摘要
基于海陆分异视角,采用BCC-CSM2-MR模式的日值降雨数据和多种数理统计方法,对比分析2015—2100年不同SSPs情景下的全球海陆暴雨的时序动态变化和突变特征。结果表明:(1)2015—2100年不同SSPs情景下全球、全球陆地和全球海洋的暴雨量、暴雨日、暴雨强、暴雨量贡献率、暴雨日贡献率均呈增加趋势,且SSP5-8.5增加趋势最大,SSP3-7.0次之,SSP2-4.5再次之,SSP1-2.6最小。(2)高辐射强迫的SSP5-8.5情景和低辐射强迫的SSP1-2.6情景下的差异特征在全球陆地最大,全球次之,全球海洋最小。(3)2015—2100年不同SSPs情景下全球、全球陆地和全球海洋的暴雨量、暴雨日、暴雨强、暴雨量贡献率、暴雨日贡献率均发生了突变,且突变年份多分布在2050年之前。
Based on the perspective of sea-land differentiation,the dynamic variation and mutation characteristics of the global sea-land rainstorm time series under different SSPs scenarios from 2015 to 2100 are comparatively analyzed herein with the daily rainfall data of BCC-CSM2-MR mode and several mathematical statistics methods.The results show that(1)all the rainstorm amounts,rainstorm days,rainstorm intensities,rainstorm amount contribution rates and rainstorm day contribution rates of the global,the global land and the global sea exhibit increasing trends under different SSPs scenarios from 2015 to 2100,for which the increasing trends are the largest for SSP5-8.5,the secondary for SSP3-7.0,the third for SSP2-4.5 and the least for SSP1-2.6.(2)The difference characteristics of SSP5-8.5 scenario with high radiation forcing and SSP1-2.6 scenario with low radiation forcing are the largest in the global land,the secondary in the whole globe and the least in the global sea.(3)Mutations occur at all the rainstorm amounts,rainstorm days,rainstorm intensities,rainstorm amount contribution rates and rainstorm day contribution rates of the global,the global land and the global sea under different SSPs scenarios from 2015 to 2100 and most of the mutation years are distributed in the period before 2050.
作者
孔锋
KONG Feng(School of Public Policy and Management, Tsinghua University, Beijing 100084, China;Center for Crisis Management Research, Tsinghua University, Beijing 100084, China;Training Center, China Meteorological Administration, Beijing 100081, China)
出处
《水利水电技术》
北大核心
2020年第10期1-9,共9页
Water Resources and Hydropower Engineering
基金
国家重点研发计划(2019YFC1510202,2018YFC1509003)
国家自然科学基金(41801064,41775078,41701103)
中国博士后科学基金资助(2019T120114,2019M650756)
中亚大气科学研究基金(CAAS201804)。