多模式下泾河上游流域未来降水变化预估

Projection of future precipitation changes in upper Jinghe River basin usingmultiple models

利用站点实测资料、GCMs月数据对GCMs进行秩评分评估排序,从21种GCMs模式优选出的6种GCM模式的日数据、6种GCM集成的气候模式、站点实测资料和NCEP再分析资料构建统计降尺度模型SDSM,预估泾河上游流域的未来降水变化。结果表明:构建的降尺度模型对降水模拟较为可靠,率定期各模式决定系数R2为0.228~0.324,标准误差为0.354~0.450,率定期和验证期模拟月均降水与实测值年内分布相近。在降尺度性能评价中集成模式表现最好。在RCP 4.5情景下,泾河上游流域未来降水大多数模式和集成模式呈增加趋势,到2030年泾河上游流域降水量将增加4.8%,且当地的春季雨量会增加,夏季雨量会减少。

The prediction of precipitation changes in the future can provide a basis for research on water resource changes in the upper Jinghe River basin.The GCMs are ranked according to the site measured data and monthly GCMs data.The statistical downscaling model SDSM is constructed based on daily data of 6 GCM models selected from 21 GCMs,the climate models integrated by 6 GCMs,in situ stations data,and NCEP reanalysis data,to predict the future precipitation change in the upper reaches of Jinghe River.The results show that the SDSM is reliable for precipitation simulation.The R2 of each model is between 0.228 and 0.324,the standard error is between 0.354 and 0.450,respectively.The simulated monthly average precipitation in the periodic and verification periods is similar to the measured value and the distribution is similar within a year.The integrated model performs best in the downscaling performance evaluation period.Under the RCP 4.5 scenario,most future precipitation models and integrated models in the upper Jinghe River show an increasing trend.By the 2030 s,precipitation in the upper Jinghe River may increase by4.8%,and local rainfall in spring also exhibits an increasing trend,and summer rainfall may decrease.