- Email: [email protected]
cover change in eastern China
Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Contents lists available at ScienceDirect
Physics and Chemistry of the Earth journal homepage: www.elsevier.com/locate/pce
Modeling the climatic effects of the land use/cover change in eastern China Mingna Wang a,b,⇑, Zhe Xiong c, Xiaodong Yan d a
Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, Beijing, China College of Earth Science, University of Chinese Academy of Sciences, Beijing, China c Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China d State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China b
a r t i c l e
i n f o
Article history: Received 16 May 2015 Received in revised form 22 July 2015 Accepted 24 July 2015 Available online xxxx Keywords: Land use/land cover change WRF Regional climate change
a b s t r a c t This study aims to quantify the contribution of land use/cover change (LUCC) during the last three decades to climate change conditions in eastern China. The effects of farmland expansion in Northeast China, grassland degradation in Northwest China, and deforestation in South China were simulated using the Weather Research and Forecasting (WRF) model in addition to the latest actual land cover datasets. The simulated results show that when forestland is converted to farmland, the air temperature decreased owing to an increase in surface albedo in Northeast China. The climatic effect of grassland degradation on the Loess Plateau was insignificant because of the negligible difference in albedo between grassland and cropland. In South China, deforestation generally led to a decrease in temperature. Furthermore, the temperature decrease caused by the increase in albedo counteracted the warming effects of the evapotranspiration decrease, so the summer temperature change was not significant in South China. Excluding the effects of urbanization in the North China Plain, the LUCC effects across the entire region of East China presented an overall cooling trend. However, the variation in temperature scale and magnitude was less in summer than that in winter. This result is due mainly to the cooling caused by the increase in albedo offset partly by the increase in temperature caused by the decrease in evaporation in summer. Summer precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC, which was induced mainly by the decrease in surface roughness and cyclone circulations appearing northwest of Northeast China, in the middle of the Loess Plateau, and in Yunnan province at 700 hPa after forests were converted into farmland. All results will be instructive for understanding the influence of LUCC on regional climate and future land planning in practice. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Greenhouse gases and land use/cover change (LUCC) are the primary human impacts on global climate change (Feddema et al., 2005; Pielke, 2005; Mahmood et al., 2010). At least onethird of the Earth’s land surface has been directly impacted by human activities (Vitousek et al., 1997). LUCC activities can influence local, regional, and global climate through biogeochemical and biogeophysical processes. LUCC leads to changes of greenhouse gas emissions, which contribute to biogeochemical feedbacks. Biogeophysical feedbacks include the effects of surface albedo, roughness, and evapotranspiration changes (Bonan, 2008). Current international intergovernmental negotiations on ⇑ Corresponding author at: Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China. E-mail address: [email protected] (M. Wang).
climate change tend to attribute global and regional climate change completely to greenhouse gas emissions caused by human activities, thus ignoring the biogeophysical process caused by land use change (Liu et al., 2011). Determining the contribution rate of large-scale land use change on climate warming can improve and deepen the understanding of climate change attribution, which can in turn provide an important scientific basis for climate warming mitigation through the regulation of human activity. The amount of vegetation produced after the founding of the People’s Republic of China has been heavily influenced by human activities due to population increases. Compared with those in the western region of China, human activities in the eastern monsoon region appear to be more prevalent. The rapid and most obvious change in land use occurred in Northeast China, North China, the Loess Plateau, South China, the middle and lower reaches of the Yangtze River, and the eastern coastal region during the
http://dx.doi.org/10.1016/j.pce.2015.07.009 1474-7065/Ó 2015 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
2
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 1. Simulation domains and the dominant land cover for datasets LU80 (left) and LU00 (right).
Table 1 Configuration of the physical parameterization schemes in the Weather Research and Forecasting (WRF) model. Physical process
Parameterization scheme
Microphysics scheme Cumulus scheme Surface-layer Land surface process Planetary boundary layer process Long-wave radiation Short-wave radiation
Lin et al. scheme Grell–Devenyi ensemble scheme Monin–Obukhov scheme Noah land-surface scheme YSU scheme CAM scheme CAM scheme
Fig. 2. The four sub-regions in eastern China analyzed in this study.
