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TC | Volume 13, issue 4
The Cryosphere, 13, 1073–1088, 2019
https://doi.org/10.5194/tc-13-1073-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
The Cryosphere, 13, 1073–1088, 2019
https://doi.org/10.5194/tc-13-1073-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Apr 2019

Research article | 03 Apr 2019

Benchmark seasonal prediction skill estimates based on regional indices

John E. Walsh et al.
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Cited articles  
Agnew, T. A. and Howell, S.: Comparison of digitized Canadian ice charts and passive microwave sea-ice concentrations, Geoscience and Remote Sensing Symposium, 24–28 June 2002, Toronto, Ontario, Canada, IGARSS '02. 2002 IEEE International, 1, 231–233, https://doi.org/10.1109/IGARSS.2002.1024996, 2002. 
AMAP: Snow, Water, Ice and Permafrost in the Arctic: 2017 Update. Arctic Monitoring and Assessment Programme, Oslo, Norway, xiv + 269 pp., 2017. 
Barnett, D. G.: A long-range ice forecasting method for the north coast of Alaska, Sea Ice Processes and Models, edited by: Pritchard, R., University of Washington Press, Seattle, WA, USA, 402–409, 1980. 
Blanchard-Wrigglesworth, E., Armour, K. C., and Bitz, C. M.: Persistence and inherent predictability of Arctic sea ice in a GCM ensemble and observations, J. Climate, 24, 231–250, 2011. 
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Short summary
Persistence-based statistical forecasts of a Beaufort Sea ice severity index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the trends are removed from the data. This finding is consistent with the notion of a springtime “predictability barrier” that has been found in sea ice forecasts based on more sophisticated methods.
Persistence-based statistical forecasts of a Beaufort Sea ice severity index as well as...
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