Projection of future precipitation changes in upper Jinghe River basin using multiple models
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Abstract:
The prediction of precipitation changes in the future can provide a basis for research on water resource changes in the upper Jinghe Riv er basin. The GCMs are ranked according to the site measured data and monthly GCMs data. The statistical downscaling model SDSM is constr ucted based on daily data of 6 GCM models selected from 21 GCMs, the climate models integrated by 6 GCMs, in situstations data, and NCEP reanalysis data, to predict the future precipitation change in the upper reaches of Jinghe Riv2 er. 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 v alue and the distribution is similar within a year. The integr ated model performs best in the downscaling performance evaluation perio d. Under the RCP 4.5 scenario, most future precipitation models and integrated models in the upper Jing he River show an increasing tr end. By the 2030s, precipitation in the upper Jinghe River may increase by 4.8% , and local rainfall in spring also exhibits an incr easing trend, and summer rainfall may decrease.
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