Download stxb201112292007 Varying responses in mean surface air

stxb201112292007
Varying responses in mean surface air temperature from land use/cover
change in different seasons over northern China
Siyan Donga,b,c; Xiaodong Yana,d,*; Zhe Xionga
a
Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of
Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
b Graduate University of the Chinese Academy of Sciences, Beijing 100049, China
c
National Climate Center, Beijing 100081, China
d Beijing Normal University, Beijing 100875, China
Abstract: Research on the impacts of land use change on climate change has become a foremost
topic in the field of global climate change research. Although many researchers have studied the
impacts of LUCC, data related to these impacts on the Chinese climate system remain sparse
because of the diversity of China's regional changes in land use, especially related to agricultural
changes. Therefore, additional studies are needed that address regional LUCC in combination with
climate modeling. Two simulations with current land use/cover patterns and potential natural
vegetation cover were used to investigate the impact of LUCC on surface air temperature in
northern China. Simulations of 11 years of climate in northern China (1 January 1990 to 31
December 2000) were carried out using Regional Environment Integrated Modeling System 2.0
(RIEMS2.0). The results showed that: (1) When potential natural vegetation cover types were
changed to current vegetation cover types, mean summer surface air temperature decreased in the
central northeastern area, eastern Gansu Province and Ningxia Hui Autonomous Region, but
increased in Shanxi, Henan and Anhui provinces. Also, surface air temperature changed
significantly on a local scale in the central northeastern area, central Henan Province and eastern
Gansu Province (P<0.05). In winter, major portions of the study area exhibited non-significant
decreases in mean surface air temperature. (2) In summer, a temperate forests removal simulation
in northern China behaved more like a tropical forests removal simulation. In winter, removal of
the temperate forests in northern China behaved more like a boreal forests removal simulation. In
model grids where forest were converted to cropland, the net radiation absorbed has less influence
on surface air temperature at lower vs. higher latitudes. Further, latent heat flux has a stronger
influence on surface air temperature at lower latitudes.
1 Introduction
Land use refers to the human activities of development and utilization of land resources.
Agricultural, forestry, traffic, and residential lands represent different land use types. Land use
change is directly related to land cover change. Land cover refers to the natural surface formation
or human-induced land cover situation. Land cover includes the earth's land surface and
near-natural state of the ground surface, mainly referring to the land's natural attributes, including
the result of human activity [1]. Therefore, land use/cover change (LUCC) is the result of the
*Corresponding author
E-mail address:[email protected](X.D. Yan)
impacts of two aspects about natural variation of the earth system and human activity. However,
land development and utilization of the earth surface associated with several thousand years of
human activity is the main reason for changes in land cover.
Human activities result in deforestation, expansion of cropland, grassland degradation,
urbanization and other large-scale LUCC, among which deforestation and cropland expansion are
two of the most important processes. These processes alter the physical properties of the land
surface, such as albedo and roughness of the surface, thereby affecting land-atmosphere material
and energy exchange. Many researchers have found through numerical simulation that
deforestation increases surface albedo at high latitudes, producing cooling [2,3], and it decreases
evapotranspiration in low-latitude (tropical) regions, increasing surface air temperature [4,5].
However, much uncertainty remains regarding deforestation impacts on land-atmosphere
exchange and regional climate in temperate regions [6,7,8].
Northern China is a typical temperate forests area. There are significant expansion of
cropland and human activities in the region, which strongly influence climate and the ecological
environment. In general, climate models have used more realistic vegetation to evaluate the effect
of LUCC on regional climate, and the impact of anthropogenic LUCC on climate was recently
examined using current and natural vegetation datasets. These studies analyzed specific seasons
(winter or summer) [9,10]. Although some studies focused on surface air temperature change from
LUCC in northern China during different seasons [11,12], there was no in-depth analysis of the
causes of these seasonal surface air temperature changes. Therefore, this study would address the
above scientific questions based on potential vegetation cover and current land use/cover data. We
used a high-resolution, long-term integral simulation of a regional climate model (RIEMS2.0) to
reveal impact of anthropogenic LUCC on seasonal mean surface air temperature in northern
China.
