利用1951—2000年中国160个气象站的降水资料和美国GFDL-CM2.1模式输出的500 hPa位势高度资料， 建立了一个统计降尺度模型， 并利用该模型对中国2011—2100年的降水进行了降尺度预估， 分析了CO2浓度变化对中国未来降水变化的可能影响。结果表明， 在未来A1B和A2情景下， 中国各气候区各季节的降水都发生了变化, 两种情景下的降水变化格局和变化幅度非常相似， 但由于A2情景下的2011—2100年平均CO2浓度比A1B情景高， 故其降水变化的幅度更为剧烈。CO2浓度的增加是中国未来降水变化的主要贡献因子， 但它不会从根本上改变中国未来降水的分布格局， 只会增强降水本身的自然变化幅度， 是降水自然变率的放大器， 且放大的幅度远远大于自然变率本身。CO2浓度变化引起的降水变化一般比CO2浓度变化滞后20～30年。CO2浓度增加引起的气温升高会导致中国大部分地区500 hPa等压面的抬升和环流形势的改变， 从而对未来降水产生影响。
The monthly rainfall data at 16 stations in China and 500 hPa geopotential height derived from GFDL-CM2.1 model were used to construct a statistical downscaling model. The precipitation China for 2011-2100 are predicted through this downscaling model. The impossible influence of the CO2 concentration variation on the precipitation in the future of China are analyzed. The results show that the precipitation of all regions and all seasons in China change in SRES A1B and SRES A2. The distribution of precipitation variation in SRES A1B are similar with that in SRES A2. However, the amplitudes of precipitation variation in SRES A2 are larger than that in SRES A1B, because the CO2 concentration in SRES A2 is higher than that in SRES A1B. The increase of CO2 concentration is the key factor contributing to the precipitation variation in China. Though the increase of CO2 concentration could not change the distribution of precipitation fundamentally, which intensify the natural variation amplitude of the climatic variables. It is the amplifier of the climatic nature variation. The variation of precipitation lags the variation of CO2 concentration about 20～30 years. The higher temperature result from the increase of the CO2 concentration leads to the lift of 500 hPa isobaric layer and the variation of atmospheric circulation, which further exerts impacts on the variation of precipitation in the future.
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