基于统计降尺度和SPI 的黄河流域干旱预测

基于黄河流域101个气象站点的实测气象数据和国际耦合模式比较计划第5阶段(coupled model intercomparison project phase 5,CMIP5)3种排放情景下的6个模型1961—2099年的降水和气温数据,采用等距离累积分布函数法(equidistant cumulative distribution function matching method,EDCDFm)进行统计降尺度;通过历史阶段(1961—2005年)实测站点数据对降尺度后的降水和气温进行精度评估;在此基础上,通过标准化降水指数(standardprecipitation index,SPI)对黄河流域气象干旱进行预估。结果表明,EDCDFm的降尺度方法能够明显提高气候模式所模拟的气温和降水精度,尤其对极值的模拟精度;黄河流域气象干旱的预估显示,3种气候情景下21世纪初的干旱情况相对于基准期均变得比较严重,但是世纪末的干旱程度均明显减轻,近期黄河流域的防旱工作形势仍然严峻。

Prediction of drought in the Yellow River based on statistical downscale study and SPI

Based on the measured data in 101 meteorological stations over the Yellow River Basin, and the precipitation and temperature data dating from 1961 to 2099 of the six CMIP5 models under three scenarias, statistical downscale study is conducted by using equidistant cumulative distribution function matching method (EDCDFm). The accuracy of the downscaled data is evaluated by validating against the measured data dating from 1961 to 2005. After that, the meteorological drought around the Yellow River Basin is predicted by means of standard precipitation index (SPI). The results show that the accuracy of the raw models simulated temperature and precipitation has been significantly improved by using EDCDFm method, it is especially true with the modelling accuracy of their extreme values. The predicted results of the drought around the Yellow River Basin indicate that, the drought condition at the beginning of the 21st century has become more severe than that of the reference period under three scenarios, but is likely to be obviously mitigated at the end of this century. Notwithstanding, preventing drought around the Yellow River Basin is still a tough job in recent years.