Fig. 3. Top three cell numbers showing the greatest grid changes in three subregions from the 1980s to 2000. The abscissa represents the corresponding conversion type.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
3
Fig. 4. Spatial distributions of (a) observed temperature, (b) simulated temperature, (c) observed precipitation, (d) simulated precipitation, (e) difference in air temperature between simulations and observations, and (f) difference in precipitation between simulations and observations. Units in (a), (b), and (e) are °C; those in (c) and (d) are mm; and those in (f) are%.
1990s (Liu et al., 2003, 2005). Therefore, eastern parts of China incurred the effects of significant LUCC during recent years, which makes the climate of the eastern region more complex. Thus, eastern China was selected as the research area in the present study. Early modeling of the climate effect on LUCC was generally based on the underlying surface-type data from the U.S. Geological Survey (USGS) compared with potential vegetation cover data (Fu and Yan, 2003; Gao et al., 2003, 2007; Zhang
et al., 2010). Other studies have conducted simulations by changing the underlying surface type to the other extreme land type, such as by replacing the underlying tropical forest with bare land or cropland (Shukla et al., 1990; Bonan et al., 1992), to estimate the effect of deforestation on climate. Although these experimental results can reflect the impact of historical and extreme LUCC on the global or regional climate, they cannot determine the contribution rate of the actual large-scale LUCC during the past several decades.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
4
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
eastern China by using the mesoscale Weather Research and Forecasting (WRF) model coupled with the latest actual land cover datasets. Moreover, the representative large-scale LUCC areas in eastern China are chosen as model domains to simulate for a long time with high resolution. The results will help to broaden our understanding of the attribution of regional climate change for planning future human activities in a reasonable and orderly fashion.
2. Data and model 2.1. Model design
Fig. 5. Differences in annual mean albedo between Case E and CTRL.
Although previous studies have focused on the historical LUCC effects in China, no research has used actual land cover datasets in a regional climate model (RCM) to simulate the regional climate effects of actual LUCC in modern China during the late 20th century. As previously mentioned, this study aims to quantify the contribution of LUCC over last three decades to climate change in
The model employed in this study is the Advanced Research WRF (ARW; version 3.3; Skamarock et al., 2008), which is a non-hydrostatic and compressible model with a mass coordinate system. The WRF model is suitable for a broad spectrum of applications across multiple spatial scales ranging from meters to thousands of kilometers, and its capacity extends from largeeddy to global climate simulations (http://www.wrf-model.org). The model is centered at 37°N, 117.5°E and extends 95 grid points west to east and 139 grid points north to south. The simulation domain is shown in Fig. 1 at a horizontal resolution of 30 km. The vertical grid contains 28 full sigma levels from the surface to 50 hPa. Both the initial and the boundary conditions are from the National Centers for Environmental Predictions (NCEP) operational Global Final (FNL) Analyses on a 1.0° 1.0° grid. The simulations were integrated from December 1, 2000 to December 31, 2010; the first month was used as the spin-up time and was not included in the analysis. We analyzed the result of 10 years from 2001 to 2010. The parameterization schemes used in the simulation are listed in Table 1. The Community Atmospheric Model (CAM) long-wave and short-wave radiation schemes, updated sea surface temperature (SST) and deep soil temperature were used for long-term simulation.
Fig. 6. Effects of land use/cover change (LUCC) in Case NE on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 7. Same as Fig. 6, but for latent heat flux. Units: W m
Fig. 8. Same as Fig. 6, but for sensible heat flux. Units: W m
2.2. Land use data The default land use and land cover data used in the WRF model are based on 1992–1993 USGS data and cannot reflect the exact land surface conditions of the 2000s. Thus, we replaced this USGS data with new datasets developed by the Chinese Academy of Sciences for the late 1980s and 2000 having a spatial resolution of 1 km l km on the national scale (Liu et al., 2005, 2009). These land use and land cover datasets, derived from the interpretation of
5
2
.
