Download Effects of Cropland Cover Changes on Regional Climate over

ADVANCES IN CLIMATE CHANGE RESEARCH 4(4): 250-259, 2013
www.climatechange.cn
DOI: 10.3724/SP.J.1248.2013.250
CHANGES IN CLIMATE SYSTEM
Effects of Cropland Cover Changes on Regional Climate
over Western China Based on Simulations
with RegCM3
SHI Xue-Li1 , HE Hui-Juan2 , REN Hong-Chang3
1
National Climate Center, China Meteorological Administration, Beijing 100081, China
2
3
Shaanxi Remote Sensing Information Center for Agriculture, Xi’an 710014, China
Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract
The impacts of land cover changes on regional climate in Shaan-Gan-Ning (SGN) in western China were simulated
with RegCM3. Sensitivity experiments were conducted by replacing crop grids with different new land cover types in
the key area of SGN, where the returning cropland to tree/grass project has been carried out since 1999. The modified
new land cover types include desert, forest, shrub and grass. They represent degraded, improved, and maintained
vegetation cover with natural canopy in the key area. Results from three individual case studies show that the land
cover change causes changes in temperature and terrestrial water variables especially within the key area, while changes
in precipitation are found for a larger area. The strongest changes appear where the cropland is degraded to bare soil,
leading to increasing temperature and decreases in rainfall, evaporation and soil water. Opposite changes occur when
cropland changed into forests, especially with strong increases in soil water. When cropland changed to grass and shrub
land, the climatic changes are closer to those with forest cover. This shows the importance of improving and maintaining
the vegetation in SGN for the ecosystem and regional climate.
Keywords: land cover change; RegCM3; regional climate
Citation: Shi, X.-L., H.-J. He, and H.-C. Ren, 2013: Effects of cropland cover changes on regional climate over western
China based on simulations with RegCM3. Adv. Clim. Change Res., 4(4), doi: 10.3724/SP.J.1248.2013.250.
1 Introduction
In this study we focus on typical arid and semiarid areas of western China, called the Shaan-GanNing (SGN), which includes parts of the provinces of
Shaanxi and Gansu, and Ningxia Hui autonomous region. The SGN is located at the transition zone from
cropland/forest (to the east) to desert (north) and
high land (west) areas, and is characterized by water
shortages and desertification. Therefore, the Chinese
Government has been funding the returning cropland
to tree/grass project since 1999. Shi and Wang [2003]
investigated possible changes in the regional climate
Numerous observation and simulation studies
have shown that land cover changes have important consequences for regional climate and ecosystem
[Pielke, 2005; Gao et al., 2003]. Cropland as a special land type related to human activities has also significant impacts on regional climate in various areas
worldwide, e.g., in China [Zhang et al., 2010], India
[Douglas et al., 2009], and the USA [Cooley et al.,
2005].
Received: 15 March 2013
Corresponding author: SHI Xue-Li, [email protected]
1
SHI Xue-Li et al. / Effects of Cropland Cover Changes on Regional Climate over Western China Based. . .
through this project. They concluded that the afforestation and re-greening of deserted land in western
China was beneficial to the eco-environment, and the
large-scale land cover change in Northwest China may
have the effect of adjusting the East Asian monsoon
system and regional climates in other parts of China.
Observation studies also show that the vegetation has
effectively improved or stabilized after the project [Li
et al., 2010].
In order to further understand the effects of different cropland cover changes, numerical simulations
have been conducted with the regional climate model
RegCM3.
2 Regional climate model and experimental design
The model used in this study is the third generation of the Regional Climate Model (RegCM3),
which was developed at the Adbus Salam International Center for Theoretical Physics (ICTP) based on
RegCM2 of the U.S. National Center for Atmospheric
Research. The detailed information of the model was
introduced in Pal et al. [2007] and other related references. RegCM3 has been applied in numerous areas
worldwide. In China, it has been used for climate simulations [Bao et al., 2006; Gao et al., 2012; Zhang et
al., 2005b], investigations of land cover and land use
change impacts at different scales and regions, such as
251
for the whole China [Gao et al., 2007; Yu and Xie,
2012], North China [Zhang et al., 2005a], and Sanjiangyuan region in the Qinghai-Tibetan Plateau [Lian
and Shu, 2009], with very few studies focusing on the
SGN.
The model has 18 vertical levels and a 30 km
horizontal resolution. There are totally 65×85 grid
points for the key area (34◦ –39◦ N, 104◦ –111◦ E) of
SGN located at the center of the model domain. The
land cover types of RegCM3 have been obtained from
the Biosphere-Atmosphere Transfer Scheme [Dickinson and Henderson-Sellers, 1993].
