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Author

Lee, Myong-In
Climate-Environment Modeling Lab
Research Interests
  • Climate Change, Seasonal Prediction, Extreme Weather, Aerosol

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

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Title
Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems
Author
Kang, DaehyunLee, Myong-InIm, JunghoKim, DaehyunKim, Hye-MiKang, Hyun-SukSchubert, Siegfried D.Arribas, AlbertoMaclachlan, Craig
Keywords
Climate variability; Coupled models of the climate system
Issue Date
201405
Publisher
AMER GEOPHYSICAL UNION
Citation
GEOPHYSICAL RESEARCH LETTERS, v.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).
URI
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DOI
http://dx.doi.org/10.1002/2014GL060011
ISSN
0094-8276
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