Electronic Supplementary Material
Assessment of urban effect on observed warming trends during 1955-2012 over China:
a case of 45 cities
Climatic Change
Kai Jin a, Fei Wang a, b, c *, Deliang Chen d, Qiao Jiao b, Lei Xia c, e, Luuk Fleskens f, g, Xingmin Mu a, b, c
a Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, Shaanxi, China
b College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, Shaanxi, China
c Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of water Resources, Yangling 712100, Shaanxi, China
d Department of Earth Sciences, University of Gothenburg, Box 460, 405 30 Gothenburg, Sweden
e University of Chinese Academy of Sciences, Beijing 100049, China
f Soil Physics and Land Management Group, Wageningen University, P.O. Box 47, 6700AA, Wageningen, The Netherlands
g Sustainability Research Institute, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
E-mail: Mr. Kai Jin (jinkai-2014@foxmail.com) and corresponding author, Dr. Fei Wang (wafe@ms.iswc.ac.cn)
Contents
SI-1 Meteorological stations and corresponding cities ........................................................................................... 2
SI-2 Trends of annual mean temperature of each meteorological stations in 1955-2012 .................................... 4
SI-3 Urban impact indicators (Uii) in China ........................................................................................................... 6
SI-4 Urban warming and their contribution to total warming for each station .................................................. 7
Abbreviations and nomenclatures
Au
Urban area: Built-up land area, in km2
Dir
Direction: Direction of meteorological station relative to city center, 16 azimuth
Dis
Distance: the distance from meteorological station to city center, in km
NDVI
Normalized Difference Vegetation Index, unitless
OLS
Operational Linescan System
PC
Principal component
PCA
Principal Component Analysis
Pop
Population: non-agricultural population, in million
R
Radius: the radius of city shape simplified as circle, in km
Rd
Distance coefficient: the ratio of Dis and R, unitless
Tmax
Annual mean daily maximum temperature, in °C
Tmean
Annual mean daily temperature, in °C
Tmin
Annual mean daily minimum temperature, in °C
UHI
Urban Heat Island
Uii
Urban impact indicator: the degree of the urbanization impact on the recorded surface temperature, in %
ESM
Electronic Supplemental Material
1
SI-1 Meteorological stations and corresponding cities
The characters of the 45 meteorological stations and corresponding cities are listed in Table S1.
We generalizes the urban area with NDVI to determine the city centers taking account of the fact that vegetation
coverage in the northwestern and northern parts of China is low, yet in small cities (Pop less than 0.50 Million) it is high.
Wang et al. (2006) showed that the mean NDVI of Beijing urban region varied from 0.27 to 0.39 during the period 1984
to 2004. Therefore, the following threshold values of NDVI for city areas were determined: NDVI ranging from 0.2 to
0.3 for the six cities in the northwest, for the 6 small cities in other regions ranging from 0.2 to 0.5, and for the other 33
cities ranging from 0.2 to 0.4.
Table S1 Meteorological stations and corresponding cities
Pop
Au
Dis
R
(million)
(km2)
(km)
(km)
Baoding (BD)
0.93
100
2.8
Baotou (BT)
1.15
178
Beijing (BJ)
8.79
Changchun (CC)
Rd
Na
NDVI
5.6
0.5
1
3.1
7.5
0.4
1226
17.4
19.8
2.51
267
11.0
Changde (CD)
0.50
65
Chifeng (CF)
0.52
Dalian(DL)
Name (abbr.)
Dir
Latitude Longitude
(16 azimuth)
(°N) b
(°E) b
0.2-0.4
E
38.85
115.52
1
0.2-0.3
E
40.67
109.85
0.9
1
0.2-0.4
SE
39.80
116.47
9.2
1.2
2
0.2-0.4
W
43.90
125.22
2.9
4.5
0.6
1
0.2-0.5
NW
29.05
111.68
72
0.9
4.8
0.2
1
0.2-0.4
W
42.27
118.93
2.48
258
19.9
9.1
2.2
2
0.2-0.4
E
38.90
121.63
Datong (DT)
1.15
91
4.4
5.4
0.8
1
0.2-0.3
E
40.10
113.33
Guangzhou (GZ)
4.91
780
11.7
15.8
0.7
1
0.2-0.4
NE
23.17
113.33
Guiyang (GY)
1.51
132
2.2
6.5
0.3
1
0.2-0.4
E
26.58
106.73
Haikou (HK)
0.90
91
10.1
5.4
1.9
2
0.2-0.4
SW
20.00
110.25
Hangzhou (HZ)
2.56
327
8.6
10.2
0.8
1
0.2-0.4
S
30.23
120.17
Hanzhong (HZg)
0.25
31
0.4
3.1
0.1
1
0.2-0.5
S
33.07
107.03
Harbin (HB)
3.41
331
11.3
10.3
1.1
1
0.2-0.4
E
45.75
126.77
Hefei (HF)
1.61
225
8.7
8.5
1.0
2
0.2-0.4
SE
31.78
117.30
Hohhot (HH)
0.84
150
1.7
6.9
0.2
1
0.2-0.4
E
40.82
111.68
Huiyang (HY)
1.18
94
1.4
5.5
0.3
1
0.2-0.4
E
23.08
114.42
Jinan (JN)
2.77
305
10.4
9.9
1.1
1
0.2-0.4
SE
36.60
117.05
Kunming (KM)
1.72
233
10.8
8.6
1.3
1
0.2-0.4
SW
25.00
102.65
Liuzhou (LZ)
0.89
110
3.5
5.9
0.6
1
0.2-0.4
N
24.35
109.40
Mianyang (MY)
0.61
80
4.1
5.0
0.8
1
0.2-0.4
SW
31.45
104.73
Nanchang (NC)
1.74
109
6.6
5.9
1.1
2
0.2-0.4
S
28.60
115.92
2
Table S1 (continued)
Pop
Au
Dis
R
(million)
(km2)
(km)
(km)
Nanjing (NJ)
4.47
575
8.0
Nanyang (NY)
0.55
77
Qinzhou (QZ)
0.20
Qiqihar (QH)
Rd
Na
NDVI
13.5
0.6
1
6.4
5.0
1.3
34
2.8
3.3
1.11
135
9.6
Rizhao (RZ)
0.60
61
Shantou (ST)
4.88
Shenyang (SY)
Name (abbr.)