2
.
high-resolution Landsat TM and CBERS-2 images, have been validated against extensive field surveys; thus, we are confident that our estimates show a significant improvement over previous estimates for land use and land cover change (Liu et al., 2005). To embed the high spatial resolution of the underlying surface data into the large-scale climate model with 30 km spatial resolution, the upscaling conversion method based on the rules of area equilibrium was employed. This method is more effective than the traditional upscaling method in maintaining the local spatial
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
6
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 9. Effects of land use/cover change (LUCC) in Case NW on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
Fig. 10. Effects of land use/cover change (LUCC) in Case S on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
distribution and plaque form. Therefore, we believe that the land use data used here can represent the actual LUCC in China. The two phases of land use/cover data used in this paper, the 1980s (LU80) and 2000s (LU00), are based on the USGS classification system. As shown in Fig. 1, the difference between LU80 and LU00 was only a slight difference in detail. The typical large-scale LUCC activities that occurred in the eastern monsoon area during the last 30 years were highly complex
and mainly include cultivation in Northeast China, reclamation and overgrazing in Northwest China, and deforestation in South China prior to 2000. However, between 2000 and 2010, the Chinese government implemented reforms and key projects to protect natural forests, return farmland to forest, and restore pasturage to natural grassland; thus, the vegetation is in the process of recovery under the guidance of the government. Liu et al. (2003, 2009, 2014) divided the research area of eastern China into four
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
7
were changed. The most significant change was from cropland/grassland mosaic to dryland cropland, followed by 25 grid cells from deciduous broadleaf forest to cropland/grassland mosaic and 24 grid cells from grassland to cropland/grassland mosaic. In NW, the top three changes were from grassland to cropland/grassland mosaic, from cropland/grassland mosaic to dryland cropland, and from deciduous broadleaf forest to cropland/grassland mosaic. Finally, the most significant changes in S were from evergreen broadleaf forest to cropland/grassland mosaic, followed by cropland/grassland mosaic converted to irrigated cropland and cropland/grassland mosaic converted to dryland cropland. From the 1980s to 2000, the main LUCCs were the conversions from forestland and grassland to farmland in Northeast China, from grassland to farmland in the Loess Plateau, and from forest to farmland in South China. Therefore, the simulation of LUCC in the present study includes the farmland expansion in Northeast China, grassland degradation in the Loess Plateau, and deforestation in South China.
2.3. Case design
Fig. 11. Effects of land use/cover change (LUCC) in Case S on summer mean wind field. Units: m/s.
partitions representing typical areas (Fig. 2). Urbanization is dominant in the Huang–Huai–Hai Plain (Partition 4). However, because its numerical simulation requires significantly higher resolution, the urbanization effect in Partition 4 is not discussed in this paper. The LUCC effects in Partition 1 (NE), Partition 2 (NW), and Partition 3 (S) are covered in this study. Grid cell changes occurring through land use type conversion at 30 km spatial resolution are listed in Fig. 3. In NE, 160 grid cells
In this study, we used two sets of land use data and conducted four sets of experiment to thoroughly evaluate the LUCC impacts in eastern China, excluding the urbanization effects in the Huang– Huai–Hai Plain. Land use dataset LU80 was used in the control experiment (CTRL). Dataset LU00 was introduced in the four sensitivity tests, although all of the conditions of CTRL were maintained. LU00 was employed in the entire simulated domain (Case E); only the underlying surfaces of NE, NW, and S were replaced by LU00, respectively (Case NE, Case NW and Case S). Therefore, the differences in the output between Case E and CTRL were considered as the LUCC effects of the entire region of eastern China. Likewise, the outputs of experiments NE, NW, and S minus that of CTRL were considered as the climate effects of the farmland expansion in Northeast China, grassland degradation in the Loess Plateau, and deforestation in South China, respectively.
Fig. 12. Effects of land use/cover change (LUCC) in Case E on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
8
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 13. Same as Fig. 12, but for latent heat flux. Units: W m
3. Result and discussion 3.1. Evaluation of the model performance The quality of the WRF model simulations was evaluated by comparing the output of the CTRL simulation against observations. The model output was interpolated to 0.5° 0.5° latitude–longitude grid points for comparison with the CN05 daily temperature dataset (Xu et al., 2009). The spatial distributions of simulated and observed annual mean temperature are shown in Fig. 4. The distribution pattern was generally well simulated, showing a gradual decreasing from south to north. The spatial correlation coefficient for temperature between observations and simulations was 0.98, and the root mean square error (RMSE) was 2.75. The model simulation results presented cold deviation with an error range of 1–3 °C; the largest errors occurred in southern part of Yunnan and the eastern part of Heilongjiang province. The simulations and observations (Yatagai et al., 2009) of precipitation are also shown in Fig. 4. Overall, the WRF model effectively simulated the decrease trend from southeast to northwest. The spatial correlation coefficient for precipitation between observations and simulations was 0.72, and the RMSE was 1.25. The simulations overestimated precipitation in part of northeast and northwest regions with relative deviation of 25–75%. However, precipitation was underestimated in the southeastern coastal areas with a relative deviation of more than 25%. The comparisons of annual mean temperature and precipitation with observations indicate that the model can reasonably simulate the spatial distribution of the temperature and precipitation characteristics. The simulation of temperature and precipitation was reasonable and reliable; thus so the WRF can be employed in the research of regional climate.
