基于MF-DFA的西安昼夜复合高温事件变化特征及影响因素

doi:10.12118/j.issn.1000–6060.2021.108

Abstract

Abstract:

Improving research methods and regional adaptation measures depend on the refining of extreme weather processes. However, it is still a great challenge to refine the types of historical warming to more sophisticated extreme events. We identified three summertime hot extremes based on daily temperature (T_max and T_min) data obtained from 22 meteorological stations in Xi’an City, Shaanxi Province, China and the surrounding areas: independent hot days, independent hot nights, and compound hot extremes. The stochastic resort detrended fluctuation analysis (MF-DFA) and extreme-point symmetric mode decomposition (ESMD) were used to determine the variation of the compound hot extremes during the day and night in Xi’an City from 1955 to 2019. Meanwhile, the influencing factors of the annual fluctuation of the compound hot extremes during the day and night were analyzed. The results show that: (1) the highest temperature and threshold of the original data are the same as the homogenized data in Xi’an City. The threshold of the lowest temperature is relatively lower by 0.2-0.5 ℃ after homogenization. As a result, the Xi’an station was relocated between urban areas and suburbs between 1959 and 2005, which resulted in an underestimation of the extreme temperature trend. (2) While the MF-DFA, 90.0%, and 95.0% threshold schemes perform similarly well in identifying high temperature events, the 99.0% threshold and relative threshold schemes are the primary sources of uncertainty. (3) The interannual fluctuation and trend changes from 3.3-3.8 a were the compound hot extremes from 1955 to 2019. The number of compound hot extremes increased significantly in the mid-1980s, while the normal number of days and independent hot days decreased, and the number of independent hot nights and compound hot extremes increased. (4) The sea surface temperature (SST) anomaly in the equatorial western Pacific Ocean can be used as a key sea area for early warning of Xi’an City’s day and night combined high temperatures. The circulation analysis of the day-night composite high temperature events lasting more than five days verified the reliability of the abnormal warming of SST in the equatorial western Pacific as early warning information. In addition, we found that the South Asian high is moving northward and the western Pacific subtropical high is extending westward, which is the specific circulation mechanism of the regional day-night composite high temperature. It is important to understand that the variation in characteristics of the compound hot extremes at day and night in Xi’an City from 1955—2019 and the circulation characteristics of hot extremes lasting more than five days. One could argue that this study establishes both a theoretical and methodological basis for urban climate adaptation.

Key words: climate change, the compound hot extremes at daytime and nighttime, El Niño, Xi’an City

LI Shuangshuang,WANG Ting. Variation characteristics and its influencing factors of the compound hot extremes at daytime and nighttime in Xi’an City based on MF-DFA[J].Arid Land Geography, 2022, 45(1): 103-112.

