Journal of Meteorological Research

, Volume 31, Issue 6, pp 1096–1108 | Cite as

Detecting primary precursors of January surface air temperature anomalies in China

  • Guirong Tan
  • Hong-Li Ren
  • Haishan Chen
  • Qinglong You
Regular Articles


This study aims to detect the primary precursors and impact mechanisms for January surface temperature anomaly (JSTA) events in China against the background of global warming, by comparing the causes of two extreme JSTA events occurring in 2008 and 2011 with the common mechanisms inferred from all typical episodes during 1979–2008. The results show that these two extreme events exhibit atmospheric circulation patterns in the mid–high latitudes of Eurasia, with a positive anomaly center over the Ural Mountains and a negative one to the south of Lake Baikal (UMLB), which is a pattern quite similar to that for all the typical events. However, the Eurasian teleconnection patterns in the 2011 event, which are accompanied by a negative phase of the North Atlantic Oscillation, are different to those of the typical events and the 2008 event. We further find that a common anomalous signal appearing in early summer over the tropical Indian Ocean may be responsible for the following late-winter Eurasian teleconnections and the associated JSTA events in China. We show that sea surface temperature anomalies (SSTAs) in the preceding summer over the western Indian Ocean (WIO) are intimately related to the UMLB-like circulation pattern in the following January. Positive WIOSSTAs in early summer tend to induce strong UMLB-like circulation anomalies in January, which may result in anomalously or extremely cold events in China, which can also be successfully reproduced in model experiments. Our results suggest that the WIOSSTAs may be a useful precursor for predicting JSTA events in China.


Eurasian teleconnection anomalous temperature in China seasonal climate prediction SST anomaly western Indian Ocean model experiment 


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The authors thank Weitao Deng and Xing Geng for their help in running the model experiments and drawing some charts.


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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Guirong Tan
    • 1
  • Hong-Li Ren
    • 2
    • 3
  • Haishan Chen
    • 1
  • Qinglong You
    • 1
  1. 1.Key Laboratory of Meteorological Disaster of Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science & TechnologyNanjingChina
  2. 2.Laboratory for Climate Studies/CMA–NJU Joint Laboratory for Climate Prediction Studies, National Climate CenterChina Meteorological AdministrationBeijingChina
  3. 3.Department of Atmospheric Science, School of Environmental StudiesChina University of GeoscienceWuhanChina

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