Impacts of Urbanization on Extreme Climate Events in Sichuan-Chongqing Region

Guo Lei; Li Xiehui; Liu Yuting

doi:10.11898/1001-7313.20230506

Vol.34, NO.5, 2023

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Article Navigation > Journal of Applied Meteorological Science > 2023 > 34(5): 574-585

Guo Lei, Li Xiehui, Liu Yuting. Impacts of urbanization on extreme climate events in Sichuan-Chongqing region. J Appl Meteor Sci, 2023, 34(5): 574-585. DOI: 10.11898/1001-7313.20230506.

Citation:

Guo Lei, Li Xiehui, Liu Yuting. Impacts of urbanization on extreme climate events in Sichuan-Chongqing region. J Appl Meteor Sci, 2023, 34(5): 574-585. DOI: 10.11898/1001-7313.20230506.

Guo Lei, Li Xiehui, Liu Yuting. Impacts of urbanization on extreme climate events in Sichuan-Chongqing region. J Appl Meteor Sci, 2023, 34(5): 574-585. DOI: 10.11898/1001-7313.20230506.

Citation:

Guo Lei, Li Xiehui, Liu Yuting. Impacts of urbanization on extreme climate events in Sichuan-Chongqing region. J Appl Meteor Sci, 2023, 34(5): 574-585. DOI: 10.11898/1001-7313.20230506.

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Impacts of Urbanization on Extreme Climate Events in Sichuan-Chongqing Region

DOI: 10.11898/1001-7313.20230506

Guo Lei¹,
Li Xiehui^{1, 2
,
,},
Liu Yuting¹

1.
School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225
2.
Insitute of Arid Meteorology, CMA, Lanzhou 730020

Received Date: 2023-03-22
Rev Recd Date: 2023-06-25
Publish Date: 2023-09-30

Abstract

Abstract

Based on daily precipitation and temperature data as well as population, gross domestic product (GDP), land use and land cover change (LUCC), night lighting remote sensing data of 46 meteorological stations in Sichuan and Chongqing Region from 1971 to 2020, 21 extreme climate indices are calculated using RClimDex software, and the interannual variation trends of these indices are analyzed using linear trend method. The Mann-Kendall nonparametric method is used to test the significance levels of all indices. These meteorological stations are categorified to further investigate the impact of urbanization on extreme climate indices, especially the impact of urbanization on extreme climate events in Sichuan and Chongqing. It's found that the monthly maximum value of daily maximum temperature (TXx), maximum value of daily minimum temperature (TNx), minimum value of daily maximum temperature (TXn), minimum value of daily minimum temperature (TNn), summer days (SU25), occurrence of hot nights(TR20), warm nights (TN90P) and warm days (TX90P) all show an increasing trend in the last 50 years, while the frost days (FD0), cold nights (TN10P) and cold days (TX10P) show a decreasing trend, and the changes are all significant. The annual total precipitation in wet days (PRCPTOT), very heavy precipitation days (R25mm), very wet days (R95P), extremely wet days (R99P) and simple precipitation intensity index (SDII), which represent the extreme precipitation and the intensity of extreme precipitation, all show an increasing trend, indicating that the extreme high temperature and extreme precipitation in Sichuan and Chongqing Region have been increasing. The extreme indices show an increasing trend in all three types of meteorological sites. The increasing trend of TXx, TNx, TR20, TX90P and daily temperature range (DTR) are most obvious in urban stations, and FD0, TN10P, TX10P and DTR are most obvious in rural stations. Urbanization has basically no effects on TXx and TN90P at rural-urban sites, but has a greater effect on the monthly TXn, TNn, FD0, TR20 and DTR at rural and urban sites, as well as the number of TN10P and TN90P at urban sites. In Sichuan and Chongqing Region, among the rural sites, all indices show a significant increasing trend except for the monthly maximum 1-day precipitation (RX1DAY), monthly maximum 5-day precipitation (RX5DAY) and consecutive wet days (CWD), which show a non-significant decreasing trend. The influence of urbanization causes a decreasing trend in the number of heavy precipitation days (R10mm), R25mm, RX1DAY, RX5DAY, R95P and PRCPTOT in urban-rural and urban sites, and causes an increasing trend in SDII and CWD. The urbanization effects contribute 100.00% to R10mm, RX1DAY, RX5DAY, R95P and PRCPTOT for both urban-rural and urban sites.
- extreme temperature index;
- extreme precipitation index;
- urbanization impact;
- contribution rate of urbanization impact;
- Sichuan-Chongqing Region

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References(33)

Figures and Tables

Fig. 1 Geographical location and elevation(the shaded) of the target area

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Fig. 2 Time series of extreme temperature indices in Sichuan-Chongqing Region in 1971-2020

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Fig. 3 Time series of extreme temperature indices at different types of meteorological stations in Sichuan-Chongqing Region in 1971-2020

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Fig. 4 Time series of extreme precipitation indices in Sichuan-Chongqing Region in 1971-2020

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Fig. 5 Time series of extreme precipitation indices at different types of meteorological stations in Sichuan-Chongqing Region in 1971-2020

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Table 1 Definitions of extreme climate indices

