and water budgets. To get a better simulation of...
