关中平原极端降水时空变化及其与大气环流的关系

doi:10.13866/j.azr.2022.01.11

Abstract

Abstract:

Based on daily precipitation data collected from 13 meteorological stations in the Guanzhong Plain in 1957-2019, the extreme precipitation indices were calculated and their spatial-temporal variation characteristics were analyzed. Specifically, the correlation between extreme precipitation and atmospheric general circulation was explored using a unitary linear regression method, Pearson correlation analysis, and wavelet coherence analysis. The results showed the following. (1) Extreme precipitation intensity showed an increasing trend at a rate of 0.007 mm·d^-1·(10a)^-1, whereas other extreme precipitation indices showed a decreasing trend in which the annual total extreme precipitation showed the most pronounced decreased with a rate of -5.528 mm·(10a)^-1. Additionally, none of the extreme precipitation indices had a significant mutation point. (2) The extreme precipitation indices were higher in the south and lower in the north, with a significant spatial difference detected. (3) Only the southern oscillation index (SOI) had a significant effect on extreme precipitation. The larger the SOI value, the more likely it was to rain less on the Guanzhong Plain. These results provide a theoretical basis for flood disaster prevention and control on the Guanzhong Plain.

Key words: Guanzhong Plain, extreme precipitation, spatial-temporal variation, atmospheric circulation

DING Yingying,QIU Dexun,WU Changxue,MU Xingmin,GAO Peng. Spatial-temporal variations in extreme precipitation and their relationship with atmospheric circulation in the Guanzhong Plain[J].Arid Zone Research, 2022, 39(1): 104-112.

