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Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems

Cited 58 time in Web of Science Cited 56 time in Scopus
Authors

Kang, Daehyun; Lee, Myong-In; Im, Jungho; Kim, Daehyun; Kim, Hye-Mi; Kang, Hyun-Suk; Schubert, Siegfried D.; Arribas, Alberto; MacLachlan, Craig

Issue Date
2014-05
Publisher
American Geophysical Union
Citation
Geophysical Research Letters, Vol.41 No.10, pp.3577-3585
Abstract
This study assesses the skill of boreal winter Arctic Oscillation (AO) predictions with state-of-the-art dynamical ensemble prediction systems (EPSs): GloSea4, CFSv2, GEOS-5, CanCM3, CanCM4, and CM2.1. Long-term reforecasts with the EPSs are used to evaluate how well they represent the AO and to assess the skill of both deterministic and probabilistic forecasts of the AO. The reforecasts reproduce the observed changes in the large-scale patterns of the Northern Hemispheric surface temperature, upper level wind, and precipitation associated with the different phases of the AO. The results demonstrate that most EPSs improve upon persistence skill scores for lead times up to 2months in boreal winter, suggesting some potential for skillful prediction of the AO and its associated climate anomalies at seasonal time scales. It is also found that the skill of AO forecasts during the recent period (1997-2010) is higher than that of the earlier period (1983-1996).© 2014. American Geophysical Union. All Rights Reserved.
ISSN
0094-8276
URI
https://hdl.handle.net/10371/201004
DOI
https://doi.org/10.1002/2014GL060011
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학

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