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An Overview of Mainland China Temperature Change Research

  • China Meteorological Administration (CMA), Beijing/China University of Geosciences (CUG), Wuhan

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There has been significant effort devoted to investigating long-term trends in land surface air temperature over mainland China by Chinese scientists over the past 50 years, and much progress has been made in understanding dynamics of the changes. This review highlights research conducted by early and current Chinese climatologists, and particularly Professor Shaowu Wang from Peking University, with special focus on systematic work that has been conducted since the mid to late 1970s. We also discuss major issues that remain unresolved in past and current studies. The most recent analyses indicate that the country-average annual mean surface air temperature rose by 1.12°C over the past 115 years (1901–2015), with a rate of increase of about 0.10°C/decade. Temperatures have risen more rapidly since the 1950s, with the rate of increase of more than 0.25°C/decade. However, the recent increase in temperatures is in large part due to contamination by systematically biased data. These data are influenced by unprecedented urbanization in China, with a contribution of urbanization to the overall increase of annual mean temperatures in mainland China of about one third over the past half a century. If the bias is corrected, the rate of increase for the country-average annual mean surface air temperature is 0.17°C/decade over the last 50–60 years, which is approximately the same as global and Northern Hemispheric averages in recent decades. Future efforts should be focused towards the recovery and digitization of early-year observational records, the homogenization of observational data, the evaluation and adjustment of urbanization bias in temperature data series from urban stations, the analysis of extreme temperatures over longer periods including the first half of the 20th century, and the investigation of the observed surface air temperature change mechanisms in mainland China.
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An Overview of Mainland China Temperature Change Research
Guoyu REN1,2*, Yihui DING1, and Guoli TANG3
1 Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081
2 Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430074
3 National Meteorological Information Center, China Meteorological Administration, Beijing 100081
(Received October 18, 2016; in final form January 28, 2017)
There has been significant effort devoted to investigating long-term trends in land surface air temperature over
mainland China by Chinese scientists over the past 50 years, and much progress has been made in understanding dy-
namics of the changes. This review highlights research conducted by early Chinese climatologists, and particularly
Professor Shaowu Wang from Peking University, with special focus on systematic work that has been conducted
since the mid to late 1970s. We also discuss major issues that remain unresolved in past and current studies. The most
recent analyses indicate that the country-average annual mean surface air temperature rose by 1.12°C over the past
115 years (1901–2015), with a rate of increase of about 0.10°C decade–1. Temperatures have risen more rapidly since
the 1950s, with the rate of increase of more than 0.25°C decade-1. However, the recent increase in temperatures is in
large part due to contamination by systematically biased data. These data are influenced by unprecedented urbaniza-
tion in China, with a contribution of urbanization to the overall increase of annual mean temperatures in mainland
China of about one third over the past half a century. If the bias is corrected, the rate of increase for the country-ave-
rage annual mean surface air temperature is 0.17°C decade–1 over the last 50–60 years, which is approximately the
same as global and Northern Hemispheric averages in recent decades. Future efforts should be focused towards the
recovery and digitization of early-year observational records, the homogenization of observational data, the evalu-
ation and adjustment of urbanization bias in temperature data series from urban stations, the analysis of extreme tem-
peratures over longer periods including the first half of the 20th century, and the investigation of the observed sur-
face air temperature change mechanisms in mainland China.
Key words: observational data, surface air temperature, mainland China, modern time, climate change, urbanization
effect, climate warming
Citation: Ren, G. Y., Y. H. Ding, and G. L. Tang, 2017: An overview of mainland China temperature change re-
search. J. Meteor. Res., 31(1), 3–16, doi: 10.1007/s13351-017-6195-2.
1. Introduction
Global and sub-continental surface air temperature
change is one of the core issues of contemporary climate
change and has garnered significant interest from cli-
mate scientists. Chinese scholars realized in as early as
the 1960s that global and Chinese climates have under-
gone significant changes (Zhu, 1962), and presented pre-
liminary analyses regarding temperature and precipita-
tion trends. From the late 1970s to the early 1980s, aver-
age global surface air temperature increased once again
from the relatively low period during the early 1950s to
the mid 1970s, and the global climate exhibited accele-
rated warming. Thus, monitoring and detection of land
surface air temperature and sea surface temperature
change began to receive further attention from Chinese
and global academic institutions.
Professor Shaowu Wang, an outstanding Chinese cli-
matologist, was one of the earliest scholars that studied
on Chinese temperature change. Beginning in the early
1960s, he analyzed temperature observations over the
previous 87 years at Xujiahui (Zikawei) Station in
Shanghai, and found that annual mean temperature signi-
ficantly increased after 1920, peaking in the 1940s, and
Supported by the National Natural Science Foundation of China (41575003) and China Meteorological Administration Special Public
Welfare Research Fund (GYHY201206012).
*Corresponding author:
©The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2017
Volume 31 Special Issue in Commemoration of Shaowu Wang FEBRUARY 2017
then declined (Wang, 1962). Although the work is local-
ized to a single site, it was of great significance in under-
standing local temperature change and evoked public in-
terest in long-term climate change. Wang also conducted
a systematic study of decadal-scale national temperature
change and found that temperatures began to rise in the
1920s, peaked in the 1940s, and declined significantly in
the 1950s. Following these results, he suggested that the
cause of climate drift after the 1950s was due to changes
in sea level pressure and the atmospheric center of ac-
tion (Wang et al., 1963). Atmospheric centers of action
are perennially or seasonally stable high and low pres-
sure systems that affect large-scale weather and climate
change. Decadal variations in average national temperat-
ures have been confirmed by later research and Wang’s
conclusions appear to be generally supported.
Chinese scientific and technological research entered a
new stage of rapid development following 1978, which
coincides with the period when global average surface
temperatures began to rise significantly and increased at-
tention was given to global warming by academia. Pro-
fessor Wang and others became the leaders of climate
change science once again in this new era of climate re-
search. This paper primarily reviews research progress
regarding land surface air temperature changes over
mainland China since the middle and late 1970s and
highlights the perseverance and contribution to the sci-
entific issue by Chinese scholars, and particularly Pro-
fessor Shaowu Wang.
Here, we discuss changes in surface air temperature
over mainland China in the modern era, with particular
reference to multi-decadal- to century-scale variations
and long-term trends of the annual mean land surface air
temperature over mainland China, covering the modern
instrumental observation period. Changes of surface air
temperature in the historical period and the geological
period, interannual and interdecadal fluctuations of mod-
ern land surface air temperature, changes in modern up-
per atmosphere temperature, and causes of modern land
surface air temperature change and possible future tem-
perature trends are not considered in the present review.
2. Temperature changes over the past 100
Studies of mainland China surface air temperature
changes using long instrumental observation data started
in the mid 1970s. Jiacheng Zhang, Xiangong Zhang, Jijia
Zhang, Qipu Tu, and others conducted preliminary ana-
lyses on the observations and potential reasons for sur-
face air temperature change over the past few decades to
100 years. Zhang et al. (1974) analyzed global and
Chinese temperature changes on different timescales, and
concluded that climatic variations on the greater than
decadal scale were similar in China and globally. Fur-
ther, their analyses indicated that global high latitude
areas began cooling during the 1940s, as was also appar-
ent in China. Zhang (1978) confirmed that Chinese tem-
perature change in the 20th century was consistent with
global temperature change by using temperature grade
data. Moreover, they identified the 1940s as a period
with relatively high temperatures and showed that the
global and Chinese annual mean temperatures dropped
0.3 and 0.4–0.8°C, respectively, from then until the early
1970s. Zhang et al. (1979) analyzed the primary features
of mainland China surface air temperature fluctuation on
the greater than decadal scales by plotting temperature
anomaly cumulative curves for representative months in
four seasons from eight stations that had long-term ob-
servational data. The results showed that amplitude and
period in East China were larger and longer than in West
China, but the smallest amplitude existed in coastal areas
of South China. They also suggested that long-term fluc-
tuation in the Northern Hemisphere is related to large-
scale atmospheric circulation anomalies.