Figures/Tables 9

Fig. 1

Tab. 1

Fig. 2

Tab. 2

Fig. 3

Tab. 3

Tab. 4

Tab. 5

Fig. 4

References 22

[1]	赵一飞, 邹欣庆, 许鑫王豪. 珠江流域极端降水事件及其与大气环流之间的关系[J]. 生态学杂志, 2014, 33(9): 2528-2537.
	[Zhao Yifei, Zou Xinqing, Xu Xinwanghao. Extreme precipitation events in the Pearl River Basin and its relationship with atmospheric circulation[J]. Chinese Journal of Ecology, 2014, 33(9): 2528-2537. ]
[2]	陈星任, 杨岳, 何佳男, 等. 近60年中国持续极端降水时空变化特征及其环流因素分析[J]. 长江流域资源与环境, 2020, 29(9): 2068-2081.
	[Chen Xingren, Yang Yue, He Jianan, et al. Analysis on the characteristics of temporal and spatial changes of continuous extreme precipitation in China and its circulation factors in the past 60 years[J]. Resources and Environment in the Yangtze Basin, 2020, 29(9): 2068-2081. ]
[3]	刘昌新, 张海玲, 吴静. 基于SSPs情景的中国极端降水影响评估[J]. 环境保护, 2021, 49(8): 29-34.
	[Liu Changxin, Zhang Hailing, Wu Jing. Assessment of the impact of extreme precipitation in China based on SSPs scenarios[J]. Environmental Protection, 2021, 49(8): 29-34. ]
[4]	马梦阳, 韩宇平, 王庆明, 等. 海河流域极端降水时空变化规律及其与大气环流的关系[J]. 水电能源科学, 2019, 37(6): 1-4.
	[Ma Mengyang, Han Yuping, Wang Qingming, et al. The temporal and spatial variation of extreme precipitation in the Haihe River Basin and its relationship with atmospheric circulation[J]. Hydropower Energy Science, 2019, 37(6): 1-4. ]
[5]	周旗, 张海宁, 任源鑫. 1961—2016年渭河流域极端降水事件研究[J]. 地理科学, 2020, 40(5): 833-841. doi: 10.13249/j.cnki.sgs.2020.05.018
	[Zhou Qi, Zhang Haining, Ren Yuanxin. A study on extreme precipitation events in the Weihe River Basin from 1961 to 2016[J]. Chinese Journal of Geography, 2020, 40(5): 833-841. ] doi: 10.13249/j.cnki.sgs.2020.05.018
[6]	邹磊, 余江游, 王飞宇, 等. 渭河流域极端降水时空演变规律及其对大气环流因子的响应[J]. 干旱区研究, 2021, 38(3): 764-774.
	[Zou Lei, Yu Jiangyou, Wang Feiyu, et al. The temporal and spatial evolution of extreme precipitation in the Weihe River Basin and its response to atmospheric circulation factors[J]. Arid Zone Research, 2021, 38(3): 764-774. ]
[7]	戴声佩, 罗红霞, 李茂芬, 等. 1959—2016年华南地区极端降水事件变化特征[J/OL]. 中国农业资源与区划: 1-17[2021-11-30].http://kns.cnki.net/kcms/detail/11.3513.S.20210607.1505.040.html.
	[Dai Shengpei, Luo Hongxia, Li Maofen, et al. Variation characteristics of extreme precipitation events in South China from 1959 to 2016[J/OL]. China Agricultural Resources and Regional Planning: 1-17[2021-11-30].http://kns.cnki.net/kcms/detail/11.3513.S.20210607.1505.040.html. ]
[8]	杜懿, 龙铠豪, 王大洋, 等. 基于机器学习方法的安徽省年降水量预测[J]. 水电能源科学, 2020, 38(7): 5-7, 41.
	[ Du Yi, Long Kaihao, Wang Dayang, et al. Prediction of annual precipitation in anhui province based on machine learning method[J]. Hydropower Energy Science, 2020, 38(7): 5-7, 41. ]
[9]	罗志文, 王小军, 刘梦洋, 等. 基于地区线性矩法的陕西省极端降水时空特征[J]. 干旱区研究, 2021, 38(5): 1295-1305.
	[Luo Zhiwen, Wang Xiaojun, Liu Mengyang, et al. Temporal and spatial characteristics of extreme precipitation in Shaanxi Province based on regional linear moment method[J]. Arid Zone Research, 2021, 38(5): 1295-1305. ]
[10]	刘燕飞, 隆霄, 王晖. 陕西中西部地区一次暴雨过程的数值模拟研究[J]. 高原气象, 2015, 34(2): 378-388.
	[Liu Yanfei, Long Xiao, Wang Hui. Numerical simulation studies on a rainstorm in central Western Shaanxi Province[J]. Plateau Meteorology, 2015, 34(2): 378-388. ]
[11]	白爱娟, 施能. 东亚冬、夏季风强度指数及其与陕西降水变化的关系[J]. 南京气象学院学报, 2004, 37(4): 519-526.
