Evaluation and Projection of Simulating Precipitation over Guizhou Province with CMIP6 Models
Based on the daily precipitation data from 18 global climate models that participated in the phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their precedent phase project (CMIP5),and the 84 observational stations in Guizhou Province,the capabilities of CMIP6 on simulating the precipitation in Guizhouwassystematically evaluated using the root mean square error (RMSE) and Taylor diagram for the evaluation period. The best simulation results were selected to project the change characteristics of the precipitation in Guizhou under three future scenarios (SSP1-2.6,SSP2-4.5 and SSP5-8.5)from 2023 to 2100. The results showed that the CMIP6-MMA(multi-model mean)generally had better performance in simulating the indices including the maximum number of consecutive dry days(CDD),the number of days with precipitation ≥20 mm ×(R20 mm),the maximum consecutive 5-day precipitation (Rx5day),simple daily intensity index (SDII) and total annual precipitation(PRCPTOT)compared to the individual model and the CMIP5-MMA in Guizhou from 1986 to 2005. Compared to the reference period(1995-2014),significant increases were detected in Guizhou from 2023 to 2100 in CDD under SSP5-8.5,and R20mm,Rx5day,SDII and PRCPTOT under three scenarios,except for CDD under SSP1-2.6 and 2-4.5. Itindicated that CDD over the southern Guizhou grew during the 21st century(2023-2048,2049-2074 and 2075-2100)under SSP2-4.5 and 5-8.5 relative to 1995-2014. The resultsimplied that more attention should be paid to the potential drought in southern Guizhou in future. Besides,the increases in R20 mm,Rx5day,SDII and PRCPTOT were also found in Guizhou during the 21st century compared to 1995-2014,with the increases generally intensifying from west to east and becoming moer pronounced over time,it suggested that the extreme heavy precipitation over Guizhou showed an increasing trend under the high emission scenario against the global warming,especially in eastern Guizhou.
万方数据
维普
