摘要
极端降水事件导致的严重灾害已经引起越来越多的关注,气候变化与极端降水之间的关系成为广泛关注的科学前沿问题之一。文中通过对比1981-2010年美国、欧洲、中国、巴西和印度的年际和年代际的暴雨雨量、暴雨雨日和暴雨雨强,来分析在不同城镇化发展速度国家的暴雨变化情况。结果表明:暴雨雨量、暴雨雨日和暴雨雨强在这五个国家和地区都呈现增加趋势,并且整体上在中国、巴西和印度的增加显著高于美国和欧洲。基于目前已有研究成果表明大气海洋等气候因子不能完全解释暴雨在五个地区的增加趋势。因此,文中引入国民生产总值(GDP)、城市化率(UR)和黑炭气溶胶光学厚度(AOD)作为快速城镇化的表征因子与五个国家和地区的暴雨雨量、暴雨雨日和暴雨雨强做相关和散点图,结果表明在GDP、UR和AOD增长速率较快的中国、巴西和印度,暴雨雨量、暴雨雨日和暴雨雨强与GDP、UR、AOD的相关性明显高于美国和欧洲。因此,城镇化发展速率越快,越有可能触发大面积暴雨的显著增加。
Severe disasters caused by extreme precipitation events have been increasingly noted worldwide,and they are often attributed to climate change,while the relationship between climate change and extreme precipitation has become one of the hottest scientific frontier issues. In this research,the interannual and interdecadal heavy rainfall amount(HRA),heavy rainfall days(HRD) and heavy rainfall intensity(HRI) in the USA,Europe,China,Brazil and India,from 1981 to 2010 were calculated and compared. the results show that HRA,HRD and HRI increased in the five countries and regions. And on the whole,HRA,HRD and HRI in China,Brazil and India increased significantly higher than those in USA and Europe. Current researches show that atmospheric and oceanic climate indices cannot completely explain the increase of heavy rainfall in five regions.Therefore,we introduce into GDP,UR and AOD as the rapid urbanization characterization in the five countries and regions,and then perform the correlation and scatter diagram between HRA,HRD,HRI and GDP,UR,AOD. The result shows that the correlation in China,Brazil and India with higher GDP,UR and AOD is higher than those in USA and Europe. Therefore,rapid urbanization most likely triggered the significant increase of heavy rainfall.
出处
《干旱区资源与环境》
CSSCI
CSCD
北大核心
2017年第10期90-97,共8页
Journal of Arid Land Resources and Environment
基金
国家自然科学基金创新研究群体项目"地表过程模型与模拟"(41321001)
中国博士后科学基金面上资助项目"基于时空变化分析的气候变化对洪水灾害影响研究"(2015M582263)
中央高校基本科研业务费专项资金课题"气候变化对长江流域洪水灾害影响研究"(2042016kf0067)资助
关键词
快速城镇化
触发因素
暴雨
年际和年代际变化
区域对比
rapid urbanization
trigger factors
heavy rainfall
interannual and interdecadal change
regional comparison