Global and Planetary Change 112 (2014) 79–91
Contents lists available at ScienceDirect
Global and Planetary Change
journal homepage: www.elsevier.com/locate/gloplacha
Recent climate changes over the Tibetan Plateau and their impacts on
energy and water cycle: A review
Kun Yang a,⁎, Hui Wu a,b, Jun Qin a, Changgui Lin a,b, Wenjun Tang a, Yingying Chen a
a
b
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
a r t i c l e
i n f o
Article history:
Received 18 May 2013
Received in revised form 9 November 2013
Accepted 2 December 2013
Available online 5 December 2013
Keywords:
warming
wind stilling
solar dimming
thermal forcing
water cycle
Bowen ratio
a b s t r a c t
The Tibetan Plateau (TP) exerts strong thermal forcing on the atmosphere over Asian monsoon region and supplies water resources to adjacent river basins. Recently, the Plateau experienced evident climate changes, which
have changed atmospheric and hydrological cycles and thus reshaped the local environment. This study
reviewed recent research progress in the climate changes and explored their impacts on the Plateau energy
and water cycle, based on which a conceptual model to synthesize these changes was proposed and urgent issues
to be explored were summarized.
The TP has experienced an overall surface air warming and moistening, solar dimming, and wind stilling since the
beginning of the 1980s. The surface warming depends on elevation and its horizontal pattern is consistent with
the one of the glacier change. Accompanying the warming was air moistening, and both facilitated the trigger of
more deep-clouds, which resulted in solar dimming. Surface wind speed declined from the 1970s, as a result of
atmospheric circulation adjustment caused by the differential surface warming between the Asian highlatitude and low-latitude.
The climate changes had weakened the thermal forcing over the TP. The warming and wind stilling lowered the
Bowen ratio and led to less surface sensible heating. Atmospheric radiative cooling was enhanced, mainly by outgoing longwave emission from the warming planetary system and slightly by solar radiation reflection. Both processes contributed to the thermal forcing weakening over the Plateau. The water cycle was also altered by the
climate changes. The wind stilling may have weakened water vapor exchange between the Asia monsoon region
and the Plateau and thus led to less precipitation in the monsoon-impacted southern and eastern Plateau, but the
warming enhanced land evaporation. Their overlap resulted in runoff reduction in the southern and eastern Plateau regions. By contrast, more convective precipitation over the central TP was triggered under the warmer and
moister condition and yielded more runoff; meanwhile, the solar dimming weakened lake evaporation. The two
together with enhanced glacier melts contributed to the lake expansion in the central TP.
© 2013 Elsevier B.V. All rights reserved.
1. Introduction
The Tibetan Plateau (TP) is an elevated region in the central Asia and
stretches about 1000 km along latitude and 2500 km along longitude
(Fig. 1). It is the highest plateau in the world, with an average elevation
exceeding 4000 m ASL (above sea level) and an area of about
2.5 × 106 km2. Its climate and environment are influenced by both
westerlies and Asian monsoon, and, in turn, the Plateau modifies the climate of the adjacent and remote regions (Zhou et al., 2009). The TP is
often called “Third Pole” and is subjected to strong interactions among
the atmosphere, hydrosphere, cryosphere, and biosphere. In terms of
regional energy cycles, the Plateau exerts a huge thermal forcing on
the mid-troposphere over the middle-latitude of the Northern
⁎ Corresponding author at: Institute of Tibetan Plateau Research, Chinese Academy of
Sciences, Bldg 3, Courtyard 16, Lincui Rd, Changyang, Beijing, 100101, China. Tel.: +86
10 84097094; fax: +86 10 84097079.
E-mail address: [email protected] (K. Yang).
0921-8181/$ – see front matter © 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.gloplacha.2013.12.001
Hemisphere during spring and summer (Flohn, 1957; Ye and Gao,
1979). The thermal forcing effectively enhances the Asian summer
monsoon and modulates its variability (Yanai et al., 1992; Wu et al.,
2012). The surface heating also triggers vigorous deep convections
over the TP (Yang et al., 2004) that greatly enhance the troposphere–
stratosphere exchanges of water vapor and air pollutants (Fu et al.,
2006). In addition, this region is the headwater areas of major rivers
in Asia; particularly, it provides a large portion of water resources for
economical activities in the oases of Northwest China (Yao et al., 2004).
Over the past three decades, the Plateau experienced evident climate
changes (Kang et al., 2010), which have changed atmospheric and hydrological cycles and thus reshaped the local environment. For instance,
river discharge and lake levels have responded to the climate changes
(Cao et al., 2006; Ye et al., 2007). On the central Plateau, lakes expanded
rapidly since the middle of the 1990s, which flooded surrounding grasslands and threatened the local economy and living. Glacier retreat due
to warming was suggested to be the major cause of the expansion of
glacier-fed lakes (Zhu et al., 2010). The warming also caused permafrost
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K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
Fig. 1. The terrain of the Tibetan Plateau and its surroundings. Major atmospheric circulation systems around the Plateau are shown, with yellow arrows for summer and blue arrows for
winter. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
degradation (Cheng and Wu, 2007) and shortened the soil frozen period
by approximately half a month per decade over the period of
1988–2007 (Li et al., 2012). Along with the climate changes, surface
pressure over the Plateau increased significantly (Moore, 2012), and
surface heating and atmospheric heating became weakened (Zhu
et al., 2007; Duan and Wu, 2008; Yang et al., 2011a, 2011b). This
warming and thermal weakening in spring and summer may affect
summer precipitation downstream (Wang et al., 2008; Ding et al.,
2009; Liu et al., 2012; Duan et al., 2013). In addition, Immerzeel et al.
