Different prediction skill for the East Asian winter monsoon in the early and late winter season

  • Baoqiang Tian
  • Ke FanEmail author


The prediction skill for the East Asian winter monsoon (EAWM) in early (November–December, ND) and late winter (January–February, JF) is investigated based on the NCEP’s Climate Forecast System, version 2 (CFSv2), at different lead months. Results show that the prediction skill of ND-EAWM is higher than that of JF-EAWM. ND-EAWM can be reasonably reproduced by CFSv2 with initial conditions from the previous May to November, whereas with initial conditions from the previous July to January it has little forecasting skill for predicting JF-EAWM. The difference in the impacts of ENSO between early and late winter may influence the ENSO–EAWM relationship and cause the subseasonal change. As the seasonality of the ENSO cycle changes from early winter to late winter, the anomalous tropical east–west Walker circulation system shifts from a double-cell to a single-cell regime. The double-cell regime in early winter is usually accompanied by intense tropical convection localized in the Maritime Continent. ENSO-related anomalous convection strongly influences the EAWM through a systematic wave train pattern. However, ENSO cannot easily influence the EAWM in late winter through this process when the turnabout of ENSO commences in late winter. CFSv2 can successfully reproduce this physical process of ENSO affecting the EAWM in early winter. It is also found that the year-to-year increment approach may enhance the skill of CFSv2 in predicting the EAWM in late winter.


Prediction skill Early and late winter East Asian winter monsoon Subseasonal ENSO-EAWM relation CFSv2 Year-to-year increment prediction 



The authors thank Executive Editor Jian Lu and three anonymous reviewers for their constructive suggestions and comments, which helped to improve the paper. This research was jointly supported by the National Natural Science Foundation of China (Grants 41730964, 41575079 and 41421004).


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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Nansen-Zhu International Research Centre, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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