Zhang and Li (1982) used monthly mean temperature
data from 137 stations to construct China surface air tem-
perature series and analyzed long-term surface air tem-
perature variation throughout the previous century. In
their study, the area-average temperatures were calcu-
lated by five to seven representative stations selected
from each of seven regions in mainland China: North-
east China, North China, Yangtze River, South China,
Southwest China, Northwest China, and the Xinjiang Re-
gion. The study represented the first country-average sur-
face air temperature grade series with almost 100 years
of data for mainland China. The results indicated that
mean surface air temperature change during 1910–1979
in China was consistent with that in the Northern Hemi-
sphere in general, which exhibited warming in the early
20th century and rapid cooling after the 1940s, with the
most obvious cooling occurring in summer and autumn.
However, the analyses were conducted in 1979 and did
not capture the significant nationwide climate warming
that occurred in the several years that followed, and par-
ticularly after the mid 1980s. Further, the country-aver-
age series lacked data from Xinjiang and Tibet in the first
half of 20th century, which resulted in a potential under-
representation of country-average warming trends.
Zhang et al. (1982) and Zhang (1983) analyzed the
spatial variability and propagation feature of global sur-
face temperatures in the late 1960s–1970s. These studies
4Journal of Meteorological Research Volume 31
indicated a spreading phenomenon from west to east in
the temperature anomaly centers of the Northern Hemi-
sphere westerly zone, while tropical temperatures pro-
gressively changed in the east to west direction. Further,
these studies linked abnormal temperatures of China and
northeastern China in the 1970s to global-scale tempera-
ture changes and indicated that the cold or warm sum-
mers in northeastern China were consistent with global
climate abnormalities. These studies were not aimed at
the long-term region-specific temperature trends, but did
aid in understanding the spatial patterns and mechanisms
of surface temperature variations in China.
Tu (1984) analyzed the annual and seasonal mean
temperatures of China’s 42 observation stations in the
time period encompassing 1881–1981 by using principal
component analysis methods. Mainland China was di-
vided into five regions based on the interannual variabil-
ity of temperature. The first principal component of an-
nual and seasonal average temperatures of most areas
was consistent with the average temperature change in
the Northern Hemisphere, with the exception of North-
east China and northern Xinjiang. From the beginning of
the 20th century to around 1945 and again from the
1970s to present day, there were two obvious warming
periods, and a mild cool period in the interim. In part due
to 3-yr additional data compared to Zhang and Li (1982)
as well as the principal component signal extraction
method, this work was the first to discover the phe-
nomenon of Chinese re-warming after the mid- to late
1970s. Importantly, the work indicated climate warming
in the new era and the consistency of the rising temperat-
ure trend with the Northern Hemisphere.
In the early 1990s, Shaowu Wang, Yihui Ding,
Xuecun Lin, and colleagues systematically evaluated
changes of land surface air temperature in mainland
China over nearly 100 years, which represented a signi-
ficant step forward in the study of Chinese long-term cli-
mate change.
Wang (1990) analyzed temperature change in eastern
China over the previous century and compared it with av-
erage temperature change in the Northern Hemisphere
and the whole world. These analyses were based on tem-
perature grade data during 1910–1988, annual mean tem-
perature data of Harbin, Beijing, Shanghai, and Guang-
zhou that were interpolated to the stations from nearby
records during 1880–1988, and the eastern China decadal
mean temperature anomaly data reconstructed from his-
torical documents. This time series mainly reflected
long-term temperature changes of the eastern monsoon
region due to the lack of data in the western non-mon-
soon region, particularly because Xinjiang and Tibet
were not included prior to 1950. This work confirmed the
large-scale regional temperature rises in China begin-
ning in the 1920s, peaking in the 1920s–1940s, declining
afterwards, and also that the northeast and coastal areas
of China began warming again in the 1980s. Compared
to global average temperature anomaly series, eastern
China exhibited a more obvious cooling period during
1950s–1970s. The warming trend lagged behind global
trends in the mid to late 1970s, indicating that China’s
climate warming was generally consistent with global av-
erages, but there were Chinese-specific particularities.
Tang and Lin (1992) were the first to use monthly
mean temperature data from a high-density network of
observation stations (716 stations) and applied the data to
estimating national land surface air temperature time
series and its trends from 1921 to 1990. The results sug-
gested that Chinese cooling during the 1940s–1960s was
more apparent than that of the Northern Hemisphere, but
the warming trends of China in the 1980s were weaker
than the Northern Hemisphere, which partially con-
firmed the conclusions of Wang et al. (1990).
Regression analyses were performed by Ren and Zhou
(1994) using 11 stations (including rural plus urban) con-
taining recent observations and four stations (urban only)
with longer and earlier records to construct and analyze
land surface air temperature anomaly time series for the
Liaodong Peninsula in the 20th century. Linear relation-
ships between the two groups for the period 1964–1988
were used to reconstruct annual and seasonal mean tem-
perature anomalies for the whole region over 1905–1988.
This approach largely eliminated the impact of urbaniza-
tion on annual and winter mean air temperature trends,
and is one of the first efforts to eliminate urbanization bi-
as on average regional long-term temperature data in the
20th century.
Ding and Dai (1994) systematically reviewed the main
findings of temperature change over the previous cen-
tury in China and highlighted that Chinese surface air
temperature change was approximately similar to North-
ern Hemisphere averages. There were differences,
however, with the highest Chinese temperatures appear-
ing in the 1940s rather than in the 1980s and later years,
and a cooling trend that had existed in Southwest China
since the 1950s. Annual warming in mainland China
mainly occurred in northeastern, northwestern, and
northern regions, and the country-average surface tem-
perature appeared to have two shifts in approximately the
last 100 years, in 1919 and 1952. Further, it was noted
that urbanization may have an impact on China’s surface
air temperature observations and the current estimate res-
ults should be adjusted appropriately. The country aver-
FEBRUARY 2017 Ren, G. Y., Y. H. Ding, and G. L. Tang 5
age surface air temperature change did not exceed the
range of natural climatic variability, and it was not cer-
tain at the time that this climate change was caused by
human activity. This comprehensive review accurately
summed up the scientific understanding of that time for
the previous century’s surface air temperature change.
In the late 1990s, Chinese scholars began to pay more
attention to the previous century’s surface air temperat-
ure changes, coinciding with the acceleration of global
and mainland China warming as well as increased focus
on climate change by the international community. Shi et
al. (1995) used the EOF method to interpolate and ana-
lyze monthly mean temperature data from 28 stations in
China covering the previous 100 years, and showed that
Chinese temperature change exhibited obvious regional
differences. Warming was most obvious in Northwest
China, Northeast China, and northern parts of North
China, whereas warming trends were weak south of the
Yellow River. Lin et al. (1995) used the monthly mean
temperature records from 711 stations of China (span-
ning 1873 to 1990) in order to evaluate the annual mean
temperature trends for the whole country and different
regions. This analysis represented the longest national
and regional temperature trend estimations (at the time)
by using historical observation data from a high-density
station network.
Wang et al. (1998) analyzed temperature change
trends in China and globally over nearly 100 years by ap-
plying various data and by dividing China into 10 re-
gions. The annual mean temperature anomaly data for
China and the 10 regions were obtained for 1880–1996
based on proxy data (ice cores, historical documents, and
tree rings) to interpolate data for the areas where instru-
mental data were lacking. The spatial coverage of the
data was greatly improved due to the use of proxy data
for Xinjiang and the Tibetan Plateau, which solved the
problem caused by spatial data heterogeneity prior to the
1950s. This analysis was the first to provide long-term
Chinese temperature series covering the whole country
with uniform variance by use of the area weighted aver-
age method. The results indicated that the rate of in-
crease for the annual mean surface air temperature was
0.04°C decade–1 from 1880–1996. This rate was signific-
antly higher than the previous estimated value, and its
decadal variation was more similar to global or Northern
Hemisphere averages. Qian and Zhu (2001) used the
temperature data of Wang et al. (1998) to further analyze
climate change characteristics, and particularly, spatial
differences among different Chinese regions. Later,
Wang and Dong (2002) and Wang et al. (2005) updated
this series, and found that the national average surface
temperature increased at a rate of 0.06°C decade–1 dur-
ing 1880–2002, which was similar to the average global
warming trend. The results of these studies were widely
used in later analyses in the Assessment Report of Cli-
mate and Environment Change in China, and the Nation-
al Assessment Report on Climate Change (Qin, 2002;
Qin et al., 2005; Committee on China’s National Assess-
ment Report on Climate Change, 2007).