(2010) projected that the warming may lead to less water resources
for the downstream regions in the future. Therefore, the TP climate
changes have become the concerns of both the local and surrounding
people, and the “Third Pole Environment” program was initiated to
pool international efforts to understand climate and environment
changes on the Plateau (Yao et al., 2012a).
In order to understand the processes of the regional water and energy
cycle, several field campaigns have been conducted in the TP since the
1990s (Koike et al., 1999) and hydro-meteorological observations were
further enhanced in recent years (Ma et al., 2008; Xu et al., 2008; Su
et al., 2011; Yang et al., 2013). These field activities have advanced our
understanding to the land–atmosphere interactions (e.g. Yamada and
Uyeda, 2006; Ma et al., 2009; Zhang et al., 2012; Ueno et al., 2012), and
supported the development of land surface models (e.g. Yang et al.,
2009a; van der Velde et al., 2009; Chen et al., 2010; Gerken et al.,
2012) and satellite remote sensing (e.g. Ma et al., 2011; Chen et al.,
2013). These model improvements are crucial steps for understanding
the response of water and energy budgets to the climate changes.
In this paper, we first reviewed recent findings in climate changes
over the TP. We then focused on the processes and mechanisms how
the water and energy budgets responded to the climate changes, following which a conceptual model is proposed to synthesize these climate changes and their impacts, in terms of the relationship between
local warming and regional warming and in terms of the water and energy exchanges. Finally, relevant urgent issues to be clarified were
recommended.
2. Observed climatic changes
The China Meteorological Administration (CMA) provided longterm station data for climate change studies in the TP region. These
stations are sparsely distributed on this region and their operations
started in different years and some stations were not regularly operated
for some early years. In this review, we mainly addressed the climate
changes over 1984–2006, because this period has not only accumulated
more surface data for climate studies but also experienced outstanding
climate changes over the TP. In addition, radiation budget data from satellites, as a complement to station data, became available over this period. Nevertheless, the decadal changes in wind speed and solar radiation
are complex, so their investigations were extended to the 1960s and the
results were compared with the case in Mainland China.
Fig. 2 shows an overview of the climate changes over the TP, including the observed linear trends in annual mean air temperature, air humidity, wind speed, and pan evaporation at the individual Plateau
stations over 1984–2006. The air temperature and specific humidity increased significantly, with more warming over the North TP while more
moistening over the South TP (Fig. 2a–b). The overall rapid warming
since the 1980s was reported in many previous studies (e.g. Liu and
Chen, 2000; Guo and Wang, 2012) and was also qualitatively produced
with satellite data (Salama et al., 2012). The wind speed significantly declined at almost all stations over this period (Fig. 2c), which is consistent
with the prevailing wind stilling occurring over Mainland China since
the beginning of the 1970s (Xu et al., 2006; Jiang et al., 2010). Meanwhile, the pan evaporation dropped, as reported in previous studies
(Zhang et al., 2007; Zhang et al., 2009), except at the Northeast TP. Details of these trends have been investigated by combining satellite data,
reanalysis data, and model simulations in recent studies, and their
major results are summarized below.
2.1. Spatial variability of surface temperature change
The environmental changes over the Plateau are mostly associated
with the rapid surface warming. Understanding the elevationdependence is crucial for the assessment of glacier/snow dynamics. According to station data, Liu and Chen (2000) showed that the warming
was elevation-dependent. Qin et al. (2009) confirmed the differential
warming rates between stations above 3000 m ASL (above sea level)
and stations below 3000 m ASL and found that their difference was amplified since 2000 (0.1 K year−1 in the region between 1000 and
3000 m and 0.21 K year−1 in the region above 3000 m). However, little
was known about the warming status for regions above 5000 m ASL,
K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
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Fig. 2. Trends in air temperature, specific humidity, wind speed and pan evaporation over 1984–2006 at the individual CMA stations on the Tibetan Plateau. The solid triangle symbol indicates a trend passes the t-test (p b 0.05) and its size indicates the magnitude of the trend. Panel (a–c): modified from Fig. 4 in Yang et al. (2011c).
where most glaciers and snow surfaces are located but no CMA station is
available. Also, the vast western Plateau has very few stations. Therefore, Qin et al. (2009) utilized satellite data to investigate the recent
temperature change over the Plateau.
Qin et al. (2009) evaluated several MODIS monthly products of
nighttime land surface temperature (LST); they found that version 4
of MODIS LST data is able to reproduce the station-observed trend,
whereas the latest version does not. The observed warming at the individual CMA stations is not always comparable to the MODIS-derived
one at the collocated pixel, but the latter approaches the former if averaged over multi-sites (~10 stations). This indicates that their differences
in spatial representativeness may be effectively eliminated through the
spatial average.
Based on this evaluation, version 4 of the MODIS LST product was applied to investigate the elevation-dependence of the warming over the
Plateau. Fig. 3a shows the warming rate averaged over all pixels within
each 200 m-elevation interval (the value given over each bar represents
the number of MODIS pixels used for averaging the warming rate). The
warming rate is clearly elevation-dependent: increased from 3000 m to
4800 m ASL, then became relatively stable between 5000 m and
6200 m ASL, and finally diminished near the highest elevations. Simultaneously, Liu et al. (2009b) projected the warming over the Tibetan
Plateau with a general circulation model and found a very similar
elevation-dependence pattern. The increasing pattern below 4800 m
has been reported before (Liu and Chen, 2000). The decreasing trend
above 6200 m ASL is a new finding but it is understandable. The land
surfaces in this elevation range protrude into the middle-high troposphere and only occupy a small fraction of the space (as seen by the
pixel number in Fig. 3a), so the surface warming over the very high elevations actually denotes the warming status of the mid-troposphere,
which decreases with respect to the increase of elevation. However,
the relatively stable warming rate between 5000 m and 6200 m ASL
is unexpected in terms of the extrapolation of the station-derived
elevation-dependence. Possibly, the presence of snow or a glacier that
is typical above 5000 m ASL resists further warming through both
reflecting solar radiation by the surface and exhausting energy by icemelting. Another possibility is that this elevation range is a transitional
zone between the increasing trend in the lower elevation and the decreasing trend in the higher elevation and thus the warming rate becomes stable.
