Urban Heat Island

1. ORIGINAL PAPER
Assessing population movement impacts on urban heat island
of Beijing during the Chinese New Year holiday: effects
of meteorological conditions
Lingyun Wu1
& Jingyong Zhang2,3
Received: 12 April 2016 /Accepted: 16 January 2017
# Springer-Verlag Wien 2017
Abstract Chinese New Year (CNY), or Spring Festival, is the
most important of all festivals in China. We use daily obser-
vations to show that Beijing’s urban heat island (UHI) effects
largely depend on precipitation, cloud cover, and water vapor
but are insensitive to wind speed, during the CNY holiday
season. Non-precipitating, clear, and low humidity conditions
favor strong UHI effects. The CNY holiday, with some 3
billion journeys made, provides a living laboratory to explore
the role of population movements in the UHI phenomenon.
Averaged over the period 2004–2013, with the Olympic year
of 2008 excluded, Beijing’s UHI effects during the CNY week
decline by 0.48 °C relative to the background period (4 weeks
including 2 to 3 weeks before, and 2 to 3 weeks after, the CNY
week). With combined effects of precipitation, large cloud
cover, and high water vapor excluded, the UHI effects during
the CNY week averaged over the study period decline by
0.76 °C relative to the background period, significant at the
99% confidence level by Student’s t test. These results indi-
cate that the impacts of population movements can be more
easily detected when excluding unfavorable meteorological
conditions to the UHI. Population movements occur not only
during the CNY holiday, but also during all the time across the
globe. We suggest that better understanding the role of
population movements will offer new insight into anthropo-
genic climate modifications.
1 Introduction
Human society has entered an urban era, with the majority of
the world’s population dwelling in cities (UN DESA 2014).
The built-up environment, impervious surfaces formed of
man-made materials, and the heat released by human activities
tend to make urban areas warmer than their surroundings—a
phenomenon called the urban heat island (UHI) (Howard
1833; Oke 1982; Kalnay and Cai 2003; Grimm et al. 2008;
Rosenzweig et al. 2009; Oleson et al. 2011; Georgescu et al.
2013; Myhre et al. 2013). UHIs occur in almost all city areas
and can generate both beneficial and adverse impacts (Taha
1997; Bonan 2008; Ren et al. 2008; Weaver et al. 2009;
Stewart and Oke 2012; Wu and Yang 2013; Zhao et al.
2014; Bounoua et al. 2015; Sachindra et al. 2015). The UHI
intensity varies across and within cities, with time, and with
meteorological conditions, including precipitation, cloud, air
humidity, and wind (Arnfield 2003; Li et al. 2004; Zhou et al.
2004; Jin et al. 2005; Mahmood et al. 2014; Martin-Vide et al.
2015; Mirzaei 2015; Taha 2015).
Beijing, located in North China, is one of the most popu-
lous cities in the world. Beijing’s population is close to 22
million in 2015 and is projected to be 28 million by 2030
(UN DESA 2014). Spatial and temporal features of Beijing’s
UHI have been widely addressed in previous studies (Zhang
et al. 2002; Chu and Ren 2005; Ren et al. 2007; Miao et al.
2009; Yan et al. 2010; Yang et al. 2013). The UHI intensity
expressed as surface air temperature difference has been found
to be strongest in winter (Liu et al. 2007; Zhang et al. 2010;
Yang et al. 2013). However, little attention is paid to how
Beijing’s UHI changes with the meteorological conditions.
* Jingyong Zhang
zjy@mail.iap.ac.cn
1
State Key Laboratory of Numerical Modeling for Atmospheric
Sciences and Geophysical Fluid Dynamics (LASG), Institute of
Atmospheric Physics, Chinese Academy of Sciences,
Beijing 100029, China
2
Center for Monsoon System Research, Institute of Atmospheric
Physics, Chinese Academy of Sciences, Beijing 100029, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
Theor Appl Climatol
DOI 10.1007/s00704-017-2043-7

2. In China, hundreds of millions of people leave the large
cities for their hometowns to celebrate the Chinese New Year
(CNY), and then return after the CNY holiday. The population
movements around the CNY, involving some 3 billion jour-
neys, represent the largest annual human migration event on
the planet. Several recent studies have detected significant
impacts of this mass human migration on the UHI effects
during the CNY holiday (Wu et al. 2015; Zhang et al. 2015;
Zhang and Wu 2015). However, how the effects of mass hu-
man migration on the UHI relate to meteorological conditions
remains a key unknown.
