Articles | Volume 19, issue 8
https://doi.org/10.5194/tc-19-3279-2025
https://doi.org/10.5194/tc-19-3279-2025
Research article
 | 
26 Aug 2025
Research article |  | 26 Aug 2025

Correcting errors in seasonal Arctic sea ice prediction of Earth system models with machine learning

Zikang He, Yiguo Wang, Julien Brajard, Xidong Wang, and Zheqi Shen

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Short summary
Declining Arctic sea ice presents both risks and opportunities for ecosystems, communities, and economic activities. To address prediction errors in dynamical models, we apply machine learning for error correction during prediction (online) or post-processing (offline). Our results show that both methods enhance sea ice predictions, particularly from September to January, with offline corrections outperforming online corrections.
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