Three case years are selected according to their
vegetation and climate status. The year 1999, as the
reference year, is characterized by low normalized difference vegetation index (NDVI) values. The years
2004 and 2007, with high NDVI values, have different
temperature and rainfall conditions (Figures omitted).
We hope to find common features of land cover change
impacts on the regional climate under different vegetation and climate conditions. For each case, besides
the control run (noted as CTL), four sensitivity experiments have been made by replacing the cropland grids
of the key area with different land cover types, including desert (type 8 in BATS), deciduous broad tree (5),
short grass (2) and deciduous shrub (17). In Table
1 the details of the experiment designs and principles
are listed. Totally 15 simulations have been conducted
for the numerical investigations.
Table 1 Simulation experiment names and designs
Simulation
CTL
CtoDesert
CtoTree
CtoGrass
CtoShrub
Experiment description
Control simulation with land cover datasets of USGS
Change the cropland grids into desert at the key area, degrading of LC
As CtoDesert, but replace cropland with forest, improving of LC
As CtoDesert, but replace cropland into short grass, maintaining of LC
As CtoDesert, but replace cropland into shrub, maintaining of LC
Figure 1 shows the land cover type distribution
within the key area of SGN, in which crop (red grids) is
majorly located in the middle and eastern part. There
are totally 78 crop grids that will be converted to different types in the different sensitivity experiments.
The integration periods in all experiments are
from February 1 to October 31, with the first month
being the spin-up. Therefore, the analysis focuses on
the period of March–October when crops are growing
in the area.
3 Effects of cropland cover change
At first, the RegCM3-simulated climate features
in the CTL experiments are evaluated. The used
observed monthly temperature and precipitation data-
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ADVANCES IN CLIMATE CHANGE RESEARCH
characteristics as the CTL-simulation, which is reasoned due to the land cover being only one of many
factors impacting (but not controlling) the regional
climate. Hence, the differences between the sensitivity experiments and the CTL-simulation represent the
effects of land cover change in this study.
3.1 Land cover change effects in 1999
Figure 1
Land cover types of the key area (34◦ –
39 N, 104 –111◦ E). The number inside the grid points
◦
◦
denotes the different land cover types.
1-crop/mixed
farming, 2-short grass, 3-evergreen needleleaf tree, 4deciduous needleleaf tree, 5-deciduous broadleaf tree, 7tall grass, 8-desert, 10-irrigated crop, 11-semi-desert, 16evergreen shrub, 17- deciduous shrub, 18-mixed woodland,
19-forest/field mosaic. The red grid points denote croplands, which are changed into different land cover types in
the following sensitivity experiments
sets are from Xie et al. [2007] and Xu et al. [2009],
respectively.
Figure 2 shows the observed and simulated surface air temperature and precipitation of March–
October 1999. The temperature is high in the northern
and north-eastern parts of the key area and relatively
low over the mid-western part. The CTL simulated
temperature is overestimated for the north-western
part (Fig. 2a&b). Although the spatial distribution
is consistently simulated, the model overestimates the
rainfall for the key area (Fig. 2c&d). This weak simulation has been also reported in other researches and
attributed to the convective parameterization schemes
in the regional climate model.
The CTL simulated climate conditions of 2004
and 2007 are generally consistent with the observed,
except that the simulated rainfall is overestimated as
in the CTL 1999 (Figures omitted). Based on this,
the simulation results are used for further sensitivity
experiments.
The sensitivity simulations have similar climatic
3.1.1 Spatial distribution of land surface variables
It is obvious that the changes in surface air temperature are generally constrained at the key area
where the crop grid points are modified, especially
during spring. These changes extend to the neighboring areas in summer and autumn (Figures omitted). In Figure 3, the mean differences between the
sensitivity and the CTL experiments from March to
October are presented. The largest increases in temperature (up to 1.6◦ C) occur in experiment CtoDesert
(Fig. 3a). The temperature is also increasing (up
to 0.8◦ C) in CtoGrass (Fig. 3b). In CtoShrub, the
temperature is increasing at the land cover change
area (mostly by less than 0.5◦ C, Fig. 3c). Decreasing temperatures are found in CtoTree but with a
small intensity (less than 0.3◦ C decrease in absolute
values, Fig. 3d). At seasonal scale, the changes are
generally larger in spring and summer, but small in
autumn. Positive temperature differences appear in
CtoDesert, CtoGrass, and partly in CtoShrub, while
negative changes occur in CtoTree (Figures omitted).
So the temperature showed a direct response to the
land cover change, it is prone to increase when vegetation is less (CtoDesert), but prone to decrease when
vegetation is changed to trees (CtoTree). The inconsistent patterns in CtoGrass and CtoShrub are related
to their different physical properties.