In this study, we investigate the dependence of Beijing’s
UHI on meteorological conditions and further explore the role
of meteorological conditions in assessing the impacts of mass
human migration on Beijing’s UHI during the CNY holiday.
We focus on the period 2004–2013 but exclude the Olympic
year of 2008 to avoid any possible effects of implemented
environmental control measures in this year.
2 Data and methods
The surface air temperature, precipitation, cloud cover, water
vapor, and wind speed data used in this study were obtained
from the China Meteorological Administration (http://data.
cma.cn/site/index.html). All the data were collected, quality
controlled, and processed by the National Meteorological
Information Center of the China Meteorological
Administration. The daily mean surface air temperature,
cloud cover, water vapor, and wind speed values were
produced by averaging measurements at 0200, 0800, 1400,
and 2000 LST.
The UHI intensity (ΔT) was calculated as daily mean sur-
face air temperature difference between urban (Turban) and
non-urban reference (Treference) stations.
ΔT ¼ Turban−Treference; ð1Þ
Urban areas of Beijing are mainly located on the southeast
plain of the city which occupies nearly 40% of the total area
and is surrounded by mountains on its northeast, north, and
west sides (Fig. 1). The urban station used in this study
[Beijing (39°48′N, 116°28′E)] is located in the southeastern
part of urban center, which is one of the most populous areas
of the city (Fig. 1). The non-urban reference station [Miyun
(40°23′N, 116°52′E)] is situated in the northeastern part of
Beijing, with a much lower population density (Yang 2015).
Miyun station has been used to represent non-urban or rural
areas in previous studies (Liu et al. 2007; Wang et al. 2013;
Zhang et al. 2015). The altitudes of Beijing and Miyun sta-
tions are 31.3 and 71.8 m, respectively. The Beijing and
Miyun stations both have no relocations in our study period
and are the only two national basic meteorological stations in
the plain areas of Beijing.
Since Beijing’s UHI effects and population movements
during the CNY holiday are both larger in recent years than
before, the study focuses on the period of 2004 to 2013, ex-
cluding 2008 to avoid any possible effects of environmental
control measures implemented in the Olympic year. The date
of the CNY is set according to the lunar calendar and falls
between 22 January and 18 February during the study period.
The CNY day is denoted as day(+1), the day before and after
as day(−1) and day(+2), and so on. The CNY week includes
7 days from CNY itself to 6 days after. In this paper, the CNY
week is referred to as week (+1), with 1 week before and after
being week(−1) and week(+2), and so on. The analysis covers
day(−21) to day(+28) or week(−3) to week(+4) for each study
year. In total, there are 441 days for the period of 2004–2013,
excluding the Olympic year of 2008. The background period
is defined as 2 to 3 weeks before and 2 to 3 weeks after the
CNY week [week(−3) to week(−2) and week(+3) to week(+
4)]. The dates of the CNY, the CNY week and the background
period are provided in Table 1. Precipitation and wind speed
data have no missing values for the analysis period. There are
the missing data for surface air temperature and water vapor
on the date of January 29, 2013 and cloud cover on the date of
February 23, 2011. We exclude the 2 days which are both
during the background period in all our analyses and use the
data for 439 days in total (Table 2).