The horizontal distribution of surface temperature change derived
from the MODIS LST data was shown in Fig. 3b. It is clear that warming
is a dominant phenomenon on the Plateau over recent years. The most
warming areas are the southeastern TP and East Himalayas, a major glaciated area. Surprisingly, the west of 80°E, another major glaciated area,
exhibited a strong cooling. In response, the glaciers in the southeastern
TP and East Himalayas retreat the most rapidly (Yao et al., 2012b),
whereas the glaciers in Karakorum and Western Kunlun Mountains
were found fairly stable and even advancing (Scherler et al., 2011; Yao
et al., 2012b).
In short, this study proves the feasibility to detect surface warming
by remote sensing, although the time series used here is too short to detect the decadal change of the surface temperature. Along with the improvement of remote sensing technique and the extension of the
observing period in the future, satellite observations can play an irreplaceable role in climate change studies.
2.2. Wind speed change
Since the beginning of the 1970s, wind speed over China declined
(e.g., Xu et al., 2006; Jiang et al., 2010) and it declined more over the
TP (Yang et al., 2011c). Several hypotheses have been proposed to explain the wind stilling over China, such as effects of urbanization and
air pollution. However, these factors cannot play an important role in
weakening wind speed over the Plateau, due to negligible urbanization
and low-level aerosol load over there. Vautard et al. (2010) found that
the wind stilling actually occurred widely over the Northern Hemisphere, and they concluded that the wind stilling can be largely explained by an increase in surface roughness over the past decades.
This may explain the contrast trends between surface wind speed and
upper-air wind speed occurring over Europe and North America, but it
is not applicable to the case over the Plateau, where bare soils and
short grasses are the dominant land types and the surface aerodynamic
roughness lengths are generally small (mm–cm). Furthermore, the
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K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
Fig. 3. Nighttime surface temperature change over 2000–2006 on the Tibetan Plateau. (a) Elevation-dependence of temperature change estimated from MODIS LST (version 4). The number of pixels within each 200 m elevation interval is given above each bar (after Qin et al., 2009); (b) The spatial variation of MODIS LST change at 0.5 degree grids.
major part of the Plateau is vegetation-free in wintertime, when wind
speed decelerated, too. So, it is unlikely that the TP wind stilling was
caused by an increase in the surface roughness.
Instead, Zhang et al. (2009) showed that in NCEP reanalysis the summertime pressure gradient force over the Plateau declined over the
wind stilling period, and they attributed the wind decline to the adjustment of atmospheric circulation. Duan and Wu (2009) based on numerical modeling, further suggested that more warming over the highlatitude of Asia may be responsible for this weakening. To further
understand characteristics of the wind speed change over this region,
Lin et al. (2013) analyzed the longer-term variations of wind speed
using both CMA data and IGRA (Integrated Global Radiosonde Archive;
Durre et al., 2006) data, in which they not only provided direct evidence
to support the finding by Duan and Wu (2009) but also revealed some
new features, as explained below.
Since 1960, wind speed over China experienced three stages: jump
of wind speed around 1970, a follow-on long-term decline until 2002,
and a stable and even recovery trend afterwards. Fig. 4a shows the
case for the TP. The jump of wind speed around 1970 is so outstanding
that one may suppose that this was a spurious one. Lin et al. (2013) presented a cross-check to justify the jump. A wind speed and ground–air
temperature gradient (Tg − Ta) together determine the sensible heat
flux. If sensible heat flux dominates the surface energy budget, a high
wind speed usually results in a low value of Tg − Ta, and vice versa.
This negative correlation between wind speed and Tg − Ta may be
used to judge the reasonability of the wind jump. As in Fig. 4a, during
the spring (MAM), a season with strong sensible heat flux, there is indeed a strong negative correlation between the wind speed and
Tg − Ta. Around 1970, the jump of the wind speed corresponds to a significant drop of Tg − Ta; afterwards, the steady decrease in wind speed
K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
83
Fig. 4. (a) Variations of annual mean surface wind speed (U) and ground–air temperature difference (Tg − Ta) over 1961–2006 on the Plateau; (b) Variations of 500-hPa geopotential
height pressure difference (“HGT”) derived from NCEP reanalysis data and surface temperature difference (“TEMP”) derived from CRU data between a low latitude belt (20°N to 25°N)
and a high latitude belt (45°N to 50°N) over 1961–2006 in China (after Lin et al., 2013).
is in contrast to the increase in Tg − Ta. Because wind speed, air temperature and ground temperature were measured independently, the opposite changes prove that the jump of the wind speed around 1970
and the follow-on wind stilling are very likely.
The jump and decline exhibit neither a diurnal cycle nor a seasonal
cycle (not shown), indicating that the wind speed change was controlled by processes that have a scale beyond the atmospheric boundary
layer. This can be further substantiated by the coherent changes between the surface wind speed and upper-air wind speed (see details
in Lin et al.). In addition, another important finding is the elevationdependence of the wind speed variability over China: the higher the elevation, the more the wind speed changed. In other words, the decadal
variability of the surface wind speed over the Plateau is larger than the
one over the rest of Mainland China. This fact implies that the signal of
wind decline is transferred from the upper-air into the boundary
layer. The wind speed over highlands may earlier respond to atmospheric adjustment than the one over lowlands; therefore, the recent
recovery of wind speed over the TP might be a precursor of the overall
change in atmospheric circulation over East Asia.
