Acta Geographica Sinica ›› 2014, Vol. 69 ›› Issue (5): 640-649.doi: 10.11821/dlxb201405007

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Changes in precipitation extremes in South China during 1961-2011

REN Zhengguo, ZHANG Mingjun, WANG Shengjie, ZHU Xiaofan, DONG Lei, QIANG Fang   

  1. College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
  • Received:2014-01-15 Revised:2014-04-02 Online:2014-05-20 Published:2014-05-20
  • Supported by:
    National Basic Research Program of China(973Program), No.2013CBA01801;National Natural Science Foundation of China, No.41161012;The BasicScientific Research Foundation in University of Gansu

Abstract: Based on the daily precipitation from a 0.5° × 0.5° gridded dataset and meteorological stations during 1961-2011 released by National Meteorological Information Center, this paper evaluates the reliability of this gridded precipitation dataset in South China. Five precipitation indices recommended by the World Meteorological Organization (WMO) were selected to investigate the changes in precipitation extremes in South China. The results indicate that the limited bias was observed between gridded data interpolated to given stations and the corresponding observed data, and that 50.64% of the stations had bias between -10% and 0. Generally, the correlation coefficients between gridded data and observed data are above 0.80 in most parts of the region. The average of precipitation indices shows a significant spatial difference with drier northwest section and wetter southeast section. The trend magnitudes of maximum 5-day precipitation (RX5day), very wet day precipitation (R95), very heavy precipitation days (R20mm) and simple daily intensity index (SDII) were 0.17 mm·a-1, 1.14 mm·a-1, 0.02 d·a-1 and 0.01 mm·d·a-1, respectively, while consecutive wet days (CWD) decreased by -0.05 d·a-1 during 1961-2011. There is spatial disparity in trend magnitudes of precipitation indices, and approximate 60.85%, 75.32% and 75.74% of the grid boxes showed increasing trends for RX5day, SDII and R95, respectively. There were high correlations between precipitation indices and total precipitation, which was statistically significant at the 0.01 level.

Key words: gridded data, precipitation extremes, South China