Climate prediction

2009 CMA Chief Forecaster

Sept.1982-Jul.1986   B.S. in dynamic meteorology, Peking University, China
Sept.2002-Dec.2006  M.S.in meteorology, Peking University, China

Jul.1986-Sept.1989 Assistant Engineer in weather forecasting, Beijing Meteorological Center
Oct.1989-Dec.1994 Engineer in long-range weather forecasting, National Meteorological Center of China
Jan.1995-Oct.2005    Senior Engineer in climate prediction, National Climate Center of China
Nov.2005-Present Professor in climate prediction, National Climate Center, China Meteorological Administration

1. “China’s short-term climate prediction system”, a project supported by the National Key Technology Research and Development Program during the 9th FYP period.
2. A project supported by the National Science and Technology Support Program during the 11th FYP period (2009BAC51B00).
3. A project supported by the National Key Research and Development Program (2010CB428401).
4. A project supported by the National Key Research and Development Program (2017YFA0603701).

1. Wang Yongguang, and Liao Quansun (1997). “A forecasting method for July precipitation in China.” Meteorological Monthly, 23 (3), 50-54.
2. Wang Yongguang (2002). “The influences of changing normals upon climate operation of China.” Meteorological Monthly, 28 (8), 41-43.
3. Wang Yongguang, Zhou Zijiang, Zhang Qiang, et al. (2008). “Main meteorological disasters and their impacts on the economic and societal development in China.” International Journal of Risk Assessment and Management, 8 (4), 384-394.
4. Yang Xiaobo, Wang Yongguang, and Liang Xiaoyun (2011). “The patterns of anomalous climate and their pre-circulation signals in November.” Journal of Applied Meteorological Science,22 (3), 275-282.
5. Hu Yamin, Wang Yongguang, Wang Juanhuai, et al. (2017). “Precursor signal analysis and prediction for the landfall typhoon intensity over South China.” Meteorological Monthly, 43 (10),1278-1286.
6. Wang Yongguang, and Zheng Zhihai (2018). “Precursor signal analysis of summer rainfall prediction in China in 2017.” Meteorological Monthly, 44 (4), 565-571.