Lin et al. (2013) presented observed evidence that the wind speed
change over China (including the Plateau) is due to the latitudinal gradient of surface warming over Central and East Asia. As shown in
Fig. 4b, the difference in 500-hPa geopotential height between a low
latitude belt (20°N to 25°N) and a high latitude belt (45°N to 50°N) in
this region (70°E to 140°E) is highly correlated with the difference in
surface temperature between the two belts, with correlation coefficient
R = 0.86. As the anomaly of the temperature difference reflects the differential warming between the two latitude belts, the high correlation
in Fig. 4b indicates that the latitudinal gradient of surface warming is
an essential factor that first changed the upper-air pressure gradient
force through lifting the geopotential height, then changed the upper-
air wind through geostrophic adjustment, and finally changed the surface wind speed through downward momentum transport into the
boundary layer. This substantiates the modeling results in Duan and
Wu (2009). Specifically, during the period of wind stilling, the Siberian
region got more warming than the south of China; during the recent period of wind speed recovery, the Siberian region received more snowfall
(Ghatak et al., 2012) that may have suppressed its rapid warming.
2.3. Solar radiation change
Solar radiation is an important indicator of global climatic changes. A
number of studies (e.g. Stanhill and Cohen, 2001; Liepert, 2002; Wild
et al., 2005) suggested that there was a transition from global dimming
to brightening around the end of the 1980s or beginning of the 1990s.
Several radiation studies also stated that China had a similar transition
(e.g., Che et al., 2005; Liang and Xia, 2005). Herein, we introduce a recent revisit to this issue.
A trend in solar radiation is so small and its estimate is sensitive to
measurement errors, so quality control to station data is a prerequisite
for the trend analysis (Shi et al., 2008). Tang et al. (2010) presented a
method to control data quality of radiation measurement in China.
After excluding spurious data and inaccurate measurements, there remain only ten radiation stations with long-term reliable records for
the years from 1979 to 2006. Therefore, the radiation stations valid for
detecting the radiation trend over China are very limited.
Alternatively, Tang et al. (2011) combined data at all CMA routine
stations and radiation stations to revisit the radiation trend over the
whole China, with a focus on the Plateau region. A widely-validated hybrid model was used to estimate solar radiation from sunshine duration
data and other meteorological measurements at all CMA stations. The
model was validated in terms of radiation trends against the observed
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K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
Fig. 5. (a) Variations of observed annual mean daily sunshine duration averaged over China and over the Plateau; (b) Variations of estimated annual mean solar radiation averaged over
China and over the Plateau (modified from Fig. 6 in Tang et al., 2011). The star symbol (*) denotes a trend that passes the significance test (p b 0.05). The unit of the trend is W m−2 year−1;
(c) Linear trend slope of annual mean solar radiation at the individual Plateau stations over 1984–2006. The solid triangle symbol indicates a trend passes the t-test (p b 0.05) and its size
indicates the magnitude of the trend.
K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
ones from the ten quality-verified stations and the derived ones by an
artificial neural network (ANN)-based model at all CMA radiation stations. Finally, the radiation data simulated by the hybrid model was
used to extend the radiation trend analysis to all CMA stations and to
a longer period.
Fig. 5a shows the changes of annual mean daily sunshine duration
averaged over all CMA stations in both the TP and Mainland China.
The sunshine duration averaged over the Mainland China decreased
since the 1960s, but it became stable since 1990. The sunshine duration
averaged over the Plateau is greater than the one over Mainland China,
due to lower values of air mass, aerosol loads, and humidity over the
Plateau. More importantly, the sunshine duration over the TP exhibits
an increasing trend up to the end of the 1970s and a persistent decreasing trend afterwards. Clearly, the decadal change in sunshine duration
over the TP is different from the one averaged over the whole China.
The variation of solar radiation exhibits a decadal change similar to
the sunshine duration. As shown in Fig. 5b, the solar radiation averaged
over all CMA stations has a decreasing trend before the 1990s, but it
does not show an overall recovery trend since 1990. This result is somehow different from previous studies that stated solar radiation in China
was recovering since 1990. In addition, the solar dimming rate before
1990 is about 2.5 W m−2 decade−1, which is about half of the values
(4–5 W m−2 decade−1) in previous reports. On the Plateau, the averaged solar radiation had an increase trend until the end of the 1970s
and went down afterwards, indicating a transition from brightening to
dimming around the end of the 1970s. Therefore, the solar radiation
changes over the last 50 years are quite different between the TP and
Mainland China. Fig. 5c shows the solar radiation changes at the individual Plateau stations for the period of 1984–2006. It is evident that the
dimming occurred at most of the stations over this period. A further
analysis shows that the dimming mainly occurred in summer.
