Climate Dynamics

, Volume 48, Issue 7–8, pp 2557–2568 | Cite as

How predictable is the winter extremely cold days over temperate East Asia?

  • Xiao Luo
  • Bin Wang


Skillful seasonal prediction of the number of extremely cold day (NECD) has considerable benefits for climate risk management and economic planning. Yet, predictability of NECD associated with East Asia winter monsoon remains largely unexplored. The present work estimates the NECD predictability in temperate East Asia (TEA, 30°–50°N, 110°–140°E) where the current dynamical models exhibit limited prediction skill. We show that about 50 % of the total variance of the NECD in TEA region is likely predictable, which is estimated by using a physics-based empirical (P-E) model with three consequential autumn predictors, i.e., developing El Niño/La Niña, Eurasian Arctic Ocean temperature anomalies, and geopotential height anomalies over northern and eastern Asia. We find that the barotropic geopotential height anomaly over Asia can persist from autumn to winter, thereby serving as a predictor for winter NECD. Further analysis reveals that the sources of the NECD predictability and the physical basis for prediction of NECD are essentially the same as those for prediction of winter mean temperature over the same region. This finding implies that forecasting seasonal mean temperature can provide useful information for prediction of extreme cold events. Interpretation of the lead–lag linkages between the three predictors and the predictand is provided for stimulating further studies.


Climate predictability Prediction of extremely cold events East Asia winter monsoon (EAWM) El Niño/La Niña Arctic Ocean temperature anomalies 



This work has been supported by the Atmosphere-Ocean Research Center sponsored by the Nanjing University of Information Science and Technology and University of Hawaii. BW acknowledges the support provided by National Research Foundation (NRF) of Korea through a Global Research Laboratory (GRL) grant of the Korean Ministry of Education, Science and Technology (MEST, #2011-0021927). The authors thank Dr. So-Young Yim for discussing EAWM prediction issues. This is the SOEST publication 9662, IPRC publication 1202, and ESMC publication 115.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Atmospheric SciencesNanjing UniversityNanjingChina
  2. 2.Department of Atmospheric Sciences and Atmosphere-Ocean Research CenterUniversity of Hawaii at ManoaHonoluluUSA
  3. 3.Earth System Modeling CenterNanjing University of Information Science and TechnologyNanjingChina

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