统计降尺度方法对黄河上游流域气象要素模拟分析

将CMIP5模式的输出作为降尺度的输入来预估区域性气候的研究较少,本文使用CMIP5中精度较高的Can ESM2模式下的RCP4.5情景(中等温室气体排放)对黄河上游流域未来气象要素进行预估。利用黄河上游流域(上诠站以上)14个气象站点1967-2010年的逐月降水、气温和NCEP再分析资料,选取拟合度、均值相对误差、标准差相对误差作为评价指标,利用逐步回归算法筛选22个预报因子,建立了月资料序列的统计降尺度模型,并将模型应用于CMIP5中Can ESM2模式下RCP4.5情景,产生了未来气候要素的变化情景。结果表明:该模型对降水的模拟效果好于对气温的模拟。

Simulation analysis of meteorological element by statistical downscaling method in Yellow River basin

The research on taking output of CMIP5 mode as input of downscaling to forecast regional climate conducts less, so this article used the CMIP5 RCP4.5 CanESM2 mode with higher accuracy in the scene (moderate greenhouse gas emissions) to forecast the meteorological elements in the future of Yellow River. By using the Yellow River (on the interpretation of stand above) 14 weather stations from 1967 to 2010 of monthly precipitation, temperature and NCEP reanalysis data, it chose the fit, mean relative error and relative standard deviation error as the evaluation index,used stepwise regression algorithm to screen 22 predictors and establish monthly data sequence statistical downscaling model .The model was applied to RCP4.5 under CanESM2 mode of CMIP5, which produced the change scenarios of future climate factors.The results show that simulation effect of the model on precipitation is better than that on temperature.