Conventionally, a solar radiation trend is explained by aerosol loads
and/or cloud changes. The Plateau region is one of the cleanest regions
in the world and a considerable aerosol loading is not expected. Meanwhile, the total cloud cover decreased over the region, which is neither
able to explain the solar dimming. To understand the mechanism of the
solar dimming, Yang et al. (2012) analyzed the effects of aerosols, water
vapor, and cloud cover. First, the inverse of visibility, a proxy of aerosol
optical depth (AOD) (Wang et al., 2009), observed at CMA stations has a
downward trend since 1980. The major aerosol over the TP is dust (Xia
et al., 2011). Along with the wind stilling, dust amount and frequency
should have decreased and thus AOD decreased, too. This is consistent
with the observed trend in Fig. 6a. Therefore, it is unlikely that aerosol
loading can explain the solar dimming. Second, an increase in water
vapor amount is highly correlated with the solar dimming (Fig. 6b),
but the direct absorption of solar radiation by the vapor (~1 W m−2)
is much lower than the observed dimming (~ 6 W m−2). Third, deep
cloud cover (DCC) is highly correlated with the solar radiation at both
annual and decadal scales. DCC can be given by the International Satellite Cloud Climatology Project (ISCCP) data or approximately represented by the station-observed low cloud cover (LCC), and Fig. 6c shows that
LCC has an increasing trend, opposite to the decreasing change in solar
radiation. Such an opposite correlation can be seen in satellite observations, too. The increase in DCC is caused by the increase in convective
available potential energy (CAPE), which is in turn due to the rapid
warming and moistening over the TP. In summary, it is important for
the radiation trend analysis to discriminate cloud types, in addition to
the often mentioned cloud cover and aerosol changes.
3. Response of energy and water cycles
3.1. Land and atmospheric energy budget
Because of the importance of the Plateau thermal forcing in the context of the Asia monsoon, there have been a number of studies since the
end of the 1970s to quantify the heat source over the TP and its effect on
85
Fig. 6. Inter-annual variations of (a) the proxy of AOD (i.e. inverse of visibility) and wind
speed, (b) solar radiation and specific humidity, and (c) solar radiation and deep cloud
cover (DCC) over 1984–2006. All the values are obtained by averaging over all CMA stations on the Plateau. Panel (b–c): modified from Figs. 3–4 in Yang et al. (2012).
various weather and climate events. The total heat source (TH) comprises of three components, i.e., surface sensible heat (SH), latent heat
release of condensation (LH), and radiative convergence (RC). Their estimation was first presented in Ye and Gao (1979) and followed by
many studies (e.g. Chen et al., 1985; Zhao and Chen, 2000).
The surface sensible heat flux is usually calculated according to the
bulk heat transfer equation, which needs input of observed wind
speed and ground–air temperature difference (Tg − Ta) as well as parameterized heat transfer coefficient CH. Conventionally, CH is either
given a constant value (Chen et al., 1985) or simply correlated with meteorological variables (Chen and Wong, 1984). These parameterizations
are widely applied in the Plateau heating studies. For instance, Duan and
Wu (2008) used the Chen Scheme and found a weakening trend in sensible heat flux. However, near-surface atmospheric stability depends on
wind speed and Tg − Ta; with the wind stilling and increase in Tg − Ta,
the atmosphere became more unstable and thus CH should have increased. So, a CH scheme that does not properly account for the stability
would cause vital errors in estimating the trend in sensible heat flux.
Accordingly, Yang et al. (2009b) developed a new scheme to estimate the heat flux from CMA station data. The new one disaggregates
CMA station data to hourly to capture the diurnal variations of
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K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
atmospheric stability, and then, uses the Monin–Obukhov similarity
theory to account for the stability effect. Yang et al. (2011a) applied
this parameterization to the Plateau, in comparison with one conventional scheme given by Chen and Wong (1984) and another by Chen
et al. (1985). As shown in Fig. 7, the estimated trend over the
period of 1984–2006 is sensitive to the selected scheme. The Chen and
Wong scheme assumes a linear relation between CH and the inverse of
wind speed and thus CH increases too quickly with the wind
stilling; as a result, it yields a positive trend in the sensible heat flux
(0.3 W m−2 decade−1). By contrast, the Chen scheme assumes a constant value of CH and thus ignores the effects of the atmospheric stability
trend on CH, so it gives a strong negative trend (−2.5 W m−2 decade−1).
The new scheme designed by Yang et al. (2009b) considers both diurnal
variations of heat transfer and the atmospheric stability, and it yields a
moderate decadal decreasing trend (− 1.2 W m−2 decade−1). Guo
et al. (2011) used observed 6-hourly data and shows a trend similar to
Yang et al. (2011a), after considering the diurnal variations of the land–
atmosphere coupling intensity.
The trend in the sensible heat flux was also investigated with land
surface modeling driven by CMA data (Yang et al., 2011c). The land surface model (LSM) was the Simple Biosphere Scheme (SiB2; Sellers et al.,
1996), with modifications to accommodate the TP environment (Yang
et al., 2009a). The simulation results were validated with surface temperature and a surface energy budget on the western Plateau. Again,
Fig. 8 shows that the simulated sensible heat flux (SH) had a negative
trend, which is comparable to the parameterized result by Yang et al.
(2011a). Zhu et al. (2012) compared several datasets of sensible heat
flux, including reanalysis products and LSM simulations, and they confirmed that the weakening trend in TP sensible heat flux occurred in
most of the datasets. Therefore, all these studies reach a consensus on
the weakening trend in the TP sensible heat flux over the warming
period.
The radiative convergence (RC) is the difference between the net radiation at the top of atmosphere (TOA) and the one at the surface. Usually, this term has negative values, which thus represent a cooling effect.
Based on Tibetan experimental data, Yang et al. (2011b) evaluated the
surface net radiation from the LSM simulation and two satellite products (the Global Energy and Water Cycle Experiment-Surface Radiation
Budget (GEWEX-SRB) and the ISCCP-Flux Data (ISCCP-FD)) and found
that the modeled one has smaller errors. Thus, the surface net radiation
from the LSM simulation and the TOA net radiation averaged on the two
satellite products were used to estimate RC. Fig. 8 shows the trends in
Fig. 8. The land surface modeling-based trend estimate (W m−2 decade−1) of seasonal
mean and annual mean of the heat source terms averaged over the Plateau for the period
of 1984–2006.
the estimated RC. The trends are negative for both seasonal mean
and annual mean, indicating an enhanced cooling. The trend slope is
about 6–8 W m− 2 decade− 1 and much less than the one presented
by Duan and Wu (2008), who calculated this term according to ISCCPFD data only. A further investigation shows that the cooling trend was
mainly caused by the increase in outgoing longwave radiation (OLR)
(by 5–6 W m− 2 decade− 1), and the weakening of the air-absorbed
solar radiation played a secondary role (by 0–2 W m− 2 decade− 1).