	[Bai Aijuan, Shi Neng. East Asian winter/summer monsoon intensity index and its relationship with precipitation change in Shaanxi Province[J]. Journal of Nanjing Institute of Meteorology, 2004, 37(4): 519-526. ]
[12]	周雅蔓, 刘晶, 赵勇, 等. 春季热带海温与北疆夏季极端降水的关系研究[J]. 冰川冻土, 2021, 43(4): 1166-1178.
	[Zhou Yaman, Liu Jing, Zhao Yong, et al. Study on the relationship between spring tropical sea temperature and extreme summer precipitation in northern Xinjiang[J]. Journal of Glaciology and Geocryology, 2021, 43(4): 1166-1178. ]
[13]	张冲, 赵景波. 厄尔尼诺/拉尼娜事件对陕西气候的影响[J]. 陕西师范大学学报(自然科学版), 2010, 38(5): 98-104.
	[Zhang Chong, Zhao Jingbo. The impact of El Nino/La Nina event on the climate of Shaanxi[J]. Journal of Shaanxi Normal University(Natural Science Edition), 2010, 38(5): 98-104. ]
[14]	窦睿音, 延军平. 1960—2010年关中地区旱涝灾害对气候变化的响应[J]. 湖南农业大学学报(自然科学版), 2012, 38(5): 542-547.
	[Dou Ruiyin, Yan Junping. Responses of drought and flood disasters in Guanzhong area from 1960 to 2010 to climate change[J]. Journal of Hunan Agricultural University (Natural Science Edition), 2012, 38(5): 542-547. ]
[15]	刘岩, 李晶, 秦克玉, 等. 基于情景的关中平原土地利用和生态系统服务预测及变化分析[J]. 陕西师范大学学报(自然科学版), 2018, 46(2): 95-103.
	[Liu Yan, Li Jing, Qin Keyu, et al. Scenario-based prediction and change analysis of land use and ecosystem services in the Guanzhong Plain[J]. Journal of Shaanxi Normal University(Natural Science Edition), 2018, 46(2): 95-103. ]
[16]	Zhou B, Xu Y, Wu J, et al. Changes in temperature and precipitation extreme indices over China: Analysis of a high-resolution grid dataset[J]. International Journal of Climatology, 2016, 36(3): 1051-1066. doi: 10.1002/joc.4400
[17]	王刚, 严登华, 张冬冬, 等. 海河流域1961—2010年极端气温与降水变化趋势分析[J]. 南水北调与水利科技, 2014, 12(1): 1-6.
	[Wang Gang, Yan Denghua, Zhang Dongdong, et al. Analysis on the trend of extreme temperature and precipitation in the Haihe River Basin from 1961 to 2010[J]. South-to-North Water Diversion and Water Conservancy Science and Technology, 2014, 12(1): 1-6. ]
[18]	Khaled H Hamed. Trend detection in hydrologic data: The Mann-Kendall trend test under the scaling hypojournal[J]. Journal of Hydrology, 2008, 349(3-4): 350-363. doi: 10.1016/j.jhydrol.2007.11.009. doi: 10.1016/j.jhydrol.2007.11.009
[19]	Grinsted A, Moore J C, Jevrejeva S. Application of the cross wavelet transform and wavelet coherence to geophysical time series[J]. Nonlinear Processes in Geophysics, 2004, 11(5/6): 561-566. doi: 10.5194/npg-11-561-2004. doi: 10.5194/npg-11-561-2004
[20]	邵骏. 基于交叉小波变换的水文多尺度相关分析[J]. 水力发电学报, 2013, 32(2): 22-26.
	[Shao Jun. Hydrological multi-scale correlation analysis based on cross wavelet transform[J]. Journal of Hydroelectric Engineering, 2013, 32(2): 22-26. ]
[21]	张菁, 张珂, 王晟, 等. 陕甘宁三河源区1971—2017年极端降水时空变化分析[J]. 河海大学学报(自然科学版), 2021, 49(3): 288-294.
	[Zhang Jing, Zhang Ke, Wang Sheng, et al. Analysis of the temporal and spatial changes of extreme precipitation in the source area of the Three Rivers in Shaanxi, Gansu and Ningxia from 1971 to 2017[J]. Journal of Hohai University (Natural Science Edition), 2021, 49(3): 288-294. ]
[22]	Lachaux J P, Lutz A, Rudrauf D, et al. Estimating the time-course of coherence between single-trial brain signals: An introduction to wavelet coherence[J]. Neurophysiologie Clinique/Clinical Neurophysiology, 2002, 32(3): 157-174.

