Trends in observed mean and extreme precipitation within the Yellow River Basin, China

被引:37
|
作者
Zhao, Yang [1 ,2 ]
Xu, Xiangde [2 ]
Huang, Wubin [3 ]
Wang, Yuhong [4 ]
Xu, Yanling [5 ]
Chen, Hong [6 ]
Kang, Zhaoping [7 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Nanjing 210044, Jiangsu, Peoples R China
[2] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China
[3] Lanzhou Cent Meteorol Observ, Lanzhou 730020, Gansu, Peoples R China
[4] China Meteorol Adm, Serv Ctr Publ Meteorol, Beijing 100081, Peoples R China
[5] Chinese Acad Environm Planning, Atmospher Environm Dept, Beijing 100012, Peoples R China
[6] Tianjin Meteorol Observ, Tianjin 300074, Peoples R China
[7] CMA, Hubei Key Lab Heavy Rain Monitoring & Warning Res, Inst Heavy Rain, Wuhan 430074, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Yellow River; Trend analysis; Extreme precipitation; Correlation analysis; China; CLIMATE EXTREMES; INDEXES; REGION; VARIABILITY; INDICATORS; WORKSHOP;
D O I
10.1007/s00704-018-2568-4
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
We analyzed spatiotemporal precipitation trends within the Yellow River Basin (YRB) in China and examined the connection between the changes in average and extreme precipitation indices. Data from 423 weather stations recorded from 1961 to 2016 were analyzed using the Mann-Kendall test to explore the linear trends of relationships between various indices, along with a simple linear regression used to detect monotonic positive or negative trends in the annual and seasonal precipitation data. Moreover, we divided the YRB into three distinct topographic regions to better understand the effect of regional geography on precipitation patterns. Our results demonstrated that mean precipitation and extreme precipitation days in different areas of the YRB had different variation trends. Precipitation in the YRB overall showed a negative trend, as did extreme precipitation days in the lower YRB. Mean and extreme precipitation indices were significantly correlated both annually and seasonally. These results may be helpful in preparing for both drought and flood events.
引用
收藏
页码:1387 / 1396
页数:10
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