The increase in OLR is due to both the warming and the decreasing in
total cloud cover (particularly high cloud cover).
The latent heat release due to vapor condensation is proportional to
surface precipitation and has a large inter-annual variability. We detected no significant temporal trend in the Plateau-averaged latent heat
release.
In summary, the LH trend is not significant, SH declined slightly,
and RC declined much more. As a result, the total heat source (SH +
LH + RC) has a significant negative trend (− 7 W m−2 decade− 1)
and is dominated by the RC trend (Fig. 8). This trend slope is comparable
to the one derived from the NCEP/NCAR reanalysis data by Ding et al.
(2009).
3.2. Land surface water budget
Fig. 7. Variations of anomaly in annual mean sensible heat flux averaged over all Plateau
stations for the period of 1984–2006. The heat flux was estimated using the schemes
given by Chen et al. (1985), Chen and Wong (1984), and Yang et al. (2009b), respectively.
All trends are derived from linear least-squares regressions.
This section introduces how climate changes influenced the surface
hydrological cycle on the TP. As there are limited data of river discharge
and evaporation, the surface water budget was usually investigated by
land surface hydrological modeling. Yang et al. (2011c) validated the capability of the improved SiB2 in simulating the discharge trend for four
large rivers sourced from the central and eastern Plateau. Zhou and
Huang (2012) also showed that this model could reproduce the observed anomaly of the surface water budget in the upper Yellow River
basin. Therefore, the simulated surface water budget presented in
Yang et al. (2011c) was introduced below.
Fig. 9 shows that the surface water balance was changed over the recent decades. In general, evaporation has an overall increasing trend,
which is consistent with a recent independent modeling study (Yin
et al., 2013). Other water budget components exhibit a clear spatial pattern, as indicated by two curved regions. On the central Plateau, we can
see increasing trends in both precipitation and evaporation. The tradeoff of the two trends leads to an increasing trend in runoff, as observed
by Liu et al. (2009a). On the South and the East Plateau, however, we can
see decreasing trends in precipitation while increasing trends in evaporation; both contribute to lowering the runoff. This implies a reduction
of water resources from the Plateau, if the enhancement of the glacier
melts was excluded from the total discharge. The western Plateau has
K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
87
Fig. 9. Trend slope in annual mean values of observed precipitation, simulated evaporation, runoff and soil moisture at the Plateau CMA stations over 1984–2006 (modified from Fig. 4 in
Yang et al., 2011c). The solid triangle symbol indicates a trend passing the t-test (p b 0.05) and its size indicates the magnitude of the trend.
a small amount of precipitation while strong solar radiation; therefore,
the precipitation is almost evaporated and the runoff is negligible.
This spatial pattern of surface water budget corresponds to lake area
changes on the TP. Since the middle of the 1990s, major lakes in the central Plateau have expanded, whereas many lakes along the marginal region of the South and East TP have shrank (personal communication
with Dr. Yanbin Lei). Another analysis (Lei et al., 2013) found that the
increasing runoff simulated by the model could account for the major
part of the lake expansion in the central Plateau, although enhanced glacier melt could be another major contributor to the expansion of some
small lakes.
In addition to the change in precipitation amount, the change in precipitation spatial distribution may also significantly change the surface
water budget, as is the case for the upper Yellow River basin on the
TP. This basin experienced wet conditions in the 1980s and dry conditions in the 1990s. In response, the river discharge had similar change
during the two periods. Since 2002, the precipitation amount increased
drastically, but the discharge still kept a low level. This incoherent
change is attributed to the change in the precipitation spatial distribution (Zhou and Huang, 2012). According to CMA observations, the increase in precipitation occurred in the arid area of this basin, whereas
the humid area received less precipitation than normal. In the arid
area where water availability controls evaporation, most of the precipitation turned into evaporation and the runoff did not increase much
when precipitation increased. In the humid area where energy availability determines the evaporation, evaporation significantly increased due
to the warming; the overlap of the increase in evaporation and the decrease in precipitation led to significant reduction in runoff. The increase
in basin-averaged evaporation almost canceled out the one in precipitation, and thus the discharge did not increased evidently. Therefore, the
change in precipitation spatial distribution changed the relationship between the precipitation, evaporation and runoff.
that the solar dimming played a major role in the pan evaporation reduction on the South Plateau while the wind stilling was more important on the North Plateau.
The opposite trends between the simulated land evaporation
(Fig. 9b) and the observed pan evaporation (Fig. 2d) may be attributed
to a complementary effect (Bouchet, 1963; Brutsaert and Parlange,
1998). As shown in Fig. 10, the sum of the simulated actual evaporation
(E) and the potential evaporation (EP) is roughly equal to 2Ew (Ew is the
evaporation in a wet environment in the absence of advection, i.e. equilibrium evaporation) in wet zones, which is consistent with Bouchet's
hypothesis. Nevertheless, the sum is lower than 2Ew in dry zones, indicating a deviation from Bouchet's complementary theory. The deviation
was attributed by Zhang et al. (2007) and Yu et al. (2009) to low vapor
pressure deficit that may suppress the power of vapor transfer. Note
that the decrease in pan evaporation implies that lake evaporation
may have weakened, due to both solar dimming and wind stilling.
