Articles | Volume 20, issue 7
https://doi.org/10.5194/tc-20-3795-2026
© Author(s) 2026. 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-20-3795-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jul 2026
Research article |
| 08 Jul 2026
| 08 Jul 2026
Enhanced prediction skill of Antarctic sea ice through sea ice thickness assimilation
Nicholas Williams
CORRESPONDING AUTHOR
Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Yiguo Wang
Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
François Counillon
Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
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Akhilesh Sivaraman Nair, François Counillon, and Noel Keenlyside
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Short summary
This study investigates whether assimilating sea ice thickness observations into a global climate model can improve reanalysis and seasonal prediction skill of the Antarctic sea ice. We found that assimilation of sea ice thickness improves the representation of sea ice variability, especially in western Antarctica. We also show that initialisation of predictions with sea ice thickness data assimilation can improve forecasts of sea ice concentration, extent and thickness in summer and autumn.
This study investigates whether assimilating sea ice thickness observations into a global...
