Articles | Volume 16, issue 3
https://doi.org/10.5194/tc-16-1141-2022
https://doi.org/10.5194/tc-16-1141-2022
Research article
 | 
01 Apr 2022
Research article |  | 01 Apr 2022

Reassessing seasonal sea ice predictability of the Pacific-Arctic sector using a Markov model

Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang

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Latest update: 09 Dec 2023
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Short summary
We develop a regional linear Markov model consisting of four modules with seasonally dependent variables in the Pacific sector. The model retains skill for detrended sea ice extent predictions for up to 7-month lead times in the Bering Sea and the Sea of Okhotsk. The prediction skill, as measured by the percentage of grid points with significant correlations (PGS), increased by 75 % in the Bering Sea and 16 % in the Sea of Okhotsk relative to the earlier pan-Arctic model.