Chen et al. (1994) used measured data to establish a
regional mean surface air temperature series in eastern
China following the 1920s and discussed the relation-
ship between air temperature change and monsoon circu-
lation variation. Later, Chen et al. (2004) updated the
mean temperature series for the eastern region (east of
100°E) from 1920 to 2002 by including data from the na-
tional reference climate stations and the national basic
meteorological stations. This series indicated that the an-
nual mean temperature of the warmest year (1998) or the
5-yr running mean temperature of the 1990s in the east-
ern region of China was almost at, or slightly higher,
than the annual mean temperature of the second warmest
year (1946) or the 5-yr running mean temperature of the
Since the 21st century, China’s climate change re-
search has garnered significant attention from govern-
ment and scientific communities, and surface air temper-
ature change research in modern China has entered an
active new stage. Compared to previous studies, re-
search since 2000 mainly has been focused on: 1) the
quality of long-range surface observed data, particularly
data inhomogeneities, and the addition of high-density
and long-term data; 2) systematical evaluation of the urb-
anization bias in regional and national surface air temper-
ature data series; and 3) comprehensive and integrated
analyses on long-term variation characteristics of ex-
treme weather and climate events.
Tang and Ren (2005) gave preliminary consideration
to the temporal inhomogeneity of long-term series obser-
vations in the 20th century, by applying the mean values
of maximum and minimum temperatures as monthly and
annual mean values. This approach avoided the discon-
tinuity caused by using observation records at different
times of a day to calculate averages, and was also con-
sistent with the standard calculation methods of interna-
tional monthly and annual mean temperatures. The study
used the highest-density observational network data
available at that time, and region averages were assessed
by using an area-weighted average method over a grid
box, which is also in accordance with international prac-
tice (Jones et al., 1990). Later, Tang et al. (2009) per-
formed further quality control and interpolation of pre-
6Journal of Meteorological Research Volume 31
1950 data and the original series was updated with data
from 291 stations, which provided more continuous ob-
servation records and more uniform spatial distribution.
However, some problems still existed in the time series
data. For example, some stations had incomplete records
despite interpolation of data before 1950, inhomogeneity
of the series due to station relocation was not corrected,
the western region still lacked early data, and urbaniza-
tion bias had not been properly considered. However, the
country average surface air temperature series has been
widely used, and has also been used in each of the previ-
ous national assessment reports on climate change (Com-
mittee on China’s National Assessment Report on Cli-
mate Change, 2007, 2011; National Climate Center of
China Meteorological Administration, 2016).
Figure 1 shows curves of the annual mean surface air
temperature anomaly series of mainland China that have
been updated by Tang and Ren (2005) and Tang et al.
(2009) (red) and Wang et al. (1998) (blue). Based on the
analysis of Tang and Ren (2005) and Tang et al. (2009),
the country-average annual mean surface temperature in-
creased significantly in mainland China during the peri-
od 1901–2015, which is similar to the results previously
generated with various methods and data. The temperat-
ure variation characteristics on the interannual and
decadal scales are prominent. There were two signific-
antly warmer stages between the 1930s and 1940s and
again after the mid to late 1980s, but the degree of warm-
ing in the latter was significantly higher than the former.
Over 115 years, the country-average annual mean sur-
face air temperature linearly increased by 1.12°C, and the
average rate of warming was about 0.10°C decade–1. The
surface air temperature anomaly in 2015 was 1.17°C (rel-
ative to the 1971–2000 average), which was the second
warmest year after 2007 since 1901, and was very close
to 1998, the first warmest year. The annual mean surface
air temperature anomaly series updated from Wang et al.
(1998) showed a slightly smaller warming trend in main-
land China during the same time period (Fig. 1 and Ta-
ble 1).
Recently, Cao et al. (2013) used data from 16 stations
with relatively complete records in eastern China to con-
struct the annual mean temperature anomaly series (Cao
et al., 2013; Wang et al., 2014; Zhao et al., 2014). They
examined and partially corrected the data for inhomogen-
eities caused by station relocation. This series indicated a
greater warming trend over the previous hundred years,
with a warming magnitude of 1.52°C for 1909–2010 and
an average warming rate of about 0.15°C decade–1 (Fig.
1), which were higher than previous estimates by other
groups. This higher warming trend may be primarily re-
lated to the recovery of urbanization effect in the single-
station series after homogenization (Zhang et al., 2014),
and may also be associated with having fewer number of
stations used. Moreover, the time series was mainly fo-
cused on data for eastern and central cities of China.
Li et al. (2010a) constructed country-average annual
and seasonal mean temperature anomaly series begin-
ning in 1900 using homogenized data from the national
reference stations and national basic meteorological sta-
tions, and also long series of observational data from a
few neighboring countries. Li et al. (2010a) and Du et al.
Fig. 1. Changes in country-averaged annual mean surface air temperature anomalies over mainland China during 1901–2015 [relative to the
1971–2000 average; updated from Wang et al. (1998), Tang and Ren (2005), Tang et al. (2009), Committee on China’s National Assessment Re-
port on Climate Change (2015), and Cao et al. ( 2013)].
FEBRUARY 2017 Ren, G. Y., Y. H. Ding, and G. L. Tang 7
(2012) further estimated and analyzed errors in the China
average surface air temperature series. Liang and Chen
(2015) analyzed multi-temporal scale temperature changes
in the past 139 years in Southeast China, with particular
emphasis on the significant contribution of rising low-
frequency component of annual mean temperature vari-
ability to the recent warming trend in the region.
Table 1 compares the data and methods used and re-
gional ranges represented by the average temperature
series from Wang et al. (1998), Tang and Ren (2005),
Tang et al. (2009), Li et al. (2010a), and Cao et al.
(2013), in addition to the annual mean temperature trends
for mainland China or eastern China, covering the peri-
od of 1901–2015 based on respective data and method.
The warming trends of each series are quite different
over roughly the same time period (Table 1). Eastern
China had the largest warming trend as estimated by Cao
et al. (2013), Li et al. (2010a) reported the second highest
warming trend for the country as a whole, while the aver-
age warming estimate from Wang et al. (1998) for whole
mainland China was the smallest. The trend estimates
from Tang and Ren (2005) and Tang et al. (2009) were
The annual mean temperature change trends in main-
land China were generally between 0.08 and 0.12°C dec-
ade–1 during the period 1901–2015 (Wang et al., 1998;
Tang and Ren, 2005; Tang et al., 2009; Li et al., 2010a).
This range is closer to global land annual mean temperat-
ure changes during 1901–2014 (Sun et al., 2016), accord-
ing to the recently developed global land surface air tem-
perature dataset (GLSAT) by the China Meteorological
Administration (CMA), and the estimates of global land
temperature change according to the CRUTEM4.4.0.0
data, but is slightly lower than the result based on GH-
CN-V3.2.0 (IPCC, 2013, Table 2). However, the annual
mean temperature trends based on homogenized data
from 16 stations in eastern China over 1909–2015 (Cao
et al., 2013) are much larger than that of any global land
temperature data series.
3. Temperature changes over the past half a
The climate observational network in mainland China
is not perfect prior to 1951, and data gaps are a serious
problem. Consequently, there is large uncertainty in es-
timating long-term trends and changes for surface air
temperatures covering the past 100 years. On the other
hand, warming has become more apparent since the
middle of the 20th century, and particularly after the late
1970s. Therefore, many researchers have turned to ana-
lyze the high-density and high-quality observational net-
work records of recent decades in order to better under-
stand detailed spatial and temporal structure features in
modern surface temperature change in mainland China.
Zhang and Fang (1988) used observational records
from 1951–1985 to analyze spatially-specific differenti-
ation characteristics of surface air temperature variations.
They found that regional temperature changes are con-
sistent with global observations with increased warming
at high latitudes and less warming at lower latitudes.
Moreover, they also indicated spatial differences of tem-
perature variations in the eastern, central, and western re-
gions, which may be related to regional differences in
monsoon circulation variation and the influence of large
terrain features on the atmospheric circulation.