3 Results
First, we examine differences in the ΔT between precipitating
days and non-precipitating days during the CNY holiday sea-
son (day(−21) to day(+28)), averaged over the study period
(i.e., 2004–2013, excluding the Olympic year of 2008). A
Fig. 1 Locations of Beijing and Miyun stations and the topography(m)
of Beijing. The three circles represent the second, fourth, and sixth Ring
Roads in Beijing. The red square denotes the urban center of Beijing
L. Wu, J. Zhang

3. precipitating day is defined as the one with the daily precipi-
tation amount at any one or both of urban and non-urban
reference stations meeting or exceeding 0.1 mm. There are
48 precipitating days and 391 non-precipitation days for the
whole study period (Table 2). The averaged ΔT is 1.07 °C on
precipitating days, which is 1.42 °C and 57% smaller than on
non-precipitating days in absolute and relative terms, respec-
tively. These results indicate that precipitation plays an impor-
tant role in influencing the UHI intensity during the CNY
holiday season.
We then analyze relationships of the ΔT to daily mean
cloud cover, water vapor, and wind speed averaged at urban
and non-urban reference stations during the CNY holiday sea-
son over the study period (Figs. 2, 3 and 4). Generally speak-
ing, the ΔT has close associations with cloud cover and water
vapor: it near-linearly decreases with increasing cloud cover
and water vapor (Figs. 2 and 3). For all years combined over
the study period, correlations of the ΔT with cloud cover and
water vapor are −0.55 and −0.46, respectively, both statistical-
ly significant at the 99% confidence level. For each year of the
study period, the associations of the ΔT with cloud cover and
water vapor are also generally strong, with the correlation
coefficients ranging from −0.27 to −0.73 and from −0.23 to
−0.63, respectively.
For all years combined, the correlation coefficients be-
tween the ΔTand wind speed during the CNY holiday season
are near zero (−0.03). For each year of the study period, the
correlation coefficients are generally very small, ranging from
−0.2 to 0.09 (Fig. 4). These results indicate that the association
of the UHI intensity with the wind speed is quite weak during
the CNY holiday season.
The strong dependence of the ΔTon cloud cover and water
vapor during the CNY holiday season also shows up in Fig. 5,
which examines the ΔT bins according to different meteoro-
logical conditions during the study period. Clearly, the ΔT
decreased with increasing cloud cover and water vapor during
the CNY holiday season. For 15% largest cloud cover (>85%)
and 15% highest water vapor (>3.7 hPa), the ΔT values are
1.12 and 1.26 °C, respectively. They are both much smaller
than the mean ΔTwhich is 2.34 °C. In contrast, the ΔTalmost
has no dependence on wind speed. It should be noted that the
higher altitude at the non-urban reference station than at the
urban station may result in the overestimation of Beijing’s
UHI intensity. Such an effect is expected to be limited regard-
ing a difference of about 40 m (~0.26 °C assuming the tem-
perature decreases with an increase of altitude at the lapse rate
of 0.65 °C per 100 m, Memon et al. 2011) and might be offset
by the effect of the urbanization development surrounding the
non-urban reference station.
The above results indicate that the ΔT strongly depends on
the meteorological conditions including precipitation, cloud
cover, and water vapor during the CNY holiday season. It is
Table 1 Dates of the Chinese New Year (CNY), the CNY week, and the background period during 2004–2013, with the Olympic year of 2008
excluded
Year CNY day CNY week Background period
(before the CNY week)
Background period
(after the CNY week)
2004 22 January 22–28 January 1–14 January 5–18 February
2005 9 February 9–15 February 19 January to 1 February 23 February to 8 March
2006 29 January 29 January to 4 February 8–21 January 12–25 February
2007 18 February 18–24 February 28 January to 10 February 4–17 March
2009 26 January 26 January to1 February 5–18 January 9–22 February
2010 14 February 14–20 February 24 January to 6 February 28 February to 13 March
2011 3 February 3–9 February 13–26 January 17 February to 2 March
2012 23 January 23–29 January 2–15 January 6–19 February
2013 10 February 10–16 February 20 January to 2 February 24 February to 9 March
Table 2 All days analyzed in the
study, precipitating days, large
cloud cover days (>85%), and
high water vapor days (>3.7 hpa)
during the whole study period, the
CNY weeks, and the background
period
Period All days Precipitating days Large cloud cover days High water vapor days
Study period 439 48 68 (15%) 68 (15%)
CNY weeks 63 4 5 6
Background period 250 30 32 41
A precipitating day is defined as the one with the daily precipitation amount at any one or both of urban and non-
urban reference stations meeting or exceeding 0.1 mm. Daily cloud cover and water vapor are averaged at urban
and non-urban reference stations. The background period is defined as 4 weeks, including 2 weeks before
[week(−3) to week(−2)] and after [week(+3) to week(+4)] the CNY week
Population movements and UHI

4. estimated that nearly half of Beijing’s urban population
returned their hometowns to celebrate the CNY in recent
years. Finally, we examine the role of meteorological condi-
tions in assessing the impacts of mass human migration on
Beijing’s UHI during the CNY holiday.