指数类型	分类	名称	指数缩写	定义	单位
极端温度指数	极值指数	最高气温最大值	TXx	每月平均日最高气温最大值	℃
		最低气温最大值	TNx	每月平均日最低气温最大值	℃
		最高气温最小值	TXn	每月平均日最高气温最小值	℃
		最低气温最小值	TNn	每月平均日最低气温最小值	℃
	绝对指数	霜冻日数	FD0	一年中日最低气温小于0℃的日数	d
		夏季日数	SU25	一年中日最高气温大于25℃的日数	d
		热夜日数	TR20	一年中日最低气温大于20℃的日数	d
	相对指数	冷夜日数	TN10P	日最低气温小于10%分位值的日数	d
		冷昼日数	TX10P	日最高气温小于10%分位值的日数	d
		暖夜日数	TN90P	日最低气温大于90%分位值的日数	d
		暖昼日数	TX90P	日最高气温大于90%分位值的日数	d
	其他指数	月平均日较差	DTR	日最高气温和日最低气温之差的月平均值	℃
极端降水指数	绝对指数	中雨日数	R10mm	日降水量大于10 mm的日数	d
		大雨日数	R25mm	日降水量大于25 mm的日数	d
		1 d最大降水量	RX1DAY	一年中最大日降水量	mm
		5 d最大降水量	RX5DAY	一年中连续5 d最大日降水量	mm
	相对指数	强降水量	R95P	日降水量大于95%分位值的年累积降水量	mm
		特强降水量	R99P	日降水量大于99%分位值的年累积降水量	mm
		降水强度	SDII	年降水量与湿日日数(日降水量大于1 mm)的比值	mm·d^-1
	持续指数	持续湿期	CWD	日降水量大于1 mm的最大持续降水日数	d
	其他指数	年降水量	PRCPTOT	日降水量大于1 mm的日累积量值	mm

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Table 2 Interdecadal change rates of extreme temperature indices in Sichuan-Chongqing Region

分类	指数	变化率
极值指数	最高气温最大值	0.37℃·(10 a)^-1
	最低气温最大值	0.24℃·(10 a)^-1
	最高气温最小值	0.35℃·(10 a)^-1
	最低气温最小值	0.37℃·(10 a)^-1
绝对指数	霜冻日数	-2.68 d·(10 a)^-1
	夏季日数	3.82 d·(10 a)^-1
	热夜日数	1.67 d·(10 a)^-1
相对指数	冷夜日数	-3.24 d·(10 a)^-1
	冷昼日数	-1.85 d·(10 a)^-1
	暖夜日数	2.97 d·(10 a)^-1
	暖昼日数	3.39 d·(10 a)^-1
其他指数	月平均日较差	0.02℃·(10 a)^-1^*
注：*表示达到0.1显著性水平，未标注表示达到0.01显著性水平。

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Table 3 Urbanization effects of extreme temperature indices

分类	指数	A₁	A₂	A₃	ΔA₂₁	ΔA₃₁	E₂₁/%	E₃₁/%
极值指数	最高气温最大值	0.36	0.35	0.41	0.01	0.05	2.44	12.20
	最低气温最大值	0.23	0.19	0.30	-0.05	0.06	13.33	23.33
	最高气温最小值	0.35	0.45	0.25^**	0.10	-0.10	40.00	40.00
	最低气温最小值	0.51	0.45	0.14^**	-0.06	-0.37	42.86	100.00
绝对指数	霜冻日数	-4.41	-2.99	-0.65	1.42	3.76	100.00	100.00
	夏季日数	3.29	4.11	4.05	0.82	0.76	20.25	18.77
	热夜日数	0.45	1.76	2.80	1.31	2.35	46.79	83.93
相对指数	冷夜日数	-3.81	-3.30	-2.60	0.51	1.21	19.62	46.54
	冷昼日数	-2.07	-1.97	-1.50	0.10	0.57	6.67	38.00
	暖夜日数	3.28	3.31	2.31	-0.03	-0.97	1.30	41.99
	暖昼日数	2.88	3.63	3.67	0.75	0.79	20.44	21.53
其他指数	月平均日较差	-0.04^***	0.05^**	0.06^**	0.09	0.01	100.00	100.00
注：表示达到0.05显著性水平，*表示未达到0.05显著性水平，未标注表示达到0.01显著性水平。

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Table 4 Interdecadal change rates of extreme precipitation indices in Sichuan-Chongqing Region

分类	指数	变化率
绝对指数	中雨日数	0.14 d·(10 a)^-1
	大雨日数	0.15 d·(10 a)^-1 ^**
	1 d最大降水量	-0.03 mm·(10 a)^-1
	5 d最大降水量	-0.22 mm·(10 a)^-1
相对指数	强降水量	3.63 mm·(10 a)^-1^*
	特强降水量	2.75 mm·(10 a)^-1^*
	降水强度	0.08(mm ·d)^-1·(10 a)^-1^*
持续指数	持续湿期	-0.08 d·(10 a)^-1
其他指数	年降水量	2.77 mm·(10 a)^-1^*
注：和*分别表示达到0.1，0.05显著性水平。

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Table 5 Urbanization effects of extreme precipitation indices

分类	指数	A₁	A₂	A₃	ΔA₂₁	ΔA₃₁	E₂₁/%	E₃₁/%
绝对指数	中雨日数	0.51^**	-0.09	0.01	-0.60	-0.50	100.00	100.00
	大雨日数	0.21^***	0.15^*	0.08	-0.06	-0.13	75.00	100.00
	1 d最大降水量	0.57^***	-0.43	-0.24	-1.00	-0.81	100.00	100.00
	5 d最大降水量	1.13^*	-1.14	-0.64	-2.27	-1.77	100.00	100.00
相对指数	强降水量	7.85^***	1.84	11	-6.01	-6.65	100.00	100.00
	特强降水量	3.15^***	-0.94	6.04	-4.09	2.89	67.72	47.85
	降水强度	0.07^***	0.09^**	0.09	0.02	0.02	22.22	22.22
持续指数	持续湿期	-0.09	-0.07	-0.08	0.02	0.01	25.00	12.50
其他指数	年降水量	5.62^**	3.17	-0.47	-2.45	-6.09	100.00	100.00
注：，和**分别表示达到0.1，0.05和0.01显著性水平。

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