Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part I. The leading forced mode of atmospheric circulation

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• 作者：XiaoJing Jia ; June-Yi Lee ; Hai Lin ; Andrea Alessandri ; Kyung-Ja Ha
• 关键词：Interdecadal?change ; Seasonal climate ; Leading mode ; Prediction skill ; El Nino and Southern Oscillation
• 刊名：Climate Dynamics
• 出版年：2014
• 出版时间：September 2014
• 年：2014
• 卷：43
• 期：5-6
• 页码：1595-1609
• 全文大小：2,207 KB
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• 作者单位：XiaoJing Jia (1) (2)
  June-Yi Lee (3)
  Hai Lin (4)
  Andrea Alessandri (5)
  Kyung-Ja Ha (3)
  
  1. Department of Earth Sciences, Zhejiang University, Hangzhou, China
  2. State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  3. Pusan National University, Busan, 609-735, Korea
  4. Atmospheric Numerical Weather Prediction Research, Environment Canada, Dorval, QC, Canada
  5. Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo, economico sostenibile, Rome, Italy
  
• ISSN：1432-0894

文摘

Using observations and 1-month lead hindcast data from six coupled atmosphere–ocean climate models, this study investigates the interdecadal change in the leading maximum covariance analysis mode (MCA1) of atmospheric circulation in response to the changes in the El Ni?o and Southern Oscillation (ENSO) occurred around late 1970s. We focus on boreal winter climate variability and predictability over the North Pacific–North American (NPNA) region using December–January–February prediction initiated from November 1st in the period of 1960-980 (P1) and 1981-001 (P2). Observed analysis reveals that ENSO variability, the related tropical convective activity, and thus the MCA1 are considerably enhanced from P1 to P2. As a result, surface climate anomalies over the NPNA are more significantly correlated with the MCA1 in P2 than P1, particularly over North America. The six coupled models and their multi-model ensemble not only are capable of capturing the interdecadal change of the MCA1 and its relationship with surface air temperature and precipitation over the NPNA regions but also have significantly higher forecast skills for the MCA1 and the surface climate anomalies in P2 than P1. However, models have systematic biases in the spatial distribution of the MCA1. It is demonstrated that the interdecadal change in the MCA1 should contribute to the improved forecast skill of the NPNA climate during recent epoch.