Figures/Tables 10

Fig. 1

Fig. 2

Tab. 1

Fig. 3

Tab. 2

Fig. 4

Fig. 5

Tab. 3

Fig. 6

Fig. 7

References 24

[1]	Diffenbaugh N S, Singh D, Mankin J S, et al. Quantifying the influence of global warming on unprecedented extreme climate events[J]. Proceedings of the National Academy of Sciences, 2017, 114(19):4881-4886. doi: 10.1073/pnas.1618082114
[2]	Power S B, Delage F P D. Setting and smashing extreme temperature records over the coming century[J]. Nature Climate Change, 2019, 9(7):529-534. doi: 10.1038/s41558-019-0498-5
[3]	Wehrli K, Guillod B P, Hauser M, et al. Identifying key driving processes of major recent heat waves[J]. Journal of Geophysical Research: Atmospheres, 2019, 124(22):11746-11765. doi: 10.1029/2019JD030635
[4]	Chuang J S, Rivoire O, Leibler S. Simpson’s paradox in a synthetic microbial system[J]. Science, 2009, 323(5911):272-275. doi: 10.1126/science.1166739 pmid: 19131632
[5]	Wu X S, Guo S L, Yin J B, et al. On the event-based extreme precipitation across China: Time distribution patterns, trends, and return levels[J]. Journal of Hydrology, 2018, 562:305-317. doi: 10.1016/j.jhydrol.2018.05.028
[6]	Shang W, Li S S, Ren X M, et al. Event-based extreme precipitation in central-eastern China: Large-scale anomalies and teleconnections[J]. Climate Dynamics, 2020, 54(3-4):2347-2360. doi: 10.1007/s00382-019-05116-1
[7]	李双双, 汪成博, 延军平, 等. 面向事件过程的秦岭南北极端降水时空变化特征[J]. 地理学报, 2020, 75(5):989-1007. doi: 10.11821/dlxb202005008
	[Li Shuangshuang, Wang Chengbo, Yan Junping, et al. Variability of the event-based extreme precipitation in the south and north Qinling Mountains[J]. Acta Geographica Sinica, 2020, 75(5):989-1007. ] doi: 10.11821/dlxb202005008
[8]	Chen Y, Zhai P. Revisiting summertime hot extremes in China during 1961—2015: Overlooked compound extremes and significant changes[J]. Geophysical Research Letters, 2017, 44(10):5096-5103. doi: 10.1002/2016GL072281
[9]	杨维涛, 孙建国, 康永泰, 等. 黄土高原地区极端气候指数时空变化[J]. 干旱区地理, 2020, 43(6):1456-1466.
	[Yang Weitao, Sun Jianguo, Kang Yongtai, et al. Temporal and spatial changes of extreme weather indices in the Loess Plateau[J]. Arid Land Geography, 2020, 43(6):1456-1466. ]
[10]	焦文慧, 张勃, 马彬, 等. 近58 a中国北方地区极端气温时空变化及影响因素分析[J]. 干旱区地理, 2020, 43(5):1220-1230.
	[Jiao Wenhui, Zhang Bo, Ma Bin, et al. Temporal and spatial changes of extreme temperature and its influencing factors in northern China in recent 58 years[J]. Arid Land Geography, 2020, 43(5):1220-1230. ]
[11]	杜海波, 吴正方, 张娜, 等. 近 60 a 丹东极端温度和降水事件变化特征[J]. 地理科学, 2013, 33(4):473-480. doi: 10.13249/j.cnki.sgs.2013.04.473
	[Du Haibo, Wu Zhengfang, Zhang Na, et al. Characteristics of extreme temperature and precipitation events over Dandong during the last six decades[J]. Scientia Geographica Sinica, 2013, 33(4):473-480. ] doi: 10.13249/j.cnki.sgs.2013.04.473
[12]	Zhu B, Sun B, Wang H. Dominant modes of interannual variability of extreme high-temperature events in eastern China during summer and associated mechanisms[J]. International Journal of Climatology, 2020, 40(2):841-857. doi: 10.1002/joc.v40.2
[13]	Yin H, Sun Y. Detection of anthropogenic influence on fixed threshold indices of extreme temperature[J]. Journal of Climate, 2018, 31(16):6341-6352. doi: 10.1175/JCLI-D-17-0853.1
[14]	Wang J, Chen Y, Tett S, et al. Anthropogenically-driven increases in the risks of summertime compound hot extremes[J]. Nature Communications, 2020, 11(1):528-538. doi: 10.1038/s41467-019-14233-8 pmid: 32047147
[15]	杨萍, 侯威, 封国林. 基于去趋势波动分析方法确定极端事件阈值[J]. 物理学报, 2008, 57(8):5333-5342.
	[Yang Ping, Hou Wei, Feng Guolin. Determining the threshold of extreme events with detrended fluctuation analysis[J]. Acta Physical Sinica, 2008, 57(8):5333-5342. ]
[16]	侯威, 章大全, 钱忠华, 等. 基于随机重排去趋势波动分析的极端高温事件研究及其综合指标的建立[J]. 高原气象, 2012, 31(2):329-341.
	[Hou Wei, Zhang Daquan, Qian Zhonghua, et al. Research about the extreme high temperature events and its composite index based on stochastic re-sort detrended fluctuation analysis[J]. Plateau Meteorology, 2012, 31(2):329-341. ]
[17]	侯威, 章大全, 杨萍, 等. 去趋势波动分析方法中不重叠等长度子区间长度的确定[J]. 物理学报, 2010, 59(12):8986-8993.
	[Hou Wei, Zhang Daquan, Yang Ping, et al. A valid method to compute the segment size in detrended fluctuation analysis[J]. Acta Physical Sinica, 2010, 59(12):8986-8993. ]
[18]	Wang S S, Hu D Y, Chen S S, et al. A partition modeling for anthropogenic heat flux mapping in China[J]. Remote Sensing, 2019, 11(9):1132-1151. doi: 10.3390/rs11091132
[19]	陕西省气象局. 陕西省基层气象台站简史[M]. 北京: 气象出版社, 2012.
	[Shaanxi Meteorological Administration. History of meteorological stations in Shaanxi Province[M]. Beijing: China Meteorological Press, 2012. ]
[20]	王博, 黄晓军, 王晨, 等. 西安城市边缘区土地利用数据集(2015)[J]. 全球变化数据学报, 2019, 3(4):382-386.
	[Wang Bo, Huang Xiaojun, Wang Chen, et al. Land use dataset of the sub-urban area in Xi’an (2015)[J]. Journal of Global Change Data & Discovery, 2019, 3(4):382-386. ]
[21]	Wang X L, Chen H, Wu Y, et al. New techniques for the detection and adjustment of shifts in daily precipitation data series[J]. Journal of Applied Meteorology and Climatology, 2010, 49(12):2416-2436. doi: 10.1175/2010JAMC2376.1
[22]	王金良, 李宗军. 极点对称模态分解方法: 数据分析与科学探索的新途径[M]. 北京: 高等教育出版社, 2015.
	[Wang Jinliang, Li Zongjun. Extreme-point symmetric mode decomposition: The new way of data analysis and scientific exploration[M]. Beijing: Higher Education Press, 2015. ]
[23]	包为民, 沈丹丹, 倪鹏, 等. 滑动平均差检测法的提出及验证[J]. 地理学报, 2018, 73(11):2075-2085. doi: 10.11821/dlxb201811003
	[Bao Weimin, Shen Dandan, Ni Peng, et al. Proposition and certification of moving mean difference method for detecting abrupt change points[J]. Acta Geographica Sinica, 2018, 73(11):2075-2085. ] doi: 10.11821/dlxb201811003
[24]	Du Q Q, Zhang M J, Wang S J, et al. Changes in air temperature over China in response to the recent global warming hiatus[J]. Journal of Geographical Sciences, 2019, 29(4):496-516. doi: 10.1007/s11442-019-1612-3