2
.
transformed to cropland in northeast Heilongjiang province led to an increase in albedo. The LUCC near the border of Inner Mongolia in the western parts of Jilin and Liaoning provinces changed from grassland to cropland; therefore, the albedo decreased (Fig. 5). Fig. 6 shows that a general decrease in temperature occurred after LUCC in NE. The annual mean temperature range was 0.7 °C to 0.5 °C, and the greatest decrease was 0.71 °C. The increase in albedo owing to the conversion from forest to cropland in northeast Heilongjiang province caused this temperature decrease. Similarly, the grid cell change from forest to grassland south of the Greater Hinggan Mountains also resulted in an albedo increase and subsequent temperature decrease. However, the latent heat flux of cropland and grassland in summer was larger than that of forest (Fig. 7), which would cause a temperature increase. Thus, the effects of both albedo and evapotranspiration resulted in insignificant changes in the temperature in northeast Heilongjiang province in summer, ranging from 0.36 °C to 0.2 °C. In winter, however, the evapotranspiration change in NE was weak
3.2. Effects of LUCC in NE As previously mentioned, the main LUCC in NE was from cropland/grassland mosaic to dryland cropland, although the albedo differences between them were not obvious. In addition, the forest
Fig. 14. Effects of land use/cover change (LUCC) in Case E on monthly mean temperature for three sub-regions: NE (48–50°N, 120–125°E), NW (35–40°N, 110– 115°E), and S (22.5–30°N, 110–117°E). Units: °C.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
9
between them were not obvious. Therefore, the seasonal and annual mean temperatures showed no significant changes (Fig. 9). Farmland reclaimed from extremely barren or sparse vegetation in the Loess Plateau decreased surface albedo, which caused an increase in temperature. Additionally, forest was converted to cropland on the eastern part of the Loess Plateau near the Taihang Mountains, resulting in an increase in albedo that reduced the temperature. In summer, the evapotranspiration of forest was stronger than that of cropland; thus, considering the effects of both albedo and evapotranspiration, the temperature showed no significant changes at the same locations. 3.4. Effects of LUCC in S
(Fig. 7). Therefore, the increase in surface albedo and decrease in net radiation (Fig. 8) resulted in a decrease in temperature, with cooling generally greater than 1.96 °C. Farmland reclaimed from barren or sparse vegetation at the border of northwest Jilin province and southwest Heilongjiang province caused an increase in surface albedo. However, the evapotranspiration was significantly greater than barren or sparsely vegetated land in summer (Fig. 7); therefore, the temperature decreased significantly in summer (Fig. 6). Conversely, the change in temperature in this area in winter was insignificant (Fig. 6) owing to minor evapotranspiration (Fig. 7).
The greatest LUCC in S was from the USGS type of evergreen broadleaf forest to cropland/grassland mosaic, which caused an albedo increase and evapotranspiration decrease. Therefore, as was expected, minor changes were detected in annual mean temperature in the range of 0.2 °C to 0.2 °C. In summer, the vegetation conversion from evergreen broadleaf forest to cropland resulted in a decrease in evapotranspiration that led to an increase in temperature. However, this effect was offset by a decrease in temperature resulting from an increase in albedo. As a result, the local summer temperature change in S was small. However, the temperature decreased owing to an increase in northwest wind in Northeast China (Figs. 10 and 11). In winter, the farmland albedo was significantly larger than that in summer; therefore, the temperature decreased with a maximum cooling of 0.42 °C (Fig. 10). The roughness was greatly reduced after the conversion from forest to cropland, resulting in an increase in wind speed in South China as well as that in parts of Northeast and North China in summer (Fig. 11). In particular, a cyclone circulation anomaly appeared in summer in the Bohai Rim region, which would have enhanced the atmospheric convergence in this area to strengthen the north wind in Northeast China. Therefore, northwest cold air advection resulted in a decrease in temperature in Northeast China (Fig. 10).
