基于CMIP6气候模式的贵州省极端降水情景预估  

Scenario Prediction of Extreme Precipitation in Guizhou Province Based on CMIP6 Climate Model

作　　者：冯椰林 贺中华[1] 焦树林[1] 刘炜 FENG Yelin;HE Zhonghua;JIAO Shulin;LIU Wei(School of Geographic and Environment Science,Guizhou Normal University,Guiyang 550025,China)

机构地区：[1]贵州师范大学地理与环境科学学院,贵阳550025

出　　处：《水土保持研究》2023年第1期282-290,共9页Research of Soil and Water Conservation

基　　金：国家自然科学基金(u1612441);国家自然科学基金(41471032);贵州省水利厅自然科研基金(KT201402)。

摘　　要：为探究气候变化下贵州省极端降水未来变化特征,基于台站观测和5个CMIP6模式的逐日降水资料,利用Delta降尺度、趋势分析等方法,分析了4种极端降水指数的历史与未来变化时空特征。结果表明:(1)利用Delta修正过后的CMIP6模式数据取得了良好的效果,适用于贵州省极端降水的预估。(2)在1961—2019年的历史时期,贵州省的R95P,R25mm和CWD均呈南高北低的空间分布,而R95C呈明显的东中西差异;除CWD外,其它3个极端降水指数在1961—2019年均呈不明显的增加趋势。(3)未来3种SSPs情景下,无论是在时间还是空间上,4个极端降水指数均呈上升的趋势。(4)相较于历史时期,4个极端指数除R95C外均有增有减。R95P与R25mm在空间变化上相似,都表现为西北部较历史时期有减少,其余地区则表现为增多,且随SSPs升高而增大;CWD在中南部地区表现为减少,其余地区为增加,以北部较为明显,且在SSP126情景下最为显著;R95C则在整个地区都较历史时期增多,在中西部变化最明显,且在SSP245情景下最显著。总体而言,在气候变化背景下,贵州省的极端降水随SSPs的不同而变化,但整体上会愈加多发,未来应加强防范与应对。In order to explore the characteristics of the future change of extreme precipitation in Guizhou Province under climate change, the temporal and spatial characteristics of the historical and future changes of four extreme precipitation indexes were analyzed by using the methods of Delta downscaling and trend analysis based on the station observation and daily precipitation data of five CMIP6 models. The results show that:(1) the CMIP6 model data modified by Delta has achieved good results and is suitable for the prediction of extreme precipitation in Guizhou Province;(2) from 1961 to 2019, the spatial distribution of R95 P, R25 mm and CWD in Guizhou Province was high in the south and low in the north, while the R95 C showed obvious differences between east and west;except for CWD, the other three extreme precipitation indices showed the insignificant increasing trend from 1961 to 2019;(3) under the future three SSPs scenarios, the four extreme precipitation indices will all show an increasing trend both in time and space;(4) compared with the historical period, the four extreme indexes except R95 C all increased and decreased;the spatial variation of R95 P and R25 mm is similar, showing decrease in the northwest compared with the historical period, and increase in the rest of the region, which increases with the increase of SSPs;CWD decreased in the central and southern regions, and increased in the rest regions, especially in the north, and was most significant under SSP126;R95 C increased throughout the region, with the most significant changes in the midwest and SSP245. In general, in the context of climate change, extreme precipitation in Guizhou Province varies with different SSPs, but it will become more frequent on the whole. Therefore, prevention and response should be strengthened in the future.

关 键 词：CMIP6 极端降水 SSPs情景 贵州省 

分 类 号：P467[天文地球—大气科学及气象学]