Metrics

Viewed

Full text

498

HTML			PDF

Just accepted	Online first	Issue	Just accepted	Online first	Issue
0	0	2	0	0	496

From	Others	local

Times	280	218
Rate	56%	44%

Abstract

394

Just accepted	Online first	Issue

0	0	394

From	Others	local

Times	386	8
Rate	98%	2%

Cited

Web of Science	Crossref	ScienceDirect	Search for Citations in Google Scholar >>


This page requires you have already subscribed to WoS.

Shared

序号	指标	原始最高温/℃	校正最高温/℃	原始最低温/℃	校正最低温/℃
1	MF-DFA方法	36.1	35.9	23.6	23.1
2	99.0%阈值	38.0	37.8	26.1	25.9
3	95.0%阈值	35.5	35.2	23.7	23.3
4	90.0%阈值	33.5	33.3	22.0	21.5
5	绝对阈值	35.0	35.0	25.0	25.0

本征模态	主周期/a	方差	F值
IMF1	3.8	2.76	6.51
IMF1	3.3	2.44	5.62
IMF2	9.3	0.63	6.63
IMF2	7.2	0.77	8.50
IMF3	21.7	1.82	16.68
	16.3	1.17	9.03
	10.8	0.90	6.49
IMF4	21.7	0.23	45.83

序号	开始（年-月-日）	结束（年-月-日）	持续时间/d	白天均温/℃	夜晚均温/℃
1	1955-08-05	1955-08-11	7	37.5	25.1
2	1959-07-26	1959-07-31	6	39.4	25.4
3	1968-07-23	1968-07-28	6	37.9	24.5
4	1971-07-19	1971-07-25	7	37.4	24.3
5	1979-08-07	1979-08-12	6	37.4	25.2
6	1981-07-31	1981-08-04	5	36.2	25.4
7	2001-07-05	2001-07-09	5	37.7	25.6
8	2002-07-10	2002-07-14	5	38.2	26.4
9	2002-07-31	2002-08-05	6	37.1	25.7
10	2004-06-23	2004-06-29	7	37.8	25.8
11	2005-06-18	2005-06-22	5	39.9	24.5
12	2012-07-26	2012-07-30	5	38.2	26.8
13	2014-07-16	2014-07-22	7	37.8	26.2
14	2015-07-26	2015-08-02	8	37.8	26.2
15	2017-07-09	2017-07-14	6	39.8	25.6
16	2017-07-18	2017-07-27	10	40.1	28.5
17	2018-07-18	2018-07-26	9	37.8	27.2
18	2018-08-06	2018-08-12	7	37.2	26.5