Dir
Latitude Longitude
(16 azimuth)
(°N) b
(°E) b
0.2-0.4
SE
32.00
118.80
1
0.2-0.4
NE
33.03
112.58
0.9
1
0.2-0.5
SE
21.95
108.62
6.6
1.5
1
0.2-0.4
NW
47.38
123.92
4.0
4.4
0.9
1
0.2-0.4
NW
35.43
119.53
170
8.7
7.4
1.2
3
0.2-0.4
N
23.40
116.68
4.44
325
14.8
10.2
1.5
1
0.2-0.4
SE
41.73
123.52
Shijiazhuang (SJ)
2.31
175
9.9
7.5
1.3
1
0.2-0.4
W
38.03
114.42
Tangshan (TS)
1.63
209
6.4
8.2
0.8
1
0.2-0.4
NW
39.67
118.15
Urumchi (UM)
1.58
236
3.9
8.7
0.4
1
0.2-0.3
SE
43.78
87.65
Weifang (WF)
0.98
123
8.5
6.3
1.4
1
0.2-0.4
NE
36.75
119.18
Wuhan (WH)
4.45
425
20.9
11.6
1.8
1
0.2-0.4
W
30.62
114.13
Wuwei (WW)
0.21
25
3.2
2.8
1.1
1
0.2-0.3
SE
37.92
102.67
Xiamen (XM)
1.09
127
10.0
6.4
1.6
3
0.2-0.4
NW
24.48
118.07
Xining (XN)
0.91
64
13.8
4.5
3.1
1
0.2-0.4
N
36.72
101.75
Xinyang (XY)
0.44
48
5.2
3.9
1.3
1
0.2-0.5
W
32.13
114.05
Yichang (YCg)
0.70
71
2.4
4.8
0.5
1
0.2-0.4
E
30.70
111.30
Yichun (YCn)
0.26
32
5.1
3.2
1.6
1
0.2-0.5
NE
27.80
114.38
Yinchuan (YC)
0.71
106
8.0
5.8
1.4
2
0.2-0.3
W
38.48
106.22
Yueyang (YY)
0.94
78
6.3
5.0
1.3
1
0.2-0.4
NW
29.38
113.08
Yulin (YL)
0.16
74
5.2
4.9
1.1
1
0.2-0.3
SE
38.27
109.78
Yuxi (YX)
0.14
21
2.9
2.6
1.1
1
0.2-0.4
SE
24.33
102.55
Zhengzhou (ZZ)
1.93
282
6.4
9.5
0.7
1
0.2-0.4
S
34.72
113.65
Note: a is the number of city centers (N); b is the Latitude and Longitude of the meteorological stations.
Table S2 Descriptive statistics of selected characteristics of 45 meteorological stations and cities
Au (km2)
Pop (million)
Dis (km)
R (km)
Rd
Mean
193.96
1.72
7.25
7.10
1.03
Median
123.00
1.11
6.40
6.30
1.10
Standard deviation
216.93
1.72
4.87
3.43
0.57
Minimum (City)
21.00 (YX)
0.14 (YX)
0.40 (HZ)
2.60 (YX)
0.10 (HZ)
Maximum (City)
1226.00 (BJ)
8.79 (BJ)
20.90 (WH)
19.80 (BJ)
3.10 (XN)
Coefficient of variation
1.12
0.99
0.67
0.48
0.56
3
SI-2 Trends of annual mean temperature of each meteorological stations in 1955-2012
The trends of Tmean, Tmin and Tmax of the 45 stations were detected by linear regressions between temperature and
year using observed temperature data in 1955-2012 (Table 1 and Fig. S1).
Generally, the temperature increase in 1955-2012 over the China except for GY (decreasing). The warming trends
become weaker from the north part to the south part of China. The change rate of Tmin is bigger than that of Tmean, and
the change rate of Tmax is relatively low.
