Climate Dynamics

, Volume 50, Issue 7–8, pp 3081–3095 | Cite as

Predictable and unpredictable modes of seasonal mean precipitation over Northeast China

Article

Abstract

This study investigates the patterns of interannual variability that arise from the potentially predictable (slow) and unpredictable (intraseasonal) components of seasonal mean precipitation over Northeast (NE) China, using observations from a network of 162 meteorological stations for the period 1961–2014. A variance decomposition method is applied to identify the sources of predictability, as well as the sources of prediction uncertainty, for January–February–March (JFM), April–May–June (AMJ), July–August–September (JAS) and October–November–December (OND). The averaged potential predictability (ratio of slow to total variance) of NE China precipitation has the highest value of 0.32 during JAS and lowest value of 0.1 in AMJ. Possible sources of seasonal prediction for the leading predictable precipitation EOF modes come from the SST anomalies in the Japan Sea, as well as the North Atlantic during JFM, the Indian Ocean SST in AMJ, and the eastern tropical Pacific SST in JAS and OND. The prolonged linear trend, which is seen in the principal component time series of the leading predictable mode in JFM and OND, may also serve as a source of predictability. The Polar–Eurasia and Northern Annular Mode atmospheric teleconnection patterns are closely connected with the leading and the second predictable mode of JAS, respectively. The Hadley cell circulation is closely related to the leading predictable mode of OND. The leading/second unpredictable precipitation modes for all these four seasons show a similar monopole/dipole structure, and can be largely attributed to the intraseasonal variabilities of the atmosphere.

Keywords

Predictable signal Unpredictable noise Atlantic SST Indian Ocean SST ENSO Atmospheric teleconnection 

Notes

Acknowledgements

We gratefully acknowledge the two anonymous reviewers for their constructive comments, which helped greatly in improving the quality of this manuscript. This work was done during the visit of KY in the School of Earth, Atmosphere and Environment, Monash University. The work was supported by the National Key R&D Program of China (2016YFA0600402) and National Natural Science Foundation of China (91325108, 91425304, 41675094, 41605066 and 41405090).

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Kairan Ying
    • 1
  • Carsten S. Frederiksen
    • 2
    • 3
  • Tianbao Zhao
    • 1
  • Xiaogu Zheng
    • 1
  • Zhe Xiong
    • 1
  • Xue Yi
    • 4
  • Chunxiang Li
    • 1
  1. 1.CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.The Bureau of MeteorologyMelbourneAustralia
  3. 3.The School of Earth, Atmosphere and EnvironmentMonash UniversityClaytonAustralia
  4. 4.Regional Climate Center of ShenyangShenyangChina

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