Unlike temperature, the changes in rainfall are
much more complicated, not only in the spatial patterns, but also in the amounts. The largest modifications occur in summer. The mean differences for
March–October 1999 in Figure 3e–g show decreases
in rainfall over the south-eastern part of the key area
and increases over the mid-western part in three sensitivity experiments, i.e., CtoDesert, CtoGrass, and
CtoShrub. Intensive rainfall increases occur in exper-
SHI Xue-Li et al. / Effects of Cropland Cover Changes on Regional Climate over Western China Based. . .
Figure 2
253
Observed (left) and CTL simulated (right) mean surface air temperature (a, b) and precipitation (c, d) of
March–October 1999
iment CtoTree (Fig. 3h). They all show increases to
the east of the key (downstream) areas in four sensitivity experiments (Figures omitted). This is similar to
responses to other initial conditions, like soil moisture
[Chow et al., 2008], and related to the interactions of
land surface and atmospheric processes.
The changes in other land surface variables also
show constraining results in the land cover change
area. For example, the soil water presents the distinct responses to the land cover change in the key
area. The largest water loss appears in CtoDesert,
followed by CtoGrass and CtoShrub. The soil water
only increases a little in CtoTree (Figures omitted).
This means that the improvements of water storage
might need a long time period, even with better vegetation conditions.
3.1.2 Temporal changes
To focus on the temporal changes in the key area,
we analyze the monthly differences between the sensitivity experiments and CTL in 1999. For the temperature and sensible heat flux (Fig. 4a–b), the differences are generally large in spring and summer, and
small in autumn. They are positive (increasing) in
temperature in CtoDesert, fluctuating around zero in
CtoGrass, and CtoShrub, and are negative (decreasing) in CtoTree. As to water related variables, rainfall
increases in CtoTree in spring and summer, but decreases in CtoGrass and CtoDesert in July (Fig. 4c).
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ADVANCES IN CLIMATE CHANGE RESEARCH
Figure 3 Differences of mean surface air temperature (left, in ◦ C) and rainfall (right, in mm d−1 ) in March–October
1999 between sensitivity and CTL experiments, (a, b) CtoDesert minus CTL, (c, d) CtoGrass minus CTL,
(e, f) CtoShrub minus CTL, (g, h) CtoTree minus CTL
SHI Xue-Li et al. / Effects of Cropland Cover Changes on Regional Climate over Western China Based. . .
Figure 3
255
(Continued)
Figure 4 Temporal changes in surface variable differences between sensitivity experiments and CTL (the former
minus CTL) in March–October 1999, (a) surface air temperature, (b) sensible heat flux, (c) precipitation,
(d) evapotranspiration, and (e) soil water at root zone
The evapotranspiration shows the largest decreases in
CtoDesert from March to October, and is followed by
CtoGrass, CtoShrub and CtoTree with lesser magnitude (Fig. 4d). Particular differences occur in soil
water at the root zone (Fig. 4e). The root zone gains
around 70 mm more water in CtoTree shows small
losses (about 10 mm) in CtoShrub and CtoGrass, and
the largest loss in CtoDesert in March (about 40 mm).
The magnitude of soil water change in CtoTree is
larger than that in CtoDesert, which implies the im-
portance of tree cover in the SGN.
3.1.3 Changes in atmosphere
The changes in land surface variables will also impact the vertical atmospheric circulations through the
re-allocations of energy and water components. Some
distinct regional differences exist. From March to October, the temperature increases significantly below
850 hPa in CtoDesert, but slightly decreases below 700
hPa in CtoTree. Slight increases in vertical temperatures also appear in CtoGrass and CtoDesert during
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ADVANCES IN CLIMATE CHANGE RESEARCH
spring and summer (Figures omitted).
Figure 5 presents the vertical profiles of monthly
water vapor differences of the two extreme sensitivity experiments (CtoDesert and CtoTree) and CTL.
There is a shallow decreasing layer (below 900 hPa) in
July in CtoDesert (Fig. 5a) and a deeper increasing
one (below 700 hPa) in June in CtoTree (Fig. 5b).
This is related to the loss (gain) in water supply from
the land surface and soil, and will impact the precipitation characteristics via processes within the atmo-
Figure 5
sphere.
For most surface variables, the impact intensity of
land cover change is the largest in CtoDesert, followed
by CtoGrass, CtoShrub and CtoTree. The changes in
CtoTree are generally opposite (with weaker intensity)
to those in CtoDesert. But the change in the soil water of the root zone is an exception, where the changes
due to land cover change are larger in CtoTree than
in CtoDesert, which is very important to protect and
improve the ecosystem of the SGN.
