4.6 Article

Predictable and unpredictable modes of seasonal mean precipitation over Northeast China

期刊

CLIMATE DYNAMICS
卷 50, 期 7-8, 页码 3081-3095

出版社

SPRINGER
DOI: 10.1007/s00382-017-3795-6

关键词

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

资金

  1. National Key R&D Program of China [2016YFA0600402]
  2. National Natural Science Foundation of China [91325108, 91425304, 41675094, 41605066, 41405090]

向作者/读者索取更多资源

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.

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