Li et al. (1990) used observational data from 160 sta-
tions to analyze Chinese temperature trends and its tem-
Table 1. Linear trends of annual mean land surface air temperature (°C decade–1) for mainland China during 1901–2015
Temperature series Data used Procedure Study area Trend*
Tang and Ren, 2005;
󳴆Tang et al., 2009
291 stations 5° × 5° grid,
area-weighted average
Mainland China 0.10
Wang et al., 1998 Observations plus proxy data,
total 50 sites
10 sub-regions,
area-weighted average
Mainland China 0.08
Cao et al., 2013 16 stations Simply arithmetical
East China 0.15 (1909–2015)
Li et al., 2010a 740 stations plus stations from
neighboring countries
5° × 5° grid,
area-weighted average
Mainland China 0.12 (1900–2015)
* The trends are significant at the 95% confidence level.
Table 2. Linear trends of annual mean land surface air temperature (°C decade–1) for mainland China and the global lands during 1901–2014
(global) and 1901–2015 (mainland China). Updated from IPCC (2013) and Sun et al. (2016) for global land average, and Wang et al. (1998),
Tang et al. (2009), and Li et al. (2010a) for mainland China average
Extent GHCN-V3.2.0 CRUTEM4.4.0.0 CMA GLSAT-V1.0
Global land 0.11* 0.10* 0.10*
Mainland China 0.08–0.12*
* The trends are significant at the 95% confidence level.
8Journal of Meteorological Research Volume 31
poral and spatial characteristics from 1951 to 1988. Their
analyses showed that annual mean temperature rose dur-
ing 1951–1988 with an increase of 0.2°C in the 1980s re-
lative to the 1950s. The surface warming trend rose with
latitude increases, and warming in the winter and au-
tumn was more obvious, while summer mean temperat-
ure change was very small and even exhibited a cooling
trend. Most of mainland China displays characteristic
winter warming and summer cooling. Lin and Yu (1990)
analyzed the annual mean temperature trends over the
past 40 years using data from 160 national reference cli-
mate stations. Their analyses indicated that temperature
increased at a rate of 0.04°C decade–1 from 1951 to 1989,
with the highest rates in Northeast and North China. In
addition, the annual mean temperature did not increase
but showed a decreasing trend in the Yangtze River and
southwestern parts of the country. This work suggested
the particularity of surface air temperature changes in the
Yangtze River and southwestern regions for the first
Chen et al. (1991) analyzed land surface climate
change characteristics over mainland China over more
than 40 years and discussed the spatial difference of tem-
perature trends by using consecutive observational data
from the higher density network of stations. They found
that climate warming only occurred in Northeast China,
North China, and Northwest China. In addition, they
showed that there was a cooling area south of 35°N,
north of the Nanling Range, and east of the Tibetan Plat-
eau, with cold centers in Sichuan, southern Shanxi, and
northern Yunnan. Later, Chen et al. (1998) used data
from over 400 sites comprising the higher density and re-
latively uniformly spatial distributed dataset to analyze
annual and seasonal mean land surface air temperature
trends between 1951 and 1995. In order to decrease the
influence of urban heat island effects, the authors re-
moved the records of 27 provincial capital stations and
Beijing and Tianjin stations when calculating the mean
temperature series and linear trends. The analysis con-
firmed the results of Chen et al. (1991), which suggested
regional differences in temperature changes. It also
showed that the country-average annual mean temperat-
ures began to significantly rise beginning in 1985.
Zhu (1992) discussed the influence of an area
weighted average on temperature trend estimates, and
obtained the estimate of annual mean temperature trends
for mainland China from 1951 to 1989 based on the
monthly mean temperature data of 160 stations. They
also compared that with annual mean temperature
changes of the Northern Hemisphere. Song (1994) used
the pentad mean land surface air temperature data of 336
stations from mainland China to analyze the spatial and
temporal temperature dynamics over 40 years. He indic-
ated that there was a significant difference in air temper-
ature interannual variability and long-term trends between
different regions and different seasons, while the annual
and winter mean air temperatures increased as a whole.
Zhai and Ren (1997) used observational data covering
the period 1951–1990 after removing observational re-
cords from potentially relocated stations and the data
from big cities (more than 500 thousand people). They
analyzed the spatial and temporal variation dynamics of
the maximum and minimum temperatures, and diurnal
temperature range (DTR) in China, showing that maxim-
um temperatures were generally increasing west of 95°E
and north of the Yellow River, but they were declining in
the south of the Yellow River. Minimum temperatures
were generally increasing over mainland China and this
increase was more significant in the north. Overall, the
annual mean DTR in China exhibited a significant de-
creasing trend. It was suggested that the significant in-
crease in minimum temperatures reflected the role of sus-
tained and strengthened greenhouse effects in the atmo-
sphere, and maximum temperature change was associ-
ated with sunshine and atmospheric moisture conditions.
They suggested that removing the observational data
with the possibility of station relocations increased the
homogeneity of data to some extent and discarding big
city stations eliminated warming biases dues to the in-
creased urban heat island effect.
Hu et al. (2003) analyzed the land surface air temper-
ature change in China using data from 160 stations and
found significant warming trends during 1951–2000 and
land surface air temperature decreased in central China.
Qian and Lin (2004) used daily observational data from
498 stations to analyze features of long-term land sur-
face air temperature changes from 1961 to 2000. They
found that although there were regional and seasonal dif-
ferences, each temperature index confirmed that it was
warming in northern China and DTR experienced a sig-
nificant decreasing trend over mainland China. The long-
term air temperature index change was suggested to be
related to increased precipitation in the Yangtze River
basin and decreased precipitation in the Yellow River
basin. However, it was probably associated with urbaniz-
ation and aerosol emission effects. A significantly de-
creased DTR trend over mainland China had been sup-
ported by Hua et al. (2004), who found that annual mean
DTR in different regions of mainland China, and particu-
larly in the east region. By analyzing surface air temper-
ature changes of China based on a daily climate dataset
of 305 stations for 1955–2000, Liu et al. (2004) also re-
FEBRUARY 2017 Ren, G. Y., Y. H. Ding, and G. L. Tang 9
ported an obvious decreasing trend of annual mean DTR
due to the large increase in minimum temperature and a
slight decrease in maximum temperature.
Wang et al. (2004) used data from 740 national refer-
ence climate stations and national basic meteorological
stations to examine long-term change characteristics in
the basic variables of surface climate and provided new
insights on land surface air temperature trends. Their res-
ults suggested that the annual mean surface air temperat-
ure rose in almost every region, except for a decreasing
trend in the middle-lower reaches of the Yangtze River in
summer. Additionally, there was a cooling trend in
spring and in the middle reaches of the Yangtze River
over the whole year, but the cooling phenomenon in the
southwest region became less significant. Their results
also indicated a warming center in the northeastern re-
gion of the Tibetan Plateau, but its reliability must be
confirmed due to poor data coverage. This study was the
first to indicate that the cooling trend in Southwest China
observed previously had been reversed by the 1990s.
Beginning in 2005, homogenized datasets obtained by
different methods were used in the analyses of land sur-
face air temperature changes over mainland China (Li et
al., 2004; Ren et al., 2005a; Yan and Jones, 2008; Li and
Yan, 2009; Li et al., 2016). Importantly, the discontinu-
ity of historical observational data due to man-made
factors, such as relocation of stations and instrument re-
placement, has been adjusted to some extent, which rep-
resents important progress over earlier research (Ding
and Ren, 2008).
