Articles | Volume 10, issue 5
https://doi.org/10.5194/tc-10-2429-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-10-2429-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Oct 2016
Research article |
| 21 Oct 2016
Assessment of Arctic and Antarctic sea ice predictability in CMIP5 decadal hindcasts
Chao-Yuan Yang
CORRESPONDING AUTHOR
Department of Atmospheric and Environmental Sciences, University at
Albany, State University of New York, Albany, NY, USA
Jiping Liu
Department of Atmospheric and Environmental Sciences, University at
Albany, State University of New York, Albany, NY, USA
Yongyun Hu
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing, China
Radley M. Horton
Columbia University Center for Climate Systems Research and NASA
Goddard Institute for Space Studies, New York, NY, USA
Liqi Chen
Key Laboratory of Global Change and Marine-Atmospheric Chemistry,
Third Institute of Oceanography, SOA, Xiamen, China
Xiao Cheng
College of Global Change and Earth System Science, Beijing Normal
University, Beijing, China
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Cited
17 citations as recorded by crossref.
- Assessment of Antarctic Sea Ice Cover in CMIP6 Prediction with Comparison to AMSR2 during 2015–2021 S. Li et al. 10.3390/rs15082048
- Seasonal Arctic Sea Ice Prediction Using a Newly Developed Fully Coupled Regional Model With the Assimilation of Satellite Sea Ice Observations C. Yang et al. 10.1029/2019MS001938
- Remote and Local Processes Controlling Decadal Sea Ice Variability in the Weddell Sea Y. Morioka & S. Behera 10.1029/2020JC017036
- Decadal oscillation provides skillful multiyear predictions of Antarctic sea ice Y. Liu et al. 10.1038/s41467-023-44094-1
- Processes Controlling Arctic and Antarctic Sea Ice Predictability in the Community Earth System Model A. Ordoñez et al. 10.1175/JCLI-D-18-0348.1
- An Assessment of the Antarctic Sea Ice Mass Budget Simulation in CMIP6 Historical Experiment S. Li et al. 10.3389/feart.2021.649743
- Multidecadal variability and predictability of Antarctic sea ice in the GFDL SPEAR_LO model Y. Morioka et al. 10.5194/tc-17-5219-2023
- Partitioning uncertainty in projections of Arctic sea ice D. Bonan et al. 10.1088/1748-9326/abe0ec
- Ocean‐Sea Ice Processes and Their Role in Multi‐Month Predictability of Antarctic Sea Ice S. Libera et al. 10.1029/2021GL097047
- Ross–Weddell Dipole Critical for Antarctic Sea Ice Predictability in MPI–ESM–HR D. Zanchettin et al. 10.3390/atmos15030295
- The mechanism linking the variability of the Antarctic sea ice extent in the Indian Ocean sector to Indian summer monsoon rainfall S. Azhar et al. 10.1007/s00382-022-06466-z
- Towards reliable Arctic sea ice prediction using multivariate data assimilation J. Liu et al. 10.1016/j.scib.2018.11.018
- Decadal Sea Ice Prediction in the West Antarctic Seas with Ocean and Sea Ice Initializations Y. Morioka et al. 10.1038/s43247-022-00529-z
- Quantifying predictability of sea ice around the Indian Antarctic stations using coupled ocean sea ice model with shelf ice A. Kumar et al. 10.1016/j.polar.2018.04.003
- Pacific Ocean Variability Influences the Time of Emergence of a Seasonally Ice‐Free Arctic Ocean J. Screen & C. Deser 10.1029/2018GL081393
- Reemergence of Antarctic sea ice predictability and its link to deep ocean mixing in global climate models S. Marchi et al. 10.1007/s00382-018-4292-2
- Major Contribution of Reduced Upper Ocean Oxygen Mixing to Global Ocean Deoxygenation in an Earth System Model D. Couespel et al. 10.1029/2019GL084162
17 citations as recorded by crossref.
- Assessment of Antarctic Sea Ice Cover in CMIP6 Prediction with Comparison to AMSR2 during 2015–2021 S. Li et al. 10.3390/rs15082048
- Seasonal Arctic Sea Ice Prediction Using a Newly Developed Fully Coupled Regional Model With the Assimilation of Satellite Sea Ice Observations C. Yang et al. 10.1029/2019MS001938
- Remote and Local Processes Controlling Decadal Sea Ice Variability in the Weddell Sea Y. Morioka & S. Behera 10.1029/2020JC017036
- Decadal oscillation provides skillful multiyear predictions of Antarctic sea ice Y. Liu et al. 10.1038/s41467-023-44094-1
- Processes Controlling Arctic and Antarctic Sea Ice Predictability in the Community Earth System Model A. Ordoñez et al. 10.1175/JCLI-D-18-0348.1
- An Assessment of the Antarctic Sea Ice Mass Budget Simulation in CMIP6 Historical Experiment S. Li et al. 10.3389/feart.2021.649743
- Multidecadal variability and predictability of Antarctic sea ice in the GFDL SPEAR_LO model Y. Morioka et al. 10.5194/tc-17-5219-2023
- Partitioning uncertainty in projections of Arctic sea ice D. Bonan et al. 10.1088/1748-9326/abe0ec
- Ocean‐Sea Ice Processes and Their Role in Multi‐Month Predictability of Antarctic Sea Ice S. Libera et al. 10.1029/2021GL097047
- Ross–Weddell Dipole Critical for Antarctic Sea Ice Predictability in MPI–ESM–HR D. Zanchettin et al. 10.3390/atmos15030295
- The mechanism linking the variability of the Antarctic sea ice extent in the Indian Ocean sector to Indian summer monsoon rainfall S. Azhar et al. 10.1007/s00382-022-06466-z
- Towards reliable Arctic sea ice prediction using multivariate data assimilation J. Liu et al. 10.1016/j.scib.2018.11.018
- Decadal Sea Ice Prediction in the West Antarctic Seas with Ocean and Sea Ice Initializations Y. Morioka et al. 10.1038/s43247-022-00529-z
- Quantifying predictability of sea ice around the Indian Antarctic stations using coupled ocean sea ice model with shelf ice A. Kumar et al. 10.1016/j.polar.2018.04.003
- Pacific Ocean Variability Influences the Time of Emergence of a Seasonally Ice‐Free Arctic Ocean J. Screen & C. Deser 10.1029/2018GL081393
- Reemergence of Antarctic sea ice predictability and its link to deep ocean mixing in global climate models S. Marchi et al. 10.1007/s00382-018-4292-2
- Major Contribution of Reduced Upper Ocean Oxygen Mixing to Global Ocean Deoxygenation in an Earth System Model D. Couespel et al. 10.1029/2019GL084162
Saved (preprint)
Latest update: 25 Apr 2024
Short summary
The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales.
The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that...
