Articles | Volume 16, issue 3
The Cryosphere, 16, 1141–1156, 2022
The Cryosphere, 16, 1141–1156, 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 et al.

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Cited articles

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Blanchard-Wrigglesworth, E., Armour, K. C., Bitz, C. M., and DeWeaver, E.: Persistence and Inherent Predictability of Arctic Sea Ice in a GCM Ensemble and Observations, J. Climate, 24, 231–250,, 2011. 
Blanchard-Wrigglesworth, E., Cullather, R., Wang, W., Zhang, J., and Bitz, C.: Model forecast skill and sensitivity to initial conditions in the seasonal Sea Ice Outlook, Geophys. Res. Lett., 42, 8042–8048,, 2015. 
Blockley, E. W. and Peterson, K. A.: Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness, The Cryosphere, 12, 3419–3438,, 2018. 
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.