Ren et al. (2005a, b) used monthly mean temperature
data from 740 stations across mainland China that were
quality controlled and adjusted for inhomogeneity to ana-
lyze spatial and temporal characteristics of annual and
seasonal mean surface air temperature changes between
1951 and 2004. Their results indicated that annual mean
surface air temperature trends were much higher than
global or Northern Hemisphere averages for the same
time period. The warming rate was about 0.25°C
decade–1, and country-wide warming mainly occurred
after the mid 1980s. This study was the first to use homo-
genized monthly surface air temperature data to analyze
large-scale climate change in China and confirmed that
surface air temperature changes exhibited seasonal and
spatial dynamics, which supported previous research res-
ults. However, it was also noted that warming is not only
highly significant in winter, spring, and autumn, but also
in summer, with a seasonal mean warming rate of about
0.15°C decade–1, which was mainly caused by a succes-
sion of abnormally hot summers after the 1990s. After
using homogenized data, the systematic bias due to urb-
anization effects was found to obviously remain in the
country-average annual and seasonal mean temperature
anomaly series based on national climate observational
data, and the bias had to be further evaluated and correc-
Tang et al. (2005) compared the east-west difference
of surface air temperature changes for the period
1951–2002, finding that annual mean temperatures in-
creased at a rate of 0.26°C decade–1 in the east, and at a
rate of 0.18°C decade–1 in the west. The increasing trends
of spring and winter mean temperatures were signific-
antly larger in the east than those in the west, but the
warming trends in summer and autumn were lower in
eastern China than those in the western region. Based on
data from 160 stations, Huang and Hu (2006) analyzed
characteristics of Chinese winter mean temperature
changes during 1951–2004. Their results indicated that
early-winter and late-winter mean temperature changes
were significantly different. In particular, early-winter
warming trends in southern China were small, but late-
winter warming was more significant. In contrast, early-
and late-winter warming trends in northern China were
both significant with late-winter seeing a very large and
significant warming over the previous decades.
Cao et al. (2016) used homogenized data collected
from 2400 stations from 1960 to 2014 to analyze annual
and seasonal mean temperature trends. They found that
the rate of increase of the annual mean maximum tem-
perature was 0.22°C decade–1, while the rate of increase
of the annual mean temperature was 0.38°C decade–1.
These estimates were larger than those that had been re-
ported previously. These higher estimates of trends were
unexpected because the 2400 stations included a higher
proportion of weather stations located in small cities,
towns, and villages. The rate of temperature increase
should be lower than the estimates obtained based on
datasets from 700 stations. Possible reasons for this lar-
ger estimation was that the starting year of the data was
later, the earlier section of the data series contained the
relatively cold period of the 1960s, and also the data
were updated to 2014 with the later section of the series
including more warm years. In addition, homogenization
processing, aimed at correcting the discontinuous re-
cords caused by relocations of stations from urban to ru-
ral areas, possibly restored the urbanization bias to a
greater extent (Zhang et al., 2014; Ren et al., 2015).
Ren et al. (2016) analyzed the spatial and temporal
characteristics of surface air temperature change in main-
land China by using hourly data from 1973 to 2011. They
10 Journal of Meteorological Research Volume 31
found that the country-average annual mean temperature
rose quickly at night until 1992, and elevated rapidly
around midnight, reaching a peak increase rate of 0.27°C
decade–1. However, stronger warming occurred in the
daytime during the time period 1992–2011, and the fast-
est temperature increases occurred in the later afternoon
with a rate of increase of 0.46°C decade–1. In addition,
spring early afternoons replaced winter midnights as the
season and time with the most rapid increase rate. The
annual warming during 1973–1992 was higher in the
northeast region, whereas the southwest, which had pre-
viously experienced cooling trends, became the faster
warming region during 1992–2011. There were various
possible reasons behind the observed trends in surface air
temperature, and seasonal and regional differences of
temperature changes, but the authors suggested that solar
radiation, cloud cover, aerosol, and urbanization around
the stations, among other factors, may have played a role.
Recently, Li et al. (2015) reported the phenomenon of
warming slowdown in mainland China after 1998, and
suggested that the increase in annual mean maximum
temperature obviously slowed down during this time,
which may have contributed to delayed rising of annual
mean surface air temperatures and the decreased differ-
ences of maximum and minimum temperatures, whereas
seasonal mean maximum temperatures in summer gene-
rally increased. Zheng et al. (2015) and Duan and Xiao
(2015) recently reported new characteristics of surface
air temperature change in the Qinghai–Tibetan Plateau,
showing that, after 1998, the slowdown of climate warm-
ing in this area was generally undetectable, and a con-
tinual rise in the plateau’s surface air temperatures in re-
cent years was prominent.
Overall, higher quality observational data with good
spatial and temporal resolutions have been used to study
surface air temperature change in mainland China in the
past more than half century, and homogenized historical
temperature data has begun to be applied since the early
part of the new century. Research towards these ends has
gradually evolved and resulted in a better understanding
of mainland China surface air temperature change, in-
cluding its spatial differences, seasonal characteristics,
diurnal patterns, and possible driving forces and mecha-
4. Urbanization effects on temperature trends
It had been a highly debated and unresolved issue re-
garding the urbanization effect or effect of enhanced urb-
an heat island intensity on surface air temperature trends
(Ren et al., 2005c; Ren and Ren, 2011). This issue could
not be ignored in the analyses of surface air temperature
change and in developing climate change monitoring ser-
vices. Chinese scientists systematically investigated this
problem and obtained a number of new results in recent
years (e.g., Ren et al., 2005c, 2008, 2015; Hua et al.,
2008; Yang X. C. et al., 2011; Wang and Ge, 2012; He et
al., 2013; Wang et al., 2013; Wu and Yang, 2013; Yang
Y.-J. et al., 2013; Sun et al., 2017). The IPCC AR5 partly
considered the research results concerning mainland
China and other regions, and suggested for the first time
that the bias from urban warming tended to be more ob-
vious in regions with rapid economic development, but
also suggested that it had little influence on the hemi-
spheric and global scales (IPCC, 2013).
Wang et al. (1990) and Zhao et al. (1990) showed that
Chinese urbanization had an effect on surface air temper-
ature trends as estimated at northern and eastern urban
stations. Zhao et al. (1990) found that annual mean tem-
perature and annual mean minimum temperature rose
more noticeably at urban stations compared to rural sta-
tions. In particular, annual mean minimum temperature
had a more noticeable increase. Concurrently, Qiao and
Qin (1990) also highlighted this problem, suggesting that
bias from urbanization might have affected the temperat-
ure trends at the county-level weather stations in China.
Further, Zhao (1991) analyzed annual and seasonal mean
temperature trends in mainland China and evaluated the
effects of urbanization on temperature changes, suggest-
ing that an obvious increase in annual mean temperat-
ures at the stations from big cities during the previous 39
years appeared, with linear trends of 0.27 to 0.45°C,
whereas the temperature trends of the stations from small
cities and towns were only 0.04 to 0.12°C. This finding
was supported by Portman (1993) who reported a signi-
ficant difference of temperature trends during 1954–1983
between 21 urban stations and 8 rural stations in North
China. These early research efforts were the first to
identify the effects of urbanization on the long-term
trends of surface air temperature for urban stations across
mainland China.
In the mid and late 1990s, studies of urbanization ef-
fects on surface air temperature change quieted. An em-
phasis on the evaluation and correction of systematic bi-
as from urbanization effect in surface air temperature
data series was reiterated following the Science and
Technology (S&T) Project of the National “Tenth Five-
Year-Plan” of China that was approved in 2001 and the
subsequent S&T Projects of the National “Eleventh Five-
Year Plan”, which financed, among others, the systema-
tic examination and evaluation of urbanization effects on
observational records of surface air temperature in main-
FEBRUARY 2017 Ren, G. Y., Y. H. Ding, and G. L. Tang 11
land China (Ren et al., 2005c, 2008, 2015; Ding and Ren,
2008; Ren and Zhou, 2014).
Compared to previous analyses, studies of the last 15
years bear a few of advantages. First, much denser and
updated-to-present observations have been applied, with
the spatial and type representatives of the temperature
data having been substantially improved. Second, the
data inhomogeneity problems due to station relocations
and other factors in the data series have been partially
solved, which allows the use of homogenized historical
observation data in the studies of urbanization bias.
Third, study objectives have been more explicit and in-
cluded different types of urban station networks, and in
particular, the national reference climate stations and na-
tional basic meteorological stations, which have been
generally used in climate change research. Fourth, the se-
lection methodology of reference station networks and
reference stations has been further developed, including
comprehensive methodologies to consider various factors
and the incorporation of land surface brightness tempera-
ture and visible light data from satellite remote sensing
products into the selection criterion. Fifth, metric indi-
cators including urbanization effect and urbanization
contribution have been developed, which has signifi-
cantly facilitated the interpretation of the scientific impli-
cations of results.