This trend is another factor responsible for the lake expansion on the
central Plateau, in addition to the contribution of increasing runoff and
enhanced glacier melts. Nevertheless, further studies are needed to
quantify the lake evaporation and its trend.
3.3. Response of heat and evaporation to climate change
The decrease in the pan evaporation on the Plateau is a prevailing
phenomenon over the past decades (Fig. 2d). This may be attributed
to both solar dimming and wind stilling. Zhang et al. (2009) showed
Fig. 10. Variations of annual mean evaporation (E) and potential evaporation (Ep) with respect to precipitation amount (P) after normalization by the equilibrium evaporation (Ew)
at the individual Plateau stations (modified from Fig. 8 in Yang et al. (2011c)).
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K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
It is concerned with what caused the decrease in the sensible heat
flux and the increase in the land evaporation (i.e., lower Bowen ratio)
under the warming environment. Herein, we present a simple theory
to explain the response of Bowen ratio to warming and wind stilling. According to the bulk transfer equation:
SH ¼ ρcp C H u T g −T a ;
lE ¼
h i
ρcp
α ðθÞC H u es T g −rh es ðT a Þ ;
γ
ð1Þ
ð2Þ
where SH is the sensible heat flux, lE is the latent heat flux, ρ is the air
density, cp is the specific heat capacity at a constant pressure, γ is the
psychometric constant, CH is the bulk coefficient for heat transfer, Tg is
the ground temperature, Ta is the air temperature, es is the vapor pressure at saturation, and rh is the air relative humidity. α(θ) is a function
of soil moisture (θ) and it has a value near zero for dry soils and approaches unity for wet soils.
The Bowen ratio is given by
T g −T a
SH
γ
h i:
¼
B≡
lE
α ðθÞ e T −rh e ðT Þ
s
g
s a
ð3Þ
As a first-order approximation, we assume that that α(θ) is timeinvariant at a decadal scale. Then, the relative change in Bowen ratio depends on the change in the ground temperature and the air temperature, as follows
∂e
∂es
3
ΔT g −rh s ΔT a 2 ΔT −ΔT
ΔT g −ΔT a
∂T g
∂T a
g
a
ΔB
4
−h þ 15;
i
¼ B
T g ‐T a
T g ‐T a
es T g −rh es ðT a Þ
ð4Þ
where ΔTg is the increase in the ground temperature, ΔTa is the increase
in the air temperature, and ΔB is the change of the Bowen ratio after
warming.
The climatology and trend of meteorological parameters over the
Plateau are derived from CMA station data, which gives Tg = 280.9 K,
Ta = 276.5 K, rh = 56 %, ΔTg = 1.8 °C and ΔTa = 1.4 °C. Given these
conditions, it can be shown with Eq. (4) that the Bowen ratio decreases
by 6% with respect to warming (indicated by the solid circle in Fig. 11),
which indicates that a warming can result in a less sensible heat flux
and more latent heat flux (or evaporation). This qualitatively explains
the sensible heat flux weakening and evaporation enhancement. If in
Eq. (4) we consider the contribution of soil moistening (Fig. 9d) to the
Fig. 11. Response of Bowen ratio to surface air warming (ΔTa) according to Eq. (4), given
Tg = 280.9 K, Ta = 276.5 K and ΔTg = 1.28ΔTa. The solid circle corresponds to the Plateau warming condition (ΔTa = 1.4 °C, ΔTg = 1.8 °C and rh = 56 %).
lowering of the Bowen ratio, then the theory can explain most of the decrease in the LSM-simulated Bowen ratio.
The Bowen ratio response to the warming may be modulated by
wind speed change. If the wind speed slows down, the efficiency of
the energy exchange would decrease; accordingly, the ground would
get warmer (i.e. Tg increases), leading to the decline of the Bowen
ratio. Over the period between 1970 and 2000, both the warming and
wind stilling weakened the Bowen ratio, leading to the decrease in sensible heat flux. Since 2000, however, the warming and wind speeding
up play contrasting roles in determining the trend in the Bowen ratio,
leading to a stable sensible heat flux, as indicated by the parameterization result with the Yang-scheme in Fig. 7.
In addition, other changes on the TP surface may have contributed to
the decadal change of the surface energy partition. The first is the abrupt
increase of snow cover in winter and spring since around 1977 (Ding
et al., 2009). The snow cover cools the surface through albedo enhancement to reduce surface net radiation and through snow melting to exhaust surface net radiation, leading to lower sensible heat flux. The
second is the increase in vegetation density (Zhong et al., 2010). This increase may result in more evaporation and less sensible heat flux and
thus lower Bowen ratios, as shown in Zuo et al. (2011). The third one
is the increase in soil moisture in the Plateau excluding the monsoonimpacted southern and eastern TP (Fig. 9d). This change also enhances
evaporation and weakens sensible heat flux (Zhang and Zuo, 2011).
4. A conceptual model for the Plateau climatic changes
There are a number of studies on the climatic changes over the Plateau, but a general and consistent framework has not been established
for the interpretation of all the changes in the Plateau climate system.
Herein, we proposed a conceptual model to synthesize these changes
and to link these changes with the global warming. This model is
shown in Fig. 12.
Wind stilling is a response of the regional circulation to the changes
in the latitudinal temperature gradient over the Central and East Asia.
Under the background of the global warming, there was more warming
over the high-latitude belt than over the low-latitude belt during the
past three decades. As a result of the adjustment of geopotential height
to the change in thermal contrast, the middle-level pressure gradient
force between the low-latitude and the high-latitude declined
(Fig. 4b), and therefore, the middle-troposphere wind speed became
weakened (Section 2.2). Due to less momentum transport from free atmosphere down to the boundary layer, the surface wind speed declined,
too. This situation over the TP and East Asia is different from the case
over Europe and North America, where the surface wind slowed down
while upper-air wind speeded up and Vautard et al. (2010) attributed
their contrast changes to the increase in surface roughness lengths.