3.3. Effects of LUCC in NW
3.5. Effects of LUCC in E
The main LUCC in NW was from the USGS type of grassland to cropland/grassland mosaic, although the albedo differences
The temperature change in eastern China after modifying the underlying surface data in all three regions to LU00 is shown in Fig. 12.
Fig. 15. Effects of land use/cover change (LUCC) in Case E on summer mean precipitation. Units: mm.
Fig. 16. Effects of land use/cover change (LUCC) in Case E on summer wind field at the surface 10 m (left), 700 hPa (middle), and 500 hPa (right). Units: m/s.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
10
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Excluding that in the North China Plain, a general cooling present in eastern China after LUCC resulted mainly from the type conversion from forest to cropland, as previously discussed. The intensity and amplitude of the temperature change in summer was much less than that in winter, mainly because part of the cooling caused by the albedo increase was offset by the warming effect caused by the reduced evaporation in summer (Fig. 13). The largest cooling, 1.22 °C, occurred in summer; that in winter was 1.93 °C. The effects of eastern LUCC on the monthly mean temperature are presented in Fig. 14. The seasonal changes in temperature differences were obvious for all three sub-regions. The LUCC effects in NE and S were similar, and both presented cooling in winter and warming in summer. The temperature change in NW was opposite, showing a decrease in summer and an increase in winter. In NE (48–50°N, 120–125°E) and S (22.5–30°N, 110–117°E), the main type conversion from frost to cropland caused an albedo increase and evaporation decrease, resulting in temperature increases in summer and decreases in winter. In NW, the albedo of cropland was smaller than that of grass; therefore, the grassland conversion to cropland resulted in temperature increases in winter and decreases in summer owing to the greater evaporation in farmland. The LUCC impact on winter precipitation and wind field was minor. In summer, the main rainy season in China, precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC (Fig. 15). As shown in Fig. 16, the surface roughness decreased after forests were converted into farmland, which caused an increase in prevailing surface wind at 10 m in summer. The surface north wind increased in Northeast China and in the Loess Plateau area, and the south wind was enhanced in South China. At 700 hPa, cyclone-type circulations appeared in the northwest region of Northeast China, in the middle of the Loess Plateau, and in Yunnan province. All of these phenomena enhanced the local atmospheric convergence, resulting in precipitation increases in these three sub-regions. 4. Conclusion This study investigates the effects of actual land use and land cover change on the regional climate in eastern China by using the WRF model and the latest actual land cover data. Three representative large-scale LUCC areas are chosen as model domains for long-term simulation with high resolution. Two sets of land use data for the late 1980s and 2000 were used in four sets of experiments to thoroughly evaluate the climate effects of the farmland expansion in Northeast China, grassland degradation in the Loess Plateau region, deforestation in South China, and all LUCC in the entire region of eastern China, respectively. The main conclusions are presented in this section. The latest data from the Chinese Academy of Sciences showed that the main LUCC from the 1980s to 2000 was the conversion from forestland and grassland to farmland in Northeast China, from grassland to farmland in the Loess Plateau, and from forest to farmland in South China. Therefore, the simulations of actual LUCC phenomenon conducted in this study include the farmland expansion in Northeast China, the grassland degradation in the Loess Plateau, and the deforestation in South China. The WRF model is shown to reasonably simulate the spatial distribution and magnitude of the temperature and precipitation. Therefore, this model can be effectively employed in research of the regional climate effects of LUCC. The scale and intensity of temperature change for the main LUCC effects in the three sub-regions are shown to be more significant in winter than those in summer. The farmland expansion in Northeast China resulted in a general reduction in temperature, which was strongly affected by the albedo change. The grassland degradation in the Loess Plateau had a less significant effect on