Vertical profiles of water vapor differences between both CtoDesert (a) and CtoTree (b) with CTL from
March to October in 1999
3.2 Land cover change impacts in 2004 and
2007
The differences between the sensitivity experiments and CTL are also analyzed for 2004 and 2007.
They show generally consistent spatial and temporal
features as for 1999, so only the mean differences of
the two years between the sensitivity experiments and
CTL are presented in this section.
As shown in Figure 6, the surface air temperature
significantly increases in the land cover change area in
CtoDesert (mostly > 0.5◦ C, Fig. 6a), but slightly decreases in CtoTree (Fig. 6c). In CtoDesert, the rainfall decreases in the south-eastern part, but increases
in the north-western and north-eastern part of the key
area (Fig. 6b). In CtoTree, the areas with decreasing
precipitation are getting smaller, while increases are
located in the north-eastern and south-western parts
in the key area (Fig. 6d).
The mean temporal changes in various land surface variables for 2004 and 2007 are shown in Figure 7.
Although the differences between the sensitivity experiments and CTL show some discrepancies in their magnitude, by comparing them with those in 1999, they
possess consistent features. For example, the largest
impacts occur in CtoDesert when replacing cropland
with desert. Here, the temperature (Fig. 7a) and sensible heat flux (Fig. 7b) are increasing in spring and
summer, while evapotranspiration and soil moisture
(Fig. 7d&e) are decreasing. The differences in precipitation are the most significant in summer in CtoGrass
(Fig. 7c), again reflecting that the rainfall characteristics as response to land cover change are non-linear
and case-dependent.
SHI Xue-Li et al. / Effects of Cropland Cover Changes on Regional Climate over Western China Based. . .
Figure 6
257
Differences of mean surface air temperature (left) and rainfall (right) between the sensitivity and CTL
experiments in 2004 and 2007, (a, c) CtoDesert minus CTL, (b, d) CtoTree minus CTL
Consequently, different cropland cover changes
show various consequences, in which the worst is the
degradation of vegetation (CtoDesert). The processes
potentially involved are related to energy and water
changes. The degradation of cropland can cause the
land surface and overlying atmospheric temperature
to increase, which might influence the wind velocity,
etc. At the same time, the soil moisture (especially
that of the root zone) and evapotranspiration are decreasing, which leads to fewer water supplies to the
atmosphere, and hence tempers with rainfall characteristics. In contrast, a better vegetation cover (like in
CtoTree) leads to decreases in temperature and sensible heat flux in spring and summer, and most impor-
tant, increases the soil moisture effectively, which is
crucial for the ecosystem and moisture supply to the
atmosphere. The introduced experiments prove the
key role of vegetation protection and improvement in
the SGN.
4 Conclusions and discussion
The RegCM3 simulations have shown that different cropland cover changes have various effects on
the regional climate of the Shaan-Gan-Ning area. In
summary: 1) The most obvious impacts of land cover
change appear in spring and summer temperature,
especially with the degradation of cropland to semi-
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Figure 7
ADVANCES IN CLIMATE CHANGE RESEARCH
Same as Figure 4, but for the mean differences of 2004 and 2007 between all sensitivity experiments and
CTL from March to October
desert (CtoDesert). 2) The changes in temperature
and soil water are constrained within the key area
as direct responses of land cover change, while those
in precipitation are extending to the whole domain.
3) The changes in experiment CtoTree are generally
opposite to those in experiment CtoDesert but with
less intensity or magnitude, while those in experiments
CtoGrass and CtoShrub range between them.
The numerical experiments in this study focus on
the impacts of changes in one particular land cover
type (crop), and the land cover change is set artificially with no consideration of the remote sensing observations. Further investigations and statistical diagnostics in the mechanisms of the land cover change
impacts are needed. Additionally, only three case
years have been studied for the land cover change
effects, while continuous integrations for multi-year
would guarantee more reasonable statistical significance. Finally, the impacts of cropland changes on the
regional climate in this study have been realized only
by the use of some assigned parameters (i.e., roughness length and conductance coefficients), but do not
include the dynamical crop processes (as in Chen and
Xie [2012]). By using updated regional climate models with improved dynamical vegetation processes in
the near future, we will get more detailed information
on the impacts of land cover change on the regional
climate.
Acknowledgements
The authors are very grateful to the anonymous reviewers and editors for their constructive comments and
suggestions. The study was jointly supported by the Special Research Program for Public-Welfare Forestry (No.
200804001), Meteorology (No. GYHY2011060114-3), and
the 863 Project (No. 2009AA122005).
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