The wind stilling weakened the energy exchange between the Plateau and its surroundings. As the Plateau provides a huge thermal forcing to the middle-troposphere during the summer half-year, a weaker
energy exchange would lead to more remaining energy to warm the
local air over the Plateau. Indeed, we found a correlation coefficient of
0.6 between wind speed and air temperature during summers. So we
speculate that the TP warming during the summer half-year is partially
attributed to the wind speed decline. Other warming causes were also
proposed in the literature. For instance, Chen et al. (2003) suggested
with modeling studies that the TP warming is due to the CO2 effects,
but Rangwala et al. (2009) argued that the enrichment of surface
water vapor enhanced the downward longwave radiation and is thus
responsible for the prominent winter warming trend over the TP. Meanwhile, Zhang and Zhou (2009) found that the total ozone amount over
the TP declined more than the one over other regions along the same
latitudes and thus suggested that the ozone depletion is a possible reason for the more warming over the TP. Similarly,Guo and Wang (2012)
suggested that the most significant warming occurring over the North
TP may be related to radiative and dynamical heating that are results
K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
89
Fig. 12. A conceptual model for interpreting climatic change and associated water and energy budget changes over the Tibetan Plateau.
of pronounced stratospheric ozone depletion. In a word, it is far from
reaching a consensus to the understanding of the TP rapid warming
and its seasonality, as the energy budget responsible for a regional
warming is small while influenced by a lot of factors.
The warming and air moistening over the central Plateau upraised
CAPE, which is favorable to triggering stronger clouds and thus causing
the solar dimming (Section 2.3). The rapid planetary warming led to enhanced radiative cooling through outgoing longwave emission. Meanwhile, the warming and wind stilling lowered the Bowen ratio and
thus reduced surface sensible heat flux. Both processes contributed to
the thermal forcing weakening over the Plateau (Section 3.1), which
in turn might contribute to the Asia monsoon weakening.
The warming enhanced land evaporation overall on the Plateau, but
the solar dimming and wind stilling may result in weaker lake evaporation. The monsoon weakening may result in less rainfall over the monsoon regions (South and East Plateau), whereas the warmer and moister
atmosphere on the central Plateau may trigger more convective precipitation and enhance water cycle. Accordingly, the climatic change may
reduce runoff on the Plateau source areas of Asian large rivers but enhance runoff on the central Plateau (Section 3.2). The latter have contributed to the lake expansion on the central Plateau.
5. Recommendations for future studies
The TP surfaces experienced an overall rapid warming and moistening as well as wind stilling and solar dimming over the past three decades. These changes further influenced the water and energy cycle
over the Plateau: weakened sensible heat flux and lake evaporation, enhanced radiative cooling and land evaporation, and changes precipitation amount and spatial distribution. All the changes may be deemed
as different but inter-dependent aspects of a changing regional climate
system. We proposed a conceptual model that can interpret major
changes observed in the TP region. Meanwhile, some key processes in
the conceptual model need to be strengthened in future studies, as current reanalysis datasets are not able to capture some crucial facts (Wang
and Zeng, 2012). For example, the warming trend over the Plateau is not
observed in NCEP reanalysis data (You et al., 2010), the wind decline is
not observed in ERA-40 and ERA-interim data, the negative trend in the
heat source is not seen in the JRA-25. A conceptual model is helpful for a
consistent and integrated interpretation of observed climatic changes
and for the prediction of the Plateau water and energy cycles from precursor signals of global and regional changes. To reach this goal, we recommend the following outstanding issues to be explored in future
studies.
First, what determines the spatial pattern of the warming? The
warming is the most striking phenomenon on the Plateau, but it has
not been understood why the warming rate over the Plateau is higher
than over the eastern part of China along the same latitude (Zhang
and Zhou, 2009). Moreover, the spatial distribution of the warming
rate within the Plateau is important for interpreting the spatial pattern
of the glacier changes, but what determines the spatially distributed
warming is little known.
Second, is a decadal climatic change occurring over the Plateau and
East Asia? Since the beginning of the 1970s, wind speed declined very
much over both the Plateau and East Asia. However, Lin et al. (2013)
found that the wind speed started to recover over the Plateau since
2002. Simultaneously, the sensible heat flux on the Plateau stopped
dropping. These signals are probably the precursor of a decadal climatic
change over the Plateau and East Asia.
Third, what is the trend in the surface radiation budget? Solar dimming over the Plateau is evident; both downward and upward
longwave radiations should have increased due to the warming. However, the trend in net radiation is far from understanding, as it is sensitive to the change in surface albedo and surface emissivity in addition
to the dimming, warming and moistening. Future studies need to find
a reliable way to quantify net radiation and its trend, in order to understand the warming. Considering that the nighttime warming rate is
greater than the daytime one, we speculate that the trend in net radiation may have a diurnal variation, large in the nighttime and small in the
daytime.
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K. Yang et al. / Global and Planetary Change 112 (2014) 79–91
Last but not least, where is the source of water vapor over central
Tibet? The lake expansion in this region indicates that the water vapor
was transported from outside. In order to understand the hydrological
cycle and its trend in this region, it is crucial to identify the source region
and the transport processes of the water vapor.
Acknowledgments
This work was supported by Global Change Program of Ministry of
Science and Technology of China (Grant No. 2010CB951703), Strategic
Priority Research Program (B) of the Chinese Academy of Sciences
(Grant No. XDB03030300), and National Natural Science Foundation
of China (Grant No. 41190083).
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