极端降水指数	名称	单位	意义和说明
CWD	持续湿期	d	日降水量>1 mm的最大持续日数
SDII	日降水强度	mm·d^-1	降水总量与有雨日数之比（日降水量≥1 mm）
PRCPTOT	降水总量	mm	日降水量>1 mm的年累积降水量
R10mm	中雨日数	d	日降水量≥10 mm的总日数
RX1day	最大1日降水量	mm	每年最大日降水量
RX5day	连续5日最大降水量	mm	每年连续5日最大降水量

	CWD/d	PRCPTOT/mm	R10mm/d	RX1day/mm	RX5day/mm	SDII/（mm·d^-1）
多年均值	7.87	513.36	14.35	29.4	61.47	5.58
最大值	17	765.6	23	45.07	108.79	7.3
最小值	4	332.6	7	17.41	35.74	4.6
最大值出现年份	2007	1964	1983	2010	2003	1983
最小值出现年份	1995、2004、2012	1997	1997	1987	1987	1977、2015

指数	上升趋势站点个数	占比/%	下降趋势站点个数	占比/%
CWD	2	15.4	11	84.6
PRCPTOT	4	30.8	9	69.2
R10mm	1	7.7	12	92.3
RX1day	10	76.9	3	23.1
RX5day	6	46.2	7	53.8
SDII	11	84.6	2	15.4

	CWD	PRCPTOT	R10mm	RX1day	RX5day	SDII
CWD	1
PRCPTOT	0.320^*	1
R10mm	0.242	0.875^**	1
RX1day	-0.073	0.319^*	0.289^*	1
RX5day	0.296^*	0.488^**	0.478^**	0.482^**	1
SDII	0.143	0.748^**	0.806^**	0.443^**	0.547^**	1

月份		CWD	PRCPTOT	R10mm	RX1day	RX5day	SDII
AMO	1—3	0.030	0.100	0.120	0.131	0.052	0.246
	4—6	-0.072	0.038	0.094	0.136	0.020	0.234
	7—9	-0.064	-0.044	0.027	0.125	0.059	0.139
	10—12	-0.008	-0.001	0.050	0.172	0.034	0.193
AO	1—3	-0.059	0.013	0.004	-0.042	-0.074	-0.120
	4—6	0.067	0.192	0.034	-0.089	0.010	-0.033
	7—9	-0.019	0.131	0.093	0.121	0.080	0.028
	10—12	-0.044	0.070	0.068	-0.013	-0.070	0.020
NAO	1—3	-0.162	-0.139	-0.103	-0.082	-0.126	-0.155
	4—6	-0.141	0.088	-0.100	-0.143	-0.145	-0.079
	7—9	0.070	0.092	0.026	-0.004	0.044	0.045
	10—12	-0.014	-0.016	-0.061	-0.188	-0.134	-0.108
NP	1—3	0.042	-0.107	-0.133	-0.164	-0.101	-0.276^*
	4—6	0.063	0.208	0.149	0.073	0.048	-0.004
	7—9	0.008	0.090	0.027	0.052	-0.043	0.023
	10—12	-0.077	0.230	0.193	0.262^*	0.056	0.270^*
PDO	1—3	-0.022	0.183	0.136	-0.014	0.001	0.149
	4—6	-0.153	0.004	0.001	-0.004	-0.036	0.120
	7—9	-0.162	-0.133	-0.133	-0.249^*	-0.101	-0.123
	10—12	-0.185	-0.195	-0.188	-0.216	-0.119	-0.151
WP	1—3	-0.062	0.103	0.143	0.032	0.053	0.088
	4—6	0.058	-0.066	-0.093	-0.200	0.026	-0.172
	7—9	0.064	0.033	-0.078	0.014	0.048	-0.102
	10—12	-0.006	-0.069	-0.068	-0.157	0.028	0.016
SOI	1—3	0.059	-0.237	-0.257^*	-0.165	-0.131	-0.425^**
	4—6	0.294^*	0.359^**	0.354^**	0.261^*	0.202	0.249^*
	7—9	0.149	0.393^**	0.412^**	0.275^*	0.159	0.356^**
	10—12	0.230	0.332^**	0.324^**	0.285^*	0.167	0.370^**

Spatial-temporal variations in extreme precipitation and their relationship with atmospheric circulation in the Guanzhong Plain

