Articles | Volume 15, issue 1
https://doi.org/10.5194/tc-15-31-2021
© 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/tc-15-31-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Jan 2021
Research article |
| 05 Jan 2021
| 05 Jan 2021
Evaluation of sea-ice thickness from four reanalyses in the Antarctic Weddell Sea
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China
Qingdao Pilot National Laboratory for Marine Science and Technology, Qingdao, China
Jinfei Wang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China
François Massonnet
Georges Lemaître Centre for Earth and Climate Research, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Matthew R. Mazloff
Scripps Institution of Oceanography, University of California, San Diego, CA, USA
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Cited
14 citations as recorded by crossref.
- Consistent Comparison of Remotely Sensed Sea Ice Concentration Products with ERA-Interim Reanalysis Data in Polar Regions S. Liang et al. 10.3390/rs12182880
- Seasonal and Interannual Variations in Sea Ice Thickness in the Weddell Sea, Antarctica (2019–2022) Using ICESat-2 M. Joshi et al. 10.3390/rs16203909
- China’s Recent Progresses in Polar Climate Change and Its Interactions with the Global Climate System X. Li et al. 10.1007/s00376-023-2323-3
- Estimation of Daily Arctic Winter Sea Ice Thickness from Thermodynamic Parameters Using a Self-Attention Convolutional Neural Network Z. Liang et al. 10.3390/rs15071887
- Southern Ocean sea ice concentration budgets of five ocean-sea ice reanalyses Y. Nie et al. 10.1007/s00382-022-06260-x
- The MET Norway Ice Service: a comprehensive review of the historical and future evolution, ice chart creation, and end user interaction within METAREA XIX W. Copeland et al. 10.3389/fmars.2024.1400479
- DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations H. Luo et al. 10.1017/jog.2021.57
- An evaluation of Antarctic sea-ice thickness from the Global Ice-Ocean Modeling and Assimilation System based on in situ and satellite observations S. Liao et al. 10.5194/tc-16-1807-2022
- Exploring sea ice transport dynamics at the eastern gate of the Ross Sea N. Krauzig et al. 10.1016/j.dsr2.2024.105428
- Optimized sea ice simulation in MITgcm-ECCO2 forced by ERA5 E. Gavilan Pascual-Ahuir & Z. Wang 10.1016/j.ocemod.2023.102183
- Evaluation of Antarctic sea ice thickness and volume during 2003–2014 in CMIP6 using Envisat and CryoSat-2 observations Y. Hou et al. 10.1088/1748-9326/ad1725
- The Impacts of Optimizing Model‐Dependent Parameters on the Antarctic Sea Ice Data Assimilation H. Luo et al. 10.1029/2023GL105690
- Effects of sea ice form drag on the polar oceans in the NEMO-LIM3 global ocean–sea ice model J. Sterlin et al. 10.1016/j.ocemod.2023.102227
- Consistent Comparison of Remotely Sensed Sea Ice Concentration Products with ERA-Interim Reanalysis Data in Polar Regions S. Liang et al. 10.3390/rs12182880
13 citations as recorded by crossref.
- Consistent Comparison of Remotely Sensed Sea Ice Concentration Products with ERA-Interim Reanalysis Data in Polar Regions S. Liang et al. 10.3390/rs12182880
- Seasonal and Interannual Variations in Sea Ice Thickness in the Weddell Sea, Antarctica (2019–2022) Using ICESat-2 M. Joshi et al. 10.3390/rs16203909
- China’s Recent Progresses in Polar Climate Change and Its Interactions with the Global Climate System X. Li et al. 10.1007/s00376-023-2323-3
- Estimation of Daily Arctic Winter Sea Ice Thickness from Thermodynamic Parameters Using a Self-Attention Convolutional Neural Network Z. Liang et al. 10.3390/rs15071887
- Southern Ocean sea ice concentration budgets of five ocean-sea ice reanalyses Y. Nie et al. 10.1007/s00382-022-06260-x
- The MET Norway Ice Service: a comprehensive review of the historical and future evolution, ice chart creation, and end user interaction within METAREA XIX W. Copeland et al. 10.3389/fmars.2024.1400479
- DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations H. Luo et al. 10.1017/jog.2021.57
- An evaluation of Antarctic sea-ice thickness from the Global Ice-Ocean Modeling and Assimilation System based on in situ and satellite observations S. Liao et al. 10.5194/tc-16-1807-2022
- Exploring sea ice transport dynamics at the eastern gate of the Ross Sea N. Krauzig et al. 10.1016/j.dsr2.2024.105428
- Optimized sea ice simulation in MITgcm-ECCO2 forced by ERA5 E. Gavilan Pascual-Ahuir & Z. Wang 10.1016/j.ocemod.2023.102183
- Evaluation of Antarctic sea ice thickness and volume during 2003–2014 in CMIP6 using Envisat and CryoSat-2 observations Y. Hou et al. 10.1088/1748-9326/ad1725
- The Impacts of Optimizing Model‐Dependent Parameters on the Antarctic Sea Ice Data Assimilation H. Luo et al. 10.1029/2023GL105690
- Effects of sea ice form drag on the polar oceans in the NEMO-LIM3 global ocean–sea ice model J. Sterlin et al. 10.1016/j.ocemod.2023.102227
Latest update: 30 Dec 2024
Short summary
The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are...
