基于1951-2010年英国东英吉利大学(East Anglia)气候研究中心降水资料来检验第六次国际耦合模式比较计划(Commentary on the Coupled Model Intercomparison Project Phase 6,CMIP6)模式资料中22套模式降水资料对中亚地区年平均降水的模拟能力,并挑选最优的一批模式资料来预估中亚未来降水的时空分布特征.结果表明:在2021-2060年不同排放情景下,多模式集合平均与历史值之差的降水气候态分布与1951-2010年间降水气候态分布特征明显不同,而均方差的分布特征基本相似,在春季和冬季,中亚未来降水趋势均体现出北部降水增长,南部降水减少的分布特征.未来中亚春季和冬季平均降水量在大部分地区始终出现变多趋势,不同排放情景下预估降水长期趋势变化的结果表明,中亚春季和冬季整体降水增长或减少趋势的强度均大于以往降水变化的强度.
Prediction of the Spatio-Temporal Variation Characteristics of Precipitation in Central Asia Based on the CMIP6 Model
Based on precipitation data from the Climate Research Unit of University of East Anglia in the UK from 1951 to 2010,this study examines the simulation ability of the precipitation data of 22 sets of model in CMIP6 model data on annual average precipitation in Central Asia,and selects the optimal batch of model data to predict the spatio-temporal distribution characteristics of precipitation in Central Asia in the future.The results show that under different emission scenarios from 2021 to 2060,the distribution characteristics of precipitation climate patterns with the difference between the average and historical values of the multimodal set are significantly different from those from 1951 to 2010,the distribution characteristics of mean square errors are basically similar,and that in spring and winter,the precipitation trend in Central Asia in the future shows the distribution characteristics of increasing precipitation in the north and decreasing precipitation in the south.In the future,the average precipitation in spring and winter in Central Asia will always show an increasing trend in most regions,and the results of predicting the long-term trend change of precipitation under different emission scenarios indicate that the intensity of the overall increase or decrease trend of precipitation in Central Asia in spring and winter is greater than that of previous pre-cipitation changes.
Central AsiaPrecipitationSpatial and temporal variationPrediction
NETL
NSTL
万方数据
维普
