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


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

DC Field Value Language Kang, Daehyun ko Lee, Myong-In ko Im, Jungho ko Kim, Daehyun ko Kim, Hye-Mi ko Kang, Hyun-Suk ko Schubert, Siegfried D. ko Arribas, Alberto ko Maclachlan, Craig ko 2014-06-09T02:37:36Z - 2014-06-09 ko 2014-05 ko
dc.identifier.citation GEOPHYSICAL RESEARCH LETTERS, v.41, no.10, pp.3577 - 3585 ko
dc.identifier.issn 0094-8276 ko
dc.identifier.uri -
dc.description.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). ko
dc.description.statementofresponsibility close -
dc.language 영어 ko
dc.title Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84901182378 ko
dc.identifier.wosid 000337610200035 ko
dc.type.rims ART ko
dc.description.wostc 1 *
dc.description.scopustc 0 * 2015-05-06 * 2014-06-09 *
dc.identifier.doi 10.1002/2014GL060011 ko
dc.identifier.url ko
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