Research results over the past decade consistently
show that large and significant biases from urbanization
effects exist in the currently used surface air temperature
data series in mainland China. For instance, in a study by
using a reference temperature dataset from 143 stations
developed based on a comprehensive method for select-
ing rural stations (Ren Y. Y. et al., 2010; Ren G. Y. et al.,
2015), Zhang et al. (2010) confirmed that the effect of
urbanization on the country-average annual mean sur-
face air temperature trend of the national reference cli-
mate stations and national basic meteorological stations
from 1961 to 2004 was at least 0.076°C decade–1. This
impact was highly statistically significant, and the contri-
bution of urbanization was greater than 27.3%. More-
over, the urbanization effects in mainland China as a
whole were highly significant across all seasons. With an
exception of northern Xinjiang, the warming trends res-
ulting from urbanization in different regions of the coun-
try were all significant. This was particularly apparent in
the Jianghuai region where the urbanization effect
reached over 0.086°C decade–1 and the urbanization con-
tribution was higher than 55.5%. Recently, Ren and Zhou
(2014) analyzed the urbanization effects on the extreme
temperature indices using the same reference network
data as Zhang et al. (2010), and found that urbanization
in mainland China had a significant influence on the
long-term trends of annual and seasonal mean minimum
temperature (Tmin), average temperature (Tavg), DTR, and
other extreme temperature indices from 1961–2008,
which are commonly used internationally. In particular,
the urbanization effects on the upward trend of Tmin and
the downward trend of DTR were large and highly signi-
ficant, with the urbanization factors accounting for at
least 32% of the negative trend of annual mean DTR in
mainland China. This suggests that urbanization not only
significantly changed the mean surface air temperature
trends on the sub-continental scale but also led to a signi-
ficant systematic bias in the time series of the extreme
temperature indices.
In general, the observational temperature records of
urban and national stations in mainland China have been
significantly affected by urbanization since mid 20th cen-
tury, regardless if the data were homogenized. This basic
conclusion was confirmed and supported by many inde-
pendent studies of the country (Hua et al., 2004; Huang
et al., 2004; Zhou et al., 2004; Chen et al., 2005; Chu and
Ren, 2005; Liu et al., 2005; Zhang and Ren, 2005; Zhou
and Ren, 2005, 2009; Bai et al., 2006; Ren et al., 2007,
2008, 2015; Hua et al., 2008; Tang et al., 2008; Zhao et
al., 2009; Li et al., 2010b; Ren and Ren, 2011; Yang X.
C. et al., 2011; Yang Y.-J. et al., 2013; Wang and Ge,
2012; He et al., 2013; Li and Huang, 2013; Wang et al.,
2013; Wu and Yang, 2013; Ren and Zhou, 2014; Zhang
et al., 2014; Bian et al., 2015; Shi et al., 2015; Wang and
Yan, 2016; Sun et al., 2017). These investigations varied
in study area, study period, the data used, the indices
considered, data processing methods, and target stations
selected. The major differences that do exist among these
studies result from the different methods to determine the
reference stations and to establish the reference temperat-
ure series. However, overall, all studies agreed that urb-
anization has had an obvious and in most cases signific-
ant effect on land surface air temperature trend estimates
in mainland China over the past decades.
The above studies represented an important step to-
ward more accurate monitoring and research of regional
climate change. They showed that the systematic bias or
urban bias in the surface air temperature data series
caused by urbanization on the sub-continental scale is in
the same order of magnitude with the overall warming
trends estimated by different research groups. These res-
ults were contrary to previous high-profile and far-reach-
ing studies by some climatologists including those by
Jones et al. (1990, 2008), Peterson (2003), and Parker
(2006). Based on these Chinese studies, the IPCC AR5
pointed out for the first time the marked effect of urban-
12 Journal of Meteorological Research Volume 31
ization on regional surface air temperature trends in rap-
idly developing regions including mainland China. The
report indicated that the effects of urbanization were up
to 20% of the overall temperature trends in eastern China
as a whole, as estimated from the currently used datasets.
It should be noted that this conclusion is clearly conser-
vative, considering the Chinese studies mentioned above.
A longstanding problem in regional climate change re-
search could also be explained by the above studies. The
rate of increase in the annual mean surface air temperat-
ure in mainland China was more rapid than those of the
global and the Northern Hemispheric averages since the
1950s, regardless of whether 160, 730, or 2400 station
observation data were used, and whether or not homo-
genized temperature data were applied. Estimates of the
temperature trends based on homogenized data of nation-
al reference climate stations and national basic meteoro-
logical stations are nearly one times larger than those re-
ported for global and the Northern Hemispheric aver-
ages. It is clear at present that the significantly higher
rate of temperature increase in mainland China mainly
results from the effects of urbanization on surface air
temperature observations. If the urbanization biases were
excluded from the current historical data series, the rate
of temperature increase for the country-average annual
mean surface air temperature in mainland China is ap-
proximately the same as global and Northern Hemispher-
ic averages over the last several decades (Ren et al.,
2012; Sun et al., 2016).
Previous studies have indicated that the rising trend of
annual mean surface air temperature was approximately
0.25°C decade–1 in mainland China over periods begin-
ning from the 1950s (Wang et al., 2004; Ren et al.,
2005c; Ren et al., 2012). Many studies have estimated
the systematic biases due to urbanization and indicated
the contribution rates of at least 25% of urbanization to
the annual mean temperature trends, based on datasets
from national reference climate stations and national ba-
sic meteorological stations (Ren et al., 2008, 2015;
Zhang et al., 2010; Yang et al., 2011; Wang and Ge,
2012; He et al., 2013). Recently, based on the data of
2400 observational stations across mainland China, an at-
tribution analysis showed that annual mean surface air
temperature change due to urbanization was found to be
1/3 of the overall temperature increase in mainland China
(Sun et al., 2016). Considering a conservative urbaniza-
tion effect of 30% in the overall upward trend, the warm-
ing rate of the country-average annual mean surface air
temperature would be reduced to about 0.17°C decade–1
over the past half a century, which is approximately the
same as global average trend estimates given by IPCC
AR5 (IPCC, 2013).
5. Conclusive remarks
Studies of land surface air temperature changes in
mainland China continue to be vigorously conducted and
expanded in many areas. The achievements are insepar-
able from the efforts of Professor Shaowu Wang and oth-
er early-time climatologists. However, there are some
major issues that need to be solved in the studies of sur-
face air temperature change in the country (Ding and
Ren, 2008; Wang et al., 2009; Ren et al., 2012; Wu et al.,
2014; Ding and Wang, 2016). The issues that remain un-
resolved consist of the following. First, the absence of
early-year observational records, particularly in western
China, brings considerable uncertainty to the studies of
long-term surface air temperature changes over the past
century. Second, there are serious inhomogeneity prob-
lems in the observational surface air temperature data
series in mainland China, which could make analyses of
trends less reliable, especially for the analyses based only
on the data from a single station or a small number of
stations. Third, the historical temperature data from urb-
an stations contain systematic biases caused by the un-
precedented urbanization process, which should be eval-
uated and adjusted accordingly in future. Fourth, studies
of extreme temperature change over longer periods, in-
cluding the first half of 20th century, have been compar-
atively scarce due to limited high-quality daily temperat-
ure data. Fifth, studies regarding the mechanisms of
long-term observed surface air temperature changes over
mainland China are only beginning, and it is thus neces-
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Tech & Copy Editor: Lan YI
Language Editor: Lan YI
16 Journal of Meteorological Research Volume 31
... Urban heat island (UHI), referring to higher temperature in urban than surrounding areas, has aroused considerable research interests because of its increasing impacts on urban environment, public health, and human well-beings (Arnfield, 2003;Kim and Brown, 2021;Manoli et al., 2019;Miao et al., 2020;Ren et al., 2017;Stewart, 2011;Wang and Yan, 2016;Wu and Ren, 2019;Yan et al., 2016;Zhao et al., 2014;Zhou et al., 2019). The UHI studies can be mainly categorized into two broad types based on observation principles and devices: atmospheric or air UHI (AUHI) and land surface UHI (SUHI) (Mirzaei and Haghighat, 2010;Oke, 1982;Zhou et al., 2019). ...
