为更精确的为区域气候模拟和预估研究提供参考，开展了基于累积分布函数的统计降尺度模型校验，在传统统计降尺度模型的基础上，使用基于累积分布函数的校验方法校正了 SDSM模型预估的A2和B2情景下中国265个站点1961～2099年逐日温度数据，校正后A2情景下，观测值和模拟值R2达到0．9999以上的比例占到85％，达到1的占6％；B2情景下，观测值和模拟值R2达到0．9999以上的比例占到87％，达到1的占19％；斜率值接近1的站点分别增加了57％和51％；截距接近0的站点分别增加了31％和16％。校正后的模型能更好地预估出未来逐年稳定通过0℃的日期，也即生长季开始的日期。%Abstrac:t For more accurate regional climate prediction to provide the reference, Carried out statistical downscaling model validation based on the cumulative distribution functions ( CDFs) , on the basis of traditional statistical downscaling model, using the SDSM based on the cumulative distribution functions model calibration predicted the daily temperature at 265 sites under the A2and B 2 scenarios from 1961 to 2099 in China.The result showed that the proportion of observation and simulation value R2 was above 0.9999 accounted for 85%under A2 scenarios after correction, R2 was 1 accounted for 6%;the proportion of observation and simulation value R2 was above 0.9999 accounted for 87%under B2 scenarios after correction, R2 was 1 accounted for 19%;The sites of the slope value close to 1 increased by 57%and 51%respectively;The sites of the intercept is close to 0 increased by 31%and 16%respectively.The model after correction could better predict steadily through the date of the 0℃in future( the ac-curate date of the beginning of the growing season) .
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