The Cryosphere
The Cryosphere
The Cryosphere
Articles | Volume 16, issue 3
Articles | Volume 16, issue 3
The Cryosphere, 16, 1141–1156, 2022
https://doi.org/10.5194/tc-16-1141-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
The Cryosphere, 16, 1141–1156, 2022
https://doi.org/10.5194/tc-16-1141-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 3
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.

Viewed

Total article views: 973 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
771 174 28 973 60 16 16
  • HTML: 771
  • PDF: 174
  • XML: 28
  • Total: 973
  • Supplement: 60
  • BibTeX: 16
  • EndNote: 16
Views and downloads (calculated since 21 Sep 2021)
Cumulative views and downloads (calculated since 21 Sep 2021)

Viewed (geographical distribution)

Total article views: 943 (including HTML, PDF, and XML) Thereof 943 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Jul 2022
Download
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.
Read more