Climate Dynamics

, Volume 48, Issue 1–2, pp 209–224 | Cite as

The statistical extended-range (10–30-day) forecast of summer rainfall anomalies over the entire China

  • Zhiwei Zhu
  • Tim Li


The extended-range (10–30-day) rainfall forecast over the entire China was carried out using spatial–temporal projection models (STPMs). Using a rotated empirical orthogonal function analysis of intraseasonal (10–80-day) rainfall anomalies, China is divided into ten sub-regions. Different predictability sources were selected for each of the ten regions. The forecast skills are ranked for each region. Based on temporal correlation coefficient (TCC) and Gerrity skill score, useful skills are found for most parts of China at a 20–25-day lead. The southern China and the mid-lower reaches of Yangtze River Valley show the highest predictive skills, whereas southwestern China and Huang-Huai region have the lowest predictive skills. By combining forecast results from ten regional STPMs, the TCC distribution of 8-year (2003–2010) independent forecast for the entire China is investigated. The combined forecast results from ten STPMs show significantly higher skills than the forecast with just one single STPM for the entire China. Independent forecast examples of summer rainfall anomalies around the period of Beijing Olympic Games in 2008 and Shanghai World Expo in 2010 are presented. The result shows that the current model is able to reproduce the gross pattern of the summer intraseasonal rainfall over China at a 20-day lead. The present study provides, for the first time, a guide on the statistical extended-range forecast of summer rainfall anomalies for the entire China. It is anticipated that the ideas and methods proposed here will facilitate the extended-range forecast in China.


Extended-range forecast Summer rainfall anomalies over China Spatial–temporal projection model Intraseasonal oscillation 



The authors thank two anonymous reviewers for their constructive comments and suggestions. This work was supported by China National 973 Project 2015CB453200, NSFC Grant 41475084, ONR Grant N00014-1210450, Jiangsu Shuang-Chuang Team, the priority academic program development of Jiangsu Higher Education institutions (PAPD), and Jiangsu NSF Key Project BK20150062. This is SOEST Contribution Number 9590, IPRC Contribution Number 1172 and ESMC Contribution Number 092.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and TechnologyNanjingChina
  2. 2.Department of Atmospheric Sciences, International Pacific Research Center, SOESTUniversity of Hawaii at ManoaHonoluluUSA

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