Variation characteristics and its influencing factors of the compound hot extremes at daytime and nighttime in Xi’an City based on MF-DFA

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 24

Related Articles 15

Metrics

Comments

Recommended 0

[1]	KANG Limin, TENG Xinru, CHE Jiahang, HUAI Baojuan. Spatiotemporal variations of snow cover on the northern slope of Kunlun Mountains [J]. Arid Land Geography, 2024, 47(9): 1462-1471.
[2]	WANG Nan, LIU Zexuan, ZHENG Jianghua, ZHONG Tao, MENG Chengfeng. Spatiotemporal characteristics and driving forces of glacial lakes in Tianshan Mountains [J]. Arid Land Geography, 2024, 47(9): 1472-1481.
[3]	CHAO Bao, ZHAO Yuanyuan, WU Haiyan, LI Yuan, SU Ning. Ecosystem services and its response to climate factors in the Mongolian Plateau from 2000 to 2020 [J]. Arid Land Geography, 2024, 47(9): 1577-1586.
[4]	XIA Tingting, XUE Xuan, WANG Haowei, XU Wenzhe, SHENG Ziyi, WANG Yang. Changes in terrestrial water storage and its drivers on the north slope of Kunlun Mountains [J]. Arid Land Geography, 2024, 47(8): 1292-1303.
[5]	ZHU Chenggang, CHEN Yaning, ZHANG Mingjun, CHE Yanjun, SUN Meiping, ZHAO Ruifeng, WANG Yang, LIU Yuting. Preliminary report on scientific investigation of water resources on the northern slope of Kunlun Mountains [J]. Arid Land Geography, 2024, 47(7): 1097-1105.
[6]	ZHANG Jing, MA Long, LIU Tingxi, SUN Bolin, QIAO Zixu. Reconstruction of the minimum temperature over the past 202 years based on tree rings of Picea crassifolia in the Helan Mountains [J]. Arid Land Geography, 2024, 47(6): 909-921.
[7]	FAN Jing, SHEN Yanbo, CHANG Rui. Impact of climate change on the selection of typical meteorological years in solar energy resource assessment [J]. Arid Land Geography, 2024, 47(6): 922-931.
[8]	LI Hui, LIU Tiejun, WANG Shaohui, LIU Dongwei. Spatial and temporal variation of water use efficiency and its influencing factors in desert steppe of Inner Mongolia from 2001 to 2021 [J]. Arid Land Geography, 2024, 47(6): 993-1003.
[9]	XIANG Yanyun, WANG Yi, CHEN Yaning, ZHANG Qifei, ZHANG Yujie. Prediction of future hydrological drought risk in the Yarkant River Basin based on CMIP6 models [J]. Arid Land Geography, 2024, 47(5): 798-809.
[10]	ZHAO Mingjie, WANG Ninglian, SHI Chenlie, HOU Jingqi. Temporal and spatial variations of lake ice phenology in large lakes of Central Asia from 2000 to 2020 [J]. Arid Land Geography, 2024, 47(4): 561-575.
[11]	WANG Shuzhi, WEN Deping. Attribution analysis of runoff change in the Datong River Basin, Qinghai-Tibet Plateau [J]. Arid Land Geography, 2024, 47(2): 203-213.
[12]	CHANG Xuexiang, ZHAO Wenzhi, TIAN Quanyan. Advances in climate change and its impact on the stability of mountain forest ecosystems and hydrological processes in arid regions [J]. Arid Land Geography, 2024, 47(2): 228-236.
[13]	CHEN Lihua, CHE Yanjun, CAO Yun, ZHANG Mingjun, GU Lailei, WU Jiakang, LYU Weiwei. Responses of glacier and lake to local climate change in the Jingyu Lake Basin, east Kunlun Mountains [J]. Arid Land Geography, 2024, 47(10): 1640-1650.
[14]	SUN Jinrong, LI Xing, WEI Jingting. Area change characteristics of Wuliangsuhai Lake driven by climate change and human activities in the basin in the past 40 years [J]. Arid Land Geography, 2024, 47(10): 1688-1699.
[15]	SUI Lu, YAN Zhiming, LI Kaifang, HE Peien, MA Yingjie, ZHANG Rucui. Prediction of habitat quality in the Ili River Valley under the influence of human activities and climate change [J]. Arid Land Geography, 2024, 47(1): 104-116.