... It is easy to quantify the AUHII by comparing observations between urban and reference stations (Chow and Roth, 2006;Ren and Ren, 2011;Scott et al., 2018;Zeng et al., 2009). However, previous studies focused primarily on individual cities that fail to capture the large-scale variability of the AUHI effects, and have been long criticized for a limited number and poor representativeness of the meteorological stations Ren et al., 2017;Ren and Ren, 2011;Wang et al., 2015). The second aims to estimate urban contribution to the observed warming trend by comparing long-term temperature trends of urban stations with that of reference stations (e.g., stations in surrounding suburban or rural areas) (Chao et al., 2020;Tysa et al., 2019;Yang et al., 2011) (referred as "urban minus rural (UMR)") or that of climate reanalysis data (termed as "observation minus reanalysis (OMR)") (Chao et al., 2020;Kalnay and Cai, 2003;Park et al., 2017;Shen and Zhao, 2021;Yang et al., 2011;Zhou et al., 2004). ...
... Nevertheless, limitations exist in both the UMR and OMR approaches, resulting in highly controversial estimates across studies (Li et al., 2020a). For example, contribution of urbanization to warming has been estimated to be <0.7 % and as high as 40 % in China (Li et al., 2020a;Ren et al., 2017;Ren et al., 2008;Shen and Zhao, 2021;Wang et al., 2015;Wang and Yan, 2016;Yan et al., 2016). In practice, prior studies mostly focused on one kind of the aforementioned AUHI estimates, though they were all claimed as "urban heating effect" in literature. ...
The atmospheric urban heat island (AUHI) effect, traditionally measured by in-situ sensors mounted on fixed meteorological stations, has been extensively studied by different and imperfect methods. However, facts and uncertainties of the AUHI estimates revealed by the different methods are not well understood at a large scale. Here we examined the spatial-temporal variations of the AUHI effects from multiple perspectives in China's 86 large cities as revealed by national-level meteorological observations at 2-m height from 1981 to 2017. We find relatively consistent patterns of larger urban heating effects in daily minimum temperature, winter, and Northeast China than their counterparts in terms of multiyear mean intensity (AUHII), long-term trend (△AUHII), and contribution to local warming (according to the CTRUMR “urban minus rural” and CTROMR “observation minus reanalysis” methods). Concurrently, a cooling impact or a reduction in the heating effect has been observed in some cities randomly, especially in daily maximum temperature. On average across cities, the AUHII, △AUHI, CTRUMR, and CTROMR for the daily mean temperature amount to 0.33 °C, 0.013 °C 10a⁻¹, 53 %, and 23 % at an annual mean time scale, respectively. Nevertheless, the poor representativeness of weather stations, discrepancies among the quantification methods, nonlinearity of the long-term tendencies, and coupling effects with rural crop land use activities lead to large uncertainties of the AUHI estimates. Our results emphasize the limitations of national-level meteorological stations in characterizing AUHI in China and suggest that the urban heat island remains a “well described but rather poorly understood” phenomenon warranting further investigation by a combined uses of multiple techniques like high-density sensor networks, remote sensing techniques, and high-resolution numerical models.
... The models perform better for the SAT change after the 1970s than for that in the early 20th century. In particular, the warming peak in the 1940s is only reproduced by 2 out of 25 CMIP5 models (Chen and Frauenfeld, 2014), although the degree of warming is smaller than that in the late 20th century and there is uncertainty between the various observational datasets (Ren et al., 2017). Both anthropogenic and natural forcings and the internal multi-decadal variability of the coupled ocean-atmosphere systems are considered to affect the overall SAT change, but attributing the changes in SAT to these factors remains challenging (Zhao et al., 2005). ...
... In particular, during 1980-2015, the warming rate over China is~0.41°C/10 a, much larger than the global figure (~0.26°C/10 a) according to the average of the five datasets, again justifying conclusions from many previous studies (Man et al., 2012;Ding and Wang, 2016;Ren et al., 2017). ...
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The increase in the average surface air temperature anomaly (SATA) over China is stronger than the global average. However, the accurate simulation and attribution of regional SATA evolution remain challenging for current global climate models. This study simulates historical SATA variations over China using the coupled (FGOALS-g3) and uncoupled (atmospheric component, GAMIL3) models and examines their possible causes. Results show that both models reproduce the historical SATA variation with higher correlation coefficients (0.735 and 0.782) than many global climate models (0.25 - 0.56), although they somewhat over- or underestimate changes in different periods. In particular, the cooling trend during 1941–1970 is well simulated by the coupled model but poorly presented in the uncoupled model. In addition, the coupled simulations produce stronger long-term trends than the uncoupled ones during 1870-2014 by allowing full interaction between the atmosphere, ocean, and sea ice. In contrast, the uncoupled simulations reproduce better decadal and multi-decadal SATA variations owing to the constraints of the observed sea surface temperature (SST), such as the Atlantic multidecadal oscillation, and sea ice cover. Using Detection and Attribution Model Intercomparison Project (DAMIP) experiments, we find that the warming in the early 20th century and the recent 50 years is mainly driven by natural forcings and greenhouse gases (GHGs), whereas the cooling during 1941–1970 is caused by natural factors and anthropogenic aerosols. The cooling effects of anthropogenic aerosols are mainly from the indirect SST-mediated responses through the atmosphere-ocean interactions in the coupled model.
... SR constitutes a key variable to the circulation of water in the atmosphere (Li et al., 2018;Wang et al., 2018). Temperatures have risen more rapidly in China since the 1950s, with the rate of increase of more than 0.25 • C decade − 1 (Ren et al., 2017). Possibly, a warmer surface and atmosphere affected by SR cause ET to increase. ...
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Evapotranspiration (ET) in terrestrial ecosystems is of great significance for water resource evaluation, crop water requirements, and drought monitoring and is affected by multiple environmental factors. Several studies investigated the environmental factors affecting evapotranspiration with long time series, but there are few detailed research exploring changes in the dominant controls of ET. It is essential to understand the primary mechanisms involved and their response to climate change. In this study, we analyzed the dominant controls on ET using variable importance in projection (VIP) scores from a Partial Least Squares Regression (PLSR) analysis and then explored the change of dominant controls over time. Our results indicated a significant ET increase trend over 1982-2015 of 1.40 mm/year in China, with solar radiation (SR), temperature (T), and leaf area index (LAI), as the dominant controls contributing to the increasing changes of ET. Increase in LAI (greening) was the primary cause of increasing ET over the 1982-2015 period, especially in temperate monsoon climate regions. In contrast, the VIP scores of SR and T indicated a negative contribution to increasing ET during the 34 years. The differences in the contribution dynamics of dominant controls to ET may result from different sensitivities to canopy resistance in different vegetation types. This research revealed an increasing contribution of greening to terrestrial evapotranspiration in China and improved our understanding of the change of dominant controls over China from 1982 to 2015 and their influence to ET under the changing climate and its impact.
... Since 1995, climate change was notable in the Yellow River Basin. The average temperature was increased by 0.4°C/10a, which was significantly higher than the growth rate in China (0.25°C/10a) [52]. The average precipitation was decreased by −2.1 mm/10a but presented the characteristic of large spatial-temporal difference. ...
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The aim of this study was to identify the impacts of different driving factors on terrestrial ecosystem evolution. The Yellow River Basin was selected as the study area, of which terrestrial ecosystem was deeply affected by climatic change and human activities. We constructed four scenarios (including without any impacts, affected by climate change, by human activities and by both impacts), and the discrepancies between them reflected the impacts of climate change or human activities. Based on this, the future land use simulation model was used to simulate the land use distribution under the four scenarios, and then, the ecosystem services values (ESV) and landscape patterns index were evaluated. The results indicated that affected by climate change during 1995–2015, the Mean Patch Area of the forestland decreased by 0.19% and the landscape patterns became fragmented. Meanwhile, the total ESV decreased by 0.03 billion dollars and the ecosystem regulation services were weakened. Under the influences of human activities, the Contagion index decreased by 1.71% and the landscape patterns became dispersed. Simultaneously, the total ESV increased by 0.56 billion dollars, but the function tends to be unitary. In addition, these effects showed great spatial heterogeneity. This study provides scientific support for ecological protection in the Yellow River Basin.