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 22

Related Articles 15

Metrics

Comments

Recommended 0

[1]	LI Hong, LI Zhongqin, CHEN Puchen, PENG Jiajia. Spatio-temporal variation of snow cover in Altai Mountains of Xinjiang in recent 20 years and its influencing factors [J]. Arid Zone Research, 2023, 40(7): 1040-1051.
[2]	HU Yanan, PEI Hao, JIANG Yanfeng, MIAO Bailing, JIA Chengzhen. Spatiotemporal variation characteristics of precipitation pH in Inner Mongolia from 1991 to 2021 [J]. Arid Zone Research, 2023, 40(4): 552-562.
[3]	HUANG Ying, WANG Suyan, MA Yang, WANG Dai, ZHANG Wen, WANG Fan. Change characteristics and circulation anomaly analysis of cold wave in Ningxia over the past 60 years [J]. Arid Zone Research, 2023, 40(11): 1718-1728.
[4]	ZHANG Zhigao, SUN Zixin, ZHANG Xiuli, GUO Kexin, LI Zhuoya, HAO Haijiao, CAI Maotang. Spatial-temporal evolution and impact factors during the climatic growing season in the Yellow River Basin from 1960 to 2020 [J]. Arid Zone Research, 2023, 40(10): 1537-1546.
[5]	ZHANG Yaozong,ZHANG Bo,ZHANG Duoyong,LIU Yanyan. Spatio temporal patterns of pan evaporation from 1960 to 2018 over the Loess Plateau: Changing properties and possible causess [J]. Arid Zone Research, 2022, 39(1): 1-9.
[6]	ZHANG Taixi,FAN Jing,LI Yuanpeng,YU Xingjie. Heatwave changes and the potential causes in Xinjiang from 1961 to 2018 [J]. Arid Zone Research, 2021, 38(5): 1274-1284.
[7]	LUO Zhiwen,WANG Xiaojun,LIU Mengyang,KE Hang,WAN Ting,YIN Yixing. Spatiotemporal characteristics of extreme precipitation in Shaanxi Province based on the regional L-moments method [J]. Arid Zone Research, 2021, 38(5): 1295-1305.
[8]	CHEN Jing,GUO Xiaoning,BAI Wenjuan,WEN Xia,YANG Yanhua. Spatiotemporal characteristics and influencing factors of dust weather in Qaidam Basin in recent 60 years [J]. Arid Zone Research, 2021, 38(4): 1040-1047.
[9]	LIU Mengyang,WANG Xiaojun,KE Hang,LUO Zhiwen,YIN Yixing. Analysis of extreme summer precipitation characteristics and typical years’circulation characteristics in Longdong Region [J]. Arid Zone Research, 2021, 38(3): 775-784.
[10]	ZOU Lei,YU Jiangyou,WANG Feiyu,ZHANG Yan. Spatial-temporal variations of extreme precipitation indices and their response to atmospheric circulation factors in the Weihe River Basin [J]. Arid Zone Research, 2021, 38(3): 764-774.
[11]	GAO Jing,JING Lihong,QIN Rong,MAO Rong,JING Lijun. Snowstorm characteristics and its relationship with atmospheric circulation and sea surface temperature in Tacheng Region, Xinjiang [J]. Arid Zone Research, 2021, 38(2): 359-368.
[12]	ZHANG Junlan,LUO Ji,WANG Rongmei. Combined analysis of the spatiotemporal variations in snowmelt (ice) flood frequency in Xinjiang over 20 years and atmospheric circulation patterns [J]. Arid Zone Research, 2021, 38(2): 339-350.
[13]	CAO Lijun,SUN Huilan,LAN Xiaoli,ZHANG Lele,LU Baobao,LIU Tianyi. Spatio-temporal evolution of the extreme dry and wet events in Tianshan Mountains, Xinjiang, China [J]. Arid Zone Research, 2021, 38(1): 188-197.
[14]	MA Ai-hua, YUE Da-peng, ZHAO Jing-bo, HU Qian. Spatiotemporal Variation and Effect of Extreme Precipitation in Inner Mongolia in Recent 60 Years [J]. Arid Zone Research, 2020, 37(1): 74-85.
[15]	YIN Tian-yuan, YIN Shu-yan, LI Fu-min. Relationship between the Summer Extreme Precipitation in the South and North of the Qinling Mountains and the Western Pacific Subtropical High [J]. Arid Zone Research, 2019, 36(6): 1379-1390.