4
Fig. S1 Trends of annual mean temperature of each meteorological stations in 1955-2012
(a, b, c depict annual mean daily temperature, annual mean daily minimum temperature and annual mean daily
maximum temperature, respectively)
5
SI-3 Urban impact indicators (Uii) in China
The Urban impact indicators (Uii) of the 45 stations were calculated using the formulae shown in Fig. 2 (Fig. S2). The
mean Uii of all stations is 11.2% (Table 1), but it varies greatly among the cities with a coefficient of variation of 0.81.
The difference of Uii between stations is very large from 1.0% (minimum in YX) to 38.2% (maximum in BJ).
Fig. S2 Urban impact indicators (Uii) of the 45 meteorological stations in China
(According to the Uii of 45 meteorological stations included in this study, the impact of urbanization is divided into five levels:
marginal impact (Uii < 5%), slight impact (5% ≤ Uii < 10%), medium impact (10% ≤ Uii < 15%), evident impact (15% ≤ Uii < 25%),
and severe impact (Uii ≥ 25%))
6
SI-4 Urban warming and their contribution to total warming for each station
The Urban warming here (Y, in °C per decade, Table S3) is the warming rate caused by urbanization (indicated as Uii,
in %). The regression equations here are from Fig.4 (constants are set as 0), and as below:
YTmin = 0.48 * X
(S1)
YTmean = 0.41 * X
(S2)
The contribution of urbanization to the total warming (in %, Table S3) is the proportion of Urban warming (in °C per
decade) in temperature change trend (in °C per decade) of each meteorological station (formula S3) as below.
Contribution = Y/Trend * 100%
(S3)
Table S3 Magnitude of urban warming and their contribution to total warming for each station
Name (abbr.)
Urban warming
Contribution
(°C per decade)
(%)
Name (abbr.)
Tmin
Tmean
Tmin
Tmean
Baoding (BD)
0.07
0.06
14.30
20.50
Baotou (BT)
0.09
0.08
16.59
Beijing (BJ)
0.18
0.16
Changchun (CC)
0.02
Changde (CD)
Urban warming
Contribution
(°C per decade)
(%)
Tmin
Tmean
Tmin
Tmean
Nanyang (NY)
0.03
0.02
7.99
14.45
18.45
Qinzhou (QZ)
0.04
0.03
15.92
15.63
34.61
39.17
Qiqihar (QH)
0.02
0.01
3.62
4.25
0.02
4.21
5.05
Rizhao (RZ)
0.03
0.03
13.47
10.18
0.05
0.04
15.99
18.41
Shantou (ST)
0.05
0.04
17.84
15.24
Chifeng (CF)
0.06
0.05
19.07
20.20
Shenyang (SY)
0.03
0.03
20.97
14.75
Dalian(DL)
0.03
0.03
9.91
9.64
Shijiazhuang (SJ)
0.03
0.02
4.62
6.38
Datong (DT)
0.06
0.05
21.44
18.31
Tangshan (TS)
0.09
0.08
28.70
29.05
Guangzhou (GZ)
0.11
0.10
56.05
53.20
Urumchi (UM)
0.12
0.10
27.75
36.40
Guiyang (GY)
0.06
0.05
100
100
Weifang (WF)
0.01
0.01
6.66
7.20
Haikou (HK)
0.01
0.01
3.94
4.96
Wuhan (WH)
0.03
0.02
6.28
7.86
Hangzhou (HZ)
0.14
0.12
41.69
37.84
Wuwei (WW)
0.03
0.02
7.49
6.96
Hanzhong (HZg)
0.04
0.04
15.53
18.85
Xiamen (XM)
0.01
0.01
22.53
24.06
Harbin (HB)
0.10
0.09
20.10
20.85
Xining (XN)
0.01
0.01
11.90
5.65
Hefei (HF)
0.03
0.03
12.44
11.60
Xinyang (XY)
0.01
0.01
4.47
5.52
Hohhot (HH)
0.09
0.08
14.02
15.64
Yichang (YCg)
0.04
0.04
23.46
32.80
Huiyang (HY)
0.07
0.06
22.84
31.21
Yichun (YCn)
0.01
0.01
2.53
3.85
Jinan (JN)
0.04
0.03
17.62
26.62
Yinchuan (YC)
0.02
0.02
5.34
5.26
Kunming (KM)
0.03
0.02
5.46
6.85
Yueyang (YY)
0.02
0.02
6.79
8.85
Liuzhou (LZ)
0.07
0.06
25.70
37.05
Yulin (YL)
0.05
0.04
12.62
14.01
Mianyang (MY)
0.06
0.05
26.75
45.69
Yuxi (YX)
0.00
0.00
1.91
2.23
Nanchang (NC)
0.03
0.02
11.71
13.34
Zhengzhou (ZZ)
0.11
0.10
30.95
37.62
Nanjing (NJ)
0.17
0.15
57.96
59.41
Reference:
Wang W, Shen W, Liu X (2006) Research on the relation of the urbanization and urban heat island effect changes in Beijing based on
remote sensing. Research of Environmental Sciences 19:44-48. doi:10.3321/j.issn:1001-6929.2006.02.014
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