We compare the ΔT differences between the CNY week
and the background period in five cases: all days; precipitating
days excluded; large cloud cover (>85%) days excluded; high
water vapor (>3.7 hPa) days excluded; and precipitating days,
large cloud cover (>85%) days, and high water vapor
Fig. 3 Scatter plots and linear
regressions between the ΔT and
daily mean water vapor averaged
at urban and non-urban reference
stations during the CNY holiday
season [day(−21) to day(+28)] for
the period 2004–2013, with the
Olympic year of 2008 excluded.
The CNY day is denoted as day(+
1), while 1 day before and after
the CNY day as day(−1) and
day(+2), and so on
Fig. 2 Scatter plots and linear
regressions between the ΔT and
daily mean cloud cover averaged
at urban and non-urban reference
stations during the CNY holiday
season [day(−21) to day(+28)] for
the period 2004–2013, with the
Olympic year of 2008 excluded.
The CNY day is denoted as day(+
1), while 1 day before and after
the CNY day as day(−1) and
day(+2), and so on
L. Wu, J. Zhang

5. (>3.7 hPa) days excluded (Fig. 6). A total of 4, 5, and 6 days
during the CNY weeks and 30, 32, and 41 days during the
background period are excluded for precipitation, large cloud
cover, and high water vapor, respectively (Table 2). There are
11 days during the CNY weeks and 68 days during the back-
ground period excluded for all unfavorable meteorological
conditions including precipitation, large cloud cover, and high
water vapor. Since two or three events happened concurrently
on some days, the days excluded for all unfavorable
meteorological conditions are less than the sum of the days
excluded for precipitation, large cloud cover, and high water
vapor. Under all meteorological conditions (all days case), the
ΔT values in the CNY week and the background period are
2.07 and 2.55 °C, respectively. The ΔT decreases by 0.48 °C
in the CNY week relative to the background period, signifi-
cant at the 98% confidence level by Student’s t test. With
precipitating days, large cloud cover days and high water va-
por days excluded, the ΔT values decrease by 0.61, 0.60, and
Fig. 4 Scatter plots and linear
regressions between the ΔT and
daily mean wind speed averaged
at urban and non-urban reference
stations during the CNY holiday
season [day(−21) to day(+28)] for
the period 2004–2013, with the
Olympic year of 2008 excluded.
The CNY day is denoted as day(+
1), while 1 day before and after
the CNY day as day(−1) and
day(+2), and so on
Fig. 5 The ΔT binned according to cloud cover, water vapor, and wind
speed values during the CNY holiday season [day(−21) to day(+28)] for
the period 2004–2013, with the Olympic year of 2008 excluded. The
CNY day is denoted as day(+1), while 1 day before and after the CNY
day as day(−1) and day(+2), and so on. The data are partitioned into 10
ranges (X-axis) with 0–1, 1–15, and so on for cloud cover (%), 0–1, 1–1.6
and so on for water vapor (hpa), and 0–1.5, 1.5–1.7, and so on for wind
speed (m/s). No water vapor and wind speed values are larger than 10 hpa
and 10 m/s, respectively
Population movements and UHI

6. 0.65 °C in the CNY week relative to the background period,
respectively. These changes are all significant at the 99% con-
fidence level. They are 0.12 ~ 0.17 °C stronger than under all
meteorological conditions. With all unfavorable meteorologi-
cal conditions including precipitation, large cloud cover, and
high water vapor excluded, the ΔT decreases by 0.76 °C in the
CNY week relative to the background period, significant at
the 99% confidence level. This reduction is 0.28 °C and 58%
stronger than those under all meteorological conditions in rel-
ative and absolute terms, respectively.
