›› 2013, Vol. 23 ›› Issue (4): 579-594.doi: 10.1007/s11442-013-1030-x

• Research Articles •     Next Articles

Change of parameters of BCC/RCG-WG for daily non-precipitation variables in China:1951-1978 and 1979-2007

LIAO Yaoming   

  1. 1. Laboratory for Climate Studies/National Climate Center, CMA, Beijing 100081, China;
    2. State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Geography, Beijing Normal University, Beijing 100875, China
  • Received:2012-12-26 Revised:2013-03-19 Online:2013-08-15
  • About author:Liao Yaoming (1972-), Ph.D and Senior Engineer, specialized in statistical downscaling and assessment of climate impact. E-mail: lymzxr@cma.gov.cn
  • Supported by:

    The Special Scientific Research Fund of Meteorological Public Welfare Profession of China, No.GYHY201106018;The Swedish Foundation for International Cooperation in Research and High Education

Abstract:

Parameters of weather generator BCC/RCG-WG for daily non-precipitation variables including maximum temperature, minimum temperature and sunshine hours at 669 stations in China are estimated using history daily records from 1951 to 1978 and from 1979 to 2007 respectively. The changes in the parameters for the two periods are revealed to explore the impact of climate change on these parameters. The results show that the parameters of the non-precipitation variables have experienced different changes. While the annual means and the amplitudes of the seasonal cycle show a clear change, the interannual variability, the timings of the seasonal cycles, and the temporal correlations for each variable remain practically unchanged. This indicates that climate changes in China over the last 57 years are mainly reflected in variations in the means and in the strength of the seasonal cycles. The changed parameters have implications for the stationary assumption implied in the parameter estimation and use of the weather generator for climate change studies.

Key words: BCC/RCG-WG weather generator, daily non-precipitation variables, climate change, parameters, China