2 Methods
The Key Laboratory of Regional Climate-Environment for Temperate East Asia (RCE-TEA)
of the Institute of Atmospheric Physics, Chinese Academy of Sciences, developed the Regional
Integrated Environmental Modeling System (RIEMS2.0), which was built on RIEMS1.0. The
RIEMS2.0 model had better simulation performance for mean surface air temperature,
precipitation and circulation characteristics of the Asian monsoon area over many years [13,14]. It
also showed good performance in the Regional Climate Model Inter-comparison Project [15].
A number of physical parameterizations were incorporated in the model. These include a
state-of-the-art surface physics package, namely the Biosphere-Atmosphere Transfer Scheme 1e
(BATS1e), a Holtslag explicit planetary boundary layer formulation, the Grell cumulus convective
parameterization scheme, and a modified radiation package (National Center for Atmospheric
Research Community Climate Model 3). The Medium Range Forecast planetary boundary layer
scheme was also used.
Initial and lateral boundary conditions for winds, temperature, water vapor, and surface
pressure were extracted from National Centers for Environmental Prediction – Reanalysis II. The
simulation domain encompasses all of northern China and uses a Lambert projection centered on
102°E, 40°N, with horizontal resolution 30 km.
*Corresponding author
E-mail address:[email protected](X.D. Yan)
Fig. 1 Potential natural vegetation cover (PVC)
Fig. 2 Current land use/cover (CLC)
Both experiments with current land use/cover (CLC) and potential natural vegetation cover
(PVC) are of 11-year lengths, with boundary conditions from RIEMS2.0 simulation. In the CLC
experiment, vegetation cover in the original RIEMS2.0 is used, which is representative of CLC. In
the PVC experiment, all conditions are the same as in the CLC experiment. North of the Qinling
Mountains and the Huaihe River except the Tibet Plateau is our study region, the potential
vegetation data of Ramankutty and Foley were used [16] (R&F). These data have high-resolution (5')
with repeated sampling, generating the required horizontal resolution of 30 km. Two land cover
data types were used in the BATS classification method, which include 18 vegetation/land cover
types: 1) crop/mixed farming; 2) short grass; 3) evergreen needleleaf trees; 4) deciduous
needleleaf trees; 5) deciduous broadleaf trees; 6) evergreen broadleaf trees; 7) tall grass; 8) desert;
9) tundra; 10) irrigated crops; 11) semi-desert; 12) ice cap/glacier; 13) bog or marsh; 14) inland
water; 15) ocean; 16) evergreen shrubs; 17) deciduous shrubs; 18) mixed woodland. The model
was continuously integrated from 1 January 1990 to 31 December 2000 (11 years). The first year
was used to spin up the model, and only results for the subsequent 10 years were analyzed.
We analyzed the 10-year average differences between the two experiments (CLC- PVC) to
characterize LUCC in northern China. At the same time, to test statistical significance of mean
surface air temperature changes, we used a point-by-point, two-tailed Student’s t-test. Changes in
the results passing a 95% confidence level in the t-test are significant (P < 0.05).
Analyzing changes in different seasons and areas in northern China would help reveal
small-scale phenomena and characteristics of these areas. Summer includes June, July and August,
and winter includes December, January and February. According to characteristics of northern
China climate change caused by LUCC. Analyzing focused on three districts (Figure 3): (1)
Northeast (NE; east of 120°E) (2) Center of North (CN; 110°E–120°E, 35°N–52°N) (3) South (S;
105°E–122°E, 30°N–35°N) .
Fig. 3 Modeled domain and focused regions
3 Results
3.1 Human activities of LUCC leading to characteristics in northern China
Figures 1 and 2 showed LUCC and spatial characteristics in northern China caused by
human activities. These include changes from predominantly deciduous broadleaf forest to
cropland in the southeast, evergreen broadleaf to cropland in the part of the northeast, and
grassland conversion to cropland in most of the central NE. By lattice calculations of LUCC, the
statistics showed that 2495 of 5281 grid points were changed in northern China. Of these, 1820
*Corresponding author
E-mail address:[email protected](X.D. Yan)
grid points were changed from natural vegetation (including forest, short grass et al.) to cropland
types, and forest (including mixed forest, deciduous broadleaf forest et al.) was converted to
cropland at 1321 grids. These statistics demonstrated that human activities caused LUCC, which
were accompanied by increased cropland and reduced natural vegetation (forest-based). These
changes produce a significant temperature effect in the region.
