[1]王芸,赵鹏祥. 黄河流域极端气候事件的时空变异特征研究[J].西北林学院学报,2021,36(3):190-196.[doi:10.3969/j.issn.1001-7461.2021.03.28]
　WANG Yun,ZHAO Peng-xiang. Temporal and Spatial Variation Characteristics of Extreme Climate Events in the Yellow River Basin[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2021,36(3):190-196.[doi:10.3969/j.issn.1001-7461.2021.03.28]
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 黄河流域极端气候事件的时空变异特征研究()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第36卷
期数:
2021年第3期
页码:
190-196
栏目:
出版日期:
2021-05-31

文章信息/Info

Title:
 Temporal and Spatial Variation Characteristics of Extreme Climate Events in the Yellow River Basin
文章编号:
1001-7461(2021)03-0190-07
作者:
 王芸1; 2; 赵鹏祥3
 （1.河北开放大学 教务处，河北 石家庄 050080；2.国家开放大学 农林医药教学部，北京 100039；3.西北农林科技大学 林学院，陕西 杨陵 712100）
Author(s):
 WANG Yun1; 2; ZHAO Peng-xiang3
 (1.Academic Affairs Office,Hebei Open University,Shijiazhuang 050080,Hebei,China; 2.School of Agroforestry & Medicine,The Open University of China,Beijing 100039,China; 3.College of Forestry,Northwest A&F University,Yangling 712100,Shaanxi,China)
关键词:
 ; 极端气候; 贝叶斯理论; 时空变异特征; 黄河流域
Keywords:
 ; extreme climate;  Bayesian Theory;  spatiotemporal variation characteristics;  Yellow River Basin
分类号:
S165
DOI:
10.3969/j.issn.1001-7461.2021.03.28
文献标志码:
A
摘要:
 以黄河流域为例，充分考虑降水要素的空间异质性，将其划分为8个子区域；选定持续干燥指数（CDD）、持续湿润指数（CWD）、强降水日数（R10）和5 d最大降水量（RX5）4个极端降水指标，采用数理统计、一元线性回归等方法对各子区域极端降水特征进行趋势性分析；并采用基于贝叶斯理论的可逆跳跃马尔科夫蒙特卡洛算法（RJMCMC），识别并量化了各子区域不同极端降水指标的突变位置及其变异程度。结果表明：1）黄河流域暖干化趋势明显，流域北部尤为突出。2）CDD、CWD、R10和RX5指数空间上趋势变化较大，但相邻区域之间存在相似的分布规律。3）不同子区域不同极端气候指数的突变年份不同，但多集中于90年代。研究结果可有效提高极端气候预测的准确性和可靠性。识别并量化气候时空变异特征对防洪、抗旱布控工作的顺利开展具有现实意义。
Abstract:
 Affected by global warming,floods and droughts caused by extreme climate change are frequent and widespread.Thus,it is of practical significance to identify and quantify the spatio-temporal variation characteristics of extreme climate for the smooth development of flood control and drought control.Taking the Yellow River Basin as an example，the basin was divided into eight sub-regions based on the spatial heterogeneity of precipitation.The trends of four extreme precipitation indices (CDD,CWD,R10 and RX5) in each sub region were analyzed by mathematical statistics and linear regression.Based on Bayesian Theory,Reversible Jump Markov Chain Monte Carlo (RJMCMC) was used to identify and quantify the mutation position and degree of extreme precipitation index in each sub-region.The results showed that 1)the trend of warming and drying was obvious in the Yellow River Basin,especially in the northern part of the basin.2)Meanwhile,the spatial trends of CDD,CWD,R10 and RX5 indices changed greatly,but there were similar distribution rules between adjacent regions.3)The abrupt change years of 4 extreme climate indices in each sub-regions were different,but most of them were concentrated in the 1990s.The results can effectively improve the accuracy and reliability of extreme climate prediction.

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备注/Memo

备注/Memo:
 收稿日期：2020-09-27修回日期：2020-11-23
基金项目：河北省社科基金项目（HB17JY030），国家重点研发计划项目(2016YFD0600203)。
作者简介：王芸，女，博士。研究方向：3S技术在资源环境中的应用。E-mail:bingyu698@163.com
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