4 Conclusions and discussion
CNYis the most important and ceremonious of all the Chinese
festivals and holidays. The present study shows that Beijing’s
UHI effects depend strongly on meteorological conditions in-
cluding precipitation, cloud cover, and water vapor during the
CNY holiday season. The UHI effects are much weaker on
precipitating days than on non-precipitating days and near-
linearly decrease with increasing cloud cover and water vapor.
We further examine the role of mass human migration in
the UHI phenomenon under different meteorological condi-
tions. ΔT in the CNY week decreases by 0.48 °C relative to
the background period under all meteorological conditions.
When excluding precipitation days, large cloud cover days,
and high water vapor days, the ΔT reductions in the CNY
week are 0.61, 0.60, and 0.65 °C, respectively. These changes
are all stronger than that under all meteorological conditions.
The ΔT difference between the CNY week and the back-
ground period is −0.76 °C when excluding all unfavorable
meteorological conditions including precipitation, large cloud
cover, and high water vapor, representing 0.28 °C and 58%
reductions in absolute and relative terms compared with those
under all meteorological conditions.
Previous several studies provided observational evidence
for the impacts of population movements on the UHI (Wu
et al. 2015; Zhang et al. 2015; Zhang and Wu 2015). In this
study, we take Beijing as an example to show that the role of
population movements can be more easily detected when tak-
ing meteorological conditions into consideration.
Meanwhile, there are some limitations of this study that
should be recognized. Since Beijing and many other regions
in China have experienced rapid urbanization since the 1980s,
it is very difficult to select corresponding rural stations in
studies of UHI effects for China’s big cities. Miyun station
used as the non-urban reference station also experienced some
urbanization development in our study period though it is
about 70 km away from the downtown Beijing, bringing some
uncertainties to estimated UHI intensity. In addition, the alti-
tude of Miyun station is about 40 m higher than that of Beijing
station and may also bias our estimates. The biases caused by
the urbanization development and the higher altitude of
Miyun station may offset each other to some degree.
A dense automatic weather station network has been devel-
oped in Beijing and can provide hourly meteorological data.
Yang et al. (2013) selected 8 non-urban reference stations
from 185 automatic weather stations based on a strictly de-
fined standard (Ren and Ren 2011), and further provided de-
tailed spatial and temporal features of Beijing’s UHI for the
period of 2007–2010. In future, to further our understanding
of the role of meteorological conditions for Beijing’s UHI and
its response to mass human migration during the CNY holi-
day, observational data from dense automatic weather stations
should be used, and more representative non-urban reference
stations should be selected following the methods in Yang
et al. (2013) and other studies.
Our results indicate that taking the impacts of meteorolog-
ical conditions into account helps to better identify the role of
population movements in the urban climate during the CNY
holiday. Some factors such as firework and firecrackers can
Fig. 6 Mean UHI effects (ΔT) during the background period (left-hand
bars) and the CNY week (right-hand bars), and the mean UHI difference
(line), between the CNY week and the background period (ΔUHI: CNY
week minus background period) averaged over the period 2004–2013,
with the Olympic year of 2008 excluded. The CNY week is denoted as
week(+1), while 1 week before and after the CNY week as week(−1) and
week(+2), and so on. The background period is defined as 4 weeks,
including 2 weeks before [week(−3) to week(−2)] and after [week(+3)
to week(+4)] the CNY week
L. Wu, J. Zhang

7. cause some uncertainties on our estimates of the population
movement impacts on Beijing’s UHI during the CNY holiday
that are subject to further investigation. Population move-
ments occur anytime and worldwide, and their impacts on
climate at a variety of temporal and spatial scales should be
further addressed to advance our understanding of anthropo-
genic climate modifications (Zhang and Wu 2016).
Acknowledgements This work was supported by the National Natural
Science Foundation of China (Grant Nos. 41675085,41275089 and
41305071).
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