3.2 Spatial characteristics of mean surface air temperature change in different seasons
Many studies have shown that the impact on mean surface air temperature of LUCC has
obvious seasonal characteristics [17,18]. Such impact was also found in northern China (Figure 4).
When potential natural vegetation cover types were converted to current vegetation cover types,
summer mean surface air temperature decreased in the central NE, eastern Gansu Province and the
Ningxia Hui Autonomous Region, but increased in Shanxi, Henan and Anhui provinces. Surface
air temperature changed significantly on a local scale in the central NE, central Henan Province
and eastern Gansu Province (P < 0.05). In winter, large areas exhibited non-significant decreases
of mean surface air temperature, similar to the simulation of Zheng [19] using the RegCM3 model.
Fig. 4 Mean surface air temperature change pattern in summer (a) and winter (b). Unit: °C. Red dashed lines indicate changes
significant at the 95% confidence level; dark dashed lines indicate changes significant at the 90% confidence level.
3.3 Mean surface air temperature change in different areas and its mechanism
Region-wide mean surface air temperature in northern China decreased by 0.02°C in summer,
and by 0.31°C in winter (Table 1). LUCC in different regions may have varying biogeophysical
effects. Thus, surface air temperature change differed by region, as did its mechanism. In summer,
this change was a decrease of 0.3°C in the NE, and a (non-significant) increase of 0.13°C in the S.
Decreasing the net absorption solar radiation flux (by −1.43 W/m2) led to cooling in the NE.
However, increasing surface albedo, which leaded to decreasing net absorption solar radiation flux
(−3.86 W/m2) (Figure 5a), produced an increase of 0.13°C in the S, where the evapotranspiration
effect is dominant, substantially reducing latent heat flux (−2.63 W/m2) (Figure 5b). The effect of
decreasing evapotranspiration on (increasing) surface air temperature was greater than that of
changing surface albedo on surface air temperature. Therefore, latent heat flux reduction was the
main cause of increasing mean surface air temperature in the S.
Table 1 Climate change in different seasons over various regions of northern China
Northeast
(NE)
North
South
All northern
China (CN)
(S)
China
JJA
DJF
JJA
DJF
JJA
DJF
JJA
DJF
−0.3
−0.44
0
−0.39
0.13
−0.59
−0.02
−0.31
−1.43
−0.96
−1.64
−0.74
−3.86
−0.84
−1.42
−0.49
Latent heat flux /(W/m2)
1.48
−0.06
−0.74
−0.40
−2.63
0.45
−0.29
−0.06
Sensible heat
−2.11
−0.36
−0.56
0.47
−0.15
0.30
−0.46
0.04
surface air
temperature/°C
Net solar absorbed
radiation /(W/m2)
*Corresponding author
E-mail address:[email protected](X.D. Yan)
flux/(W/m2)
In winter, mean surface air temperature showed a cooling of 0.44°C in the NE, cooling of
0.39°C in CN, and cooling of 0.59°C in the S. Mean surface air temperature in the S is lower than
the NE and CN (Table 1). In the S, net absorbed radiation flux decreased by 0.84 W/m2 (Figure
5c), and latent heat flux increased by 0.45 W/m2. It seems that during winter in the S, where forest
was converted to cropland, surface roughness was reduced and wind speed increased. This
increased turbulent heat exchange, and contemporaneously the latent heat flux and sensible heat
fluxes increased evaporative cooling. This caused the greater surface air temperature decrease in
the S relative to the other areas (Figure 5d).
Fig. 5 Net absorbed solar flux (a) and latent flux (b) change in summer; net absorbed solar flux (c) and latent flux (d) change in
winter. Unit: W/m2
3.4 Effect on mean surface air temperature at grids with forest conversion to cropland
at different latitudes
After land use/cover was converted from potential vegetation to current cover in northern
China, summer mean surface air temperature showed a warming of 0.14°C at grids with forest
conversion to cropland (Table 1). The winter change at these grids was a cooling of 0.64°C (Table
2). Previous studies of temperate forests change came to a similar conclusion. Snyder [17] showed
that snow in winter and spring makes for high seasonal variability of the water cycle and energy
fluxes after temperate deforestation. Bonan [20,21] suggested that a land use/cover shift from natural
vegetation to modern vegetation, including temperate forest to cropland, caused summer warming
in the western United States. We found with correlation analysis that net absorbed radiation has a
stronger influence on surface air temperature in winter, whereas latent heat flux has a stronger
influence in summer (Table 2). Conversion of boreal forest to cropland has a significant effect on
surface air temperature. The reason for this is that in summer, deforestation decreases latent heat
flux, which reduces evaporative cooling and increases surface air temperature. In winter,
deforestation with cropland expansion increases surface albedo in conjunction with the positive
feedback effect of snow. The effect of surface albedo change on surface air temperature is greater
than that of decreasing evapotranspiration, increasing cooling [22].