... Megacities are mainly characterized by dense population and high-rise buildings. Tremendous land use and land cover changes in urban areas have formed unique urban climatic characteristics, such as urban heat island and urban dry island [1][2][3][4][5]. e fundamental cause for these urban climate effects is that the modification of the underlying surface changes the original energy and mass exchange process between the surface and the atmosphere, finally resulting in the weather and climate change [6][7][8]. ...
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In order to meet the demand of more refined urban weather forecast, it is of great practical significance to improve and optimize the single-layer urban canopy model (SLUCM) suitable for the megacity of Shanghai. In this paper, based on the offline SLUCM model driven by a whole-year surface flux observation data in the Shanghai central business district, a series of parameter sensitivity tests are carried out by using the one at a time (OAT) method, the relative importance and a set of optimized parameters of the SLUCM suitable for high-density urban area are established, and the improvement of simulation is evaluated. The results show that SLUCM well reproduces the seasonal mean diurnal patterns of the net all-wave radiation flux ( Q ∗ ) and sensible heat flux (QH) but underestimates their magnitudes. Both Q ∗ and QH are linearly sensitive to the albedo, and most sensitive to the roof albedo, the second to the wall albedo, but relatively insensitive to the road albedo. The sensitivity of Q ∗ and QH to emissivity is not as strong as that of albedo, and the variation trend is also linear. Similar to albedo, Q ∗ and QH are most sensitive to roof emissivity. The effect of thermal parameters (heat capacity and conductivity) on fluxes is logarithmic. The sensitivity of surface fluxes to geometric parameters has no specific variation pattern. After parameter optimization, RMSE of Q ∗ decreases by about 3.4–18.7 Wm−2 in four seasons. RMSE of the longwave radiation (L↑) decreases by about 1.2–7.87 Wm−2. RMSE of QH decreases by about 2–5 Wm−2. This study provides guidance for future development of the urban canopy model parameterizations and urban climate risk response.
... Soon et al. (2018) suggest that one way to minimize this blending problem of homogenization would be to ensure that the neighbor network used for the homogenization process is not systemically biased relative to the target stations, e.g., rural stations should be homogenized using a mostly rural station network [38]. Indeed, they note that Ren et al. have effectively carried this out for their homogenization of Chinese records for the post-1960 period [42,43]. However, this is a non-trivial challenge for future research, which is beyond the scope of this paper. ...
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The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011-2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community’s homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments.
Quantitative assessment of urbanization effect on surface air temperature (SAT) change provides crucial basis for formal detection and attribution analyses of climate change. However, debates about urbanization‐related warming bias in documented regional SAT trend still persist, mainly due to different determination of rural stations. Here the urbanization effect on SAT change over the Beijing–Tianjin–Hebei region in China during 1980–2019 is estimated through three kinds of ways (i.e., comparisons between urban and rural stations [arithmetically station‐averaged], urban‐dominated and rural‐dominated patches [patch‐weighted mean], and realistic urban and rural areas [area‐weighted mean]). The last method explicitly takes urban and rural land cover fractions into account when calculating urban/rural and regional mean SAT trends. Urbanization‐induced warming in the annual mean SAT change of urban stations (areas) through the three ways are estimated as 0.159°C, 0.195°C, and 0.138°C per decade, respectively. And urbanization effect on regional averaged annual mean SAT calculated by patch‐weighted and area‐weighted methods are 0.113°C and 0.050°C per decade, respectively, which account for 33.8% and 14.8% of the total regional warming. The urbanization effect on observed SAT change estimated by considering realistic urban/rural land cover proportions is much lower than traditional station‐unweighted way. Patch types (b) determined by nearest neighbor interpolation of station types (a) exhibited much higher urban proportion than grid types (c) based on the urban land fraction within each grid cells, which results in overestimation in the urbanization‐induced warming by comparing between urban‐dominated and rural‐dominated patches‐weighted mean (e). While incorporating realistic urban/rural land cover proportions into urban–rural comparison yields a much lower contribution of urbanization to regional warming trend (f).
Distinguishing the respective roles of climate change and anthropogenic activities can provide crucial information for sustainable management of the environment. Here, using the residual trend method (RESTREND), which measures the residue of the actual and potential trends of vegetation, we quantified the relative contributions of human activities (e.g., ecological restoration, overgrazing, and urbanization) and climate change (the warmer and wetter trend) to vegetation dynamics in China during 1988–2018 based on multiple vegetation indices, including the vegetation optical depth (Ku-VOD, C-VOD), normalized difference vegetation index (NDVI), and gross primary productivity (GPP). The results showed that the VOD, NDVI, and GPP exhibited overall increasing trends during 1988–2018. Human activities contributed >70% to the increases in NDVI and GPP in China, whereas a counterbalanced contribution of human activities and climate change was identified for the VOD dynamics (51% vs. 49%). Regions with high contributions from human activities to NDVI, GPP, and VOD were located in northeastern, southern, central, and northwestern China. In northern China, the positive impacts of human activities on NDVI (78%) and BEPS-GPP (83%) were greater than those of climate change. In contrast, human activities contributed 96% to the decrease in Ku-VOD over the same period. Before 2000, climate change promoted increases in GPP and NDVI in most regions of southern China. The increasing rates of GPP and NDVI accelerated after 2000 due to afforestation. However, human activities like overgrazing and urbanization have led to decreases in Ku-VOD in northern and southwestern China, and in C-VOD in northeastern, eastern, central, southwestern, and southern China. In all, the relative roles of climate and human factors varied in different regions when NDVI, GPP, or VOD were individually considered. Our results highlighted that the regional-scale vegetation conditions should be taken into full account to achieve sustainable management of ecosystems.
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The last millennium (LM, 1000–1850 AD) is crucial for studying historical climate change on decadal to multidecadal timescales. The summer surface air temperature (SAT) evolutions on regional scales (e.g., over China) are more uncertain than the globe/Northern Hemisphere, especially in response to external forcing factors and internal climate variability. Here we provide one‐signal (full‐forcing) fingerprints of summer SAT in China derived from three large ensemble model archives with a multi‐proxy reconstruction during the LM, Little Ice Age (LIA, 1451–1850 AD), and Medieval Climate Anomaly (MCA, 1000–1250 AD), respectively. Our results show that (1) SATs in the northeast, southeast, northwest, and Tibetan Plateau regions of China show evident decreasing trends during the LM. External forcing response from all model archives agrees with the regional SAT reconstruction but underestimates variability in northwest China at the multidecadal timescale. (2) During the LIA, the summer regional SAT exhibits a cold condition in the reconstruction and simulations, especially in the northeast and northwest regions of China. External forcing responses in most model archives are the dominant factor on multidecadal SAT evolutions in the southeast, northeast, and Tibetan Plateau regions of China and decadal SAT evolutions in northwest China. (3) During the MCA, detection and attribution of SAT shows that internal climate variability dominates in southeast, northeast, and Tibetan Plateau regions of China, but external forcing dominates in northwest China at decadal to multidecadal timescales. These results contribute to a better understanding of the causes and mechanisms of regional climate change. This article is protected by copyright. All rights reserved.
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In this paper, we briefly report the first analysis results of the global annual mean Land Surface Air Temperature (LSAT) changes during different periods since 1901 based on the newly developed CMA GLSAT-v1.0 data set. The results show that the upward trends of annual mean LSAT for Sothern Hemisphere, Northern Hemisphere (NH) and the globe were 0.088℃/decade, 0.115℃/decade and 0.104℃/decade, respectively. The global land surface warming trends during 1979-2014 were considerably higher than those of the entire time period (1901-2014), with particularly large trends occurring in the high latitudes of the NH. A high incoherence in global LSAT changes can be seen for the recent “warming hiatus” (1998–2014), with the abnormal warming in Arctic areas neighboring the Eurasian Continent and North Atlantic Ocean, and remarkable cooling at the low and mid- latitudes of the hemispheres, especially in the boreal cold season.