After land use/cover type was converted from forest to cropland, the surface biogeophysical
effects were very different, because of the latitude difference of the NE and S areas. This causes
regional water and energy variations, and different mean surface air temperature changes with
season. At the converted grids, whether in summer or winter (Table 2), latent heat flux effects on
surface air temperature at low latitudes (S area) are stronger. This is associated with the
relationship between low-latitude high temperature and saturated vapor pressure. Regional mean
surface air temperature increased, and so did evapotranspiration. Comparing the high-latitude (NE)
and low-latitude (S area) regions, we see that at lower latitudes, surface air temperature is less
influenced by net absorbed radiation and more strongly affected by latent heat flux.
Table 2 Mean surface air temperature change at grids converted from forest to cropland, and its spatial correlation with flux
change (values to right of slashes)
*Corresponding author
E-mail address:[email protected](X.D. Yan)
surface air temperature/°C
Net solar absorbed radiation /(W/m2)
Latent heat flux /(W/m2)
JJA
DJF
JJA
DJF
JJA
DJF
CN
0.14
−0.64
−3.28/0.36
−1.52/0.49
−2.81/−0.32
−0.25/0.21
NE
−0.07
−0.94
−3.94/0.53
−4.04/0.71
−1.91/-0.01
−0.92/0.62
S
0.17
−0.60
−3.62/0.38
−0.85/0.42
−3.38/-0.19
0.46/0.30
4 Discussions
(1) After land use/cover was converted from potential vegetation to the current cover, differences
between the two experiments (CLC- PVC) was found to have great impact on the spatial
distribution of surface air temperature change in summer. There was a decrease of mean surface
air temperature in the NE, which is the result of reducing net radiation flux and increasing latent
heat flux. There was an increase of mean surface air temperature in the S, mainly associated with
decreased latent heat flux. The decrease in roughness increased winter wind speed, leading to
increased turbulent heat exchange and resulting enhancement of evaporative cooling. This caused
mean surface air temperature in the S to be lower than other areas in winter. LUCC not only
impacted the near-surface climate, but also modified atmospheric circulation via energy exchange.
This in turn affected simulation of the East Asian monsoon. Therefore, monsoon circulation
changes caused by land use/cover require further study.
(2) In summer, a temperate forests removal simulation of mean surface air temperature in northern
China behaved more like a tropical forest removal simulation. In winter, temperate forests removal
simulation of mean surface air temperature behaves more like a boreal forest removal simulation.
LUCC at varying latitudes not only has different impact on mean surface air temperature, but also
on local surface air temperature under climate change. Stone et al. [23] pointed out that a reasonable
adjustment of land use can mitigate climate change, which may be a more effective way than a
reduction of greenhouse gas emissions. Therefore, land use/cover management in northern China
should focus on its temperature effects.
(3) We need more realistic land use/cover information and to more accurately describe physical
parameters. Regional climate models do not directly use land use/cover types to drive climate
change, but instead use roughness, surface albedo and other physical surface parameters that
represent each type. Land cover classification at small scales is very important, but it is not
directly used by models. Therefore, regional models need to better represent the relationship
between land use types and physical parameters [24,25].
(4) Chinese LUCC is complex and diverse, which has been a problem for accurately reflecting
land use/cover characteristics in research. In our study the use of remote sensing imagery, revised
survey data, and a more rational classification of these data has increased the accuracy of land use
/cover information, therefore, the new current land use/cover data were particularly important
when input into our model.
Acknowledgment
This project was financially supported by the National Key Basic Research and Development
Program (2010CB950903, 2009CB431100).
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*Corresponding author
E-mail address:[email protected](X.D. Yan)
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*Corresponding author
E-mail address:[email protected](X.D. Yan)