temperature change. The deforestation in South China generally led to a decrease in temperature. However, the temperature change in summer was not obvious under the effects of both surface albedo increase and evaporation decrease in that season. We can see that LUCC grids are sparsely distributed in the simulated area, and LUCC effect is mainly limited to local on the temperature. Furthermore, different types of LUCC exert positive and negative effects on the temperature, and they cancel each other when calculating regional temperature change on average, so the magnitude of temperature change from LUCC is really smaller in comparison to the regional climate change. Excluding the urbanization effects in the Huang–Huai–Hai Plain, the LUCC climate effects in eastern China showed an overall cooling trend caused mainly by an increase in albedo from forest to farmland. The changes in temperature scale were less in summer than those in winter, because cooling caused by an increase in albedo was offset by an increase in temperature resulting from a decrease in evaporation in summer. The seasonal changes in monthly mean temperature differences caused by the LUCC were significant for all three sub-regions. The LUCC effects in NE and S were similar, both presenting cooling in winter and warming in summer. However, the temperature change in NW was opposite, owing mainly to the different conversion type of LUCC. Summer precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC. This phenomenon was induced mainly by a decrease in surface roughness after forests were converted into farmland in addition to the occurrence of cyclone-type circulations in the northwest region of Northeast China, in the middle of the Loess Plateau, and in Yunnan province at 700 hPa. This paper used the WRF model to simulate the main climate effects caused by vegetation albedo, evaporation, roughness, and other physical changes. However, analysis of additional biogeochemical factors such as the forcing of greenhouse gases and aerosols is needed in future work to thoroughly evaluate the regional climate effects of LUCC. And for WRF, in the future it is necessary to in-depth analysis how the background field simulation deviation influenced simulation results of LUCC, so we could better evaluate the uncertainty. Acknowledgments This research was sponsored by the National Basic Research Program of China (973 Program, No. 2014CB954300) and the National Natural Science Foundation of China (Nos. 41405072 and 91425304). References Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449. Bonan, G.B., Pollard, D., Thompson, S.L., 1992. Effects of boreal forest vegetation on global climate. Nature 359, 716–718. Feddema, J.J., Oleson, K.W., Bonan, G.B., Mearns, L.O., Buja, L.E., Meehl, G.A., Washington, W.M., 2005. The importance of land-cover change in simulating future climates. Science 310, 1674–1678. Fu, C., Yan, X., 2003. Preface. Global Planet. Change 37, 169. Gao, X.J., Luo, Y., Lin, W.T., Zhao, Z.C., Giorgi, F., 2003. Simulation of effects of land use change on climate in China by a regional climate model. Adv. Atmos. Sci. 20, 583–592. Gao, X.J., Zhang, D.F., Chen, Z.X., Pal, J.S., Giorgi, F., 2007. Land use effects on climate in china as simulated by a regional climate model. Sci. China (Series D): Earth Sci. 50, 620–628. Liu, J.Y., Liu, M.L., Zhuang, D.F., Zhang, Z.X., Deng, X.Z., 2003. Study on spatial pattern of land-use change in China during 1995–2000. Sci. China (Series D): Earth Sci. 32 (12), 373–384. Liu, J.Y., Tian, H.Q., Liu, M.L., Zhuang, D.F., Melillo, J.M., Zhang, Z.X., 2005. China’s changing landscape during the 1990s: large-scale land transformations estimated with satellite data. Geophys. Res. Lett. 32, L02405. Liu, J.Y., Zhang, Z.X., Xu, X.L., Kuang, W.H., Zhou, W.C., Zhang, S.W., Li, R.D., Yan, C.Z., Yu, D.S., Wu, S.X., Ning, J., 2009. Spatial patterns and driving forces of land use
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx change in china in the early 21st century. Acta Geograph. Sinica 64, 1411–1420 (in Chinese). Liu, J.Y., Shao, Q.Q., Yan, X.D., Fan, J.W., Deng, X.Z., Zhan, J.Y., Gao, X.J., Huang, L., Xu, X.L., Hu, Y.F., W, J.B., Kuang, W.H., 2011. An overview of the progress and research framework on the effects of landuse change upon global climate. Adv. Earth Sci. 26 (10), 1015–1022 (in Chinese). Liu, J.Y., Kuang, W.H., Zhang, Z.X., Xu, X.L., Qin, Y.W., Ning, J., Zhou, W.C., Zhang, S. W., Li, R.D., Yan, C.Z., Wu, S.X., Shi, X.Z., Jiang, N., Yu, D.S., Pan, X.Z., Chi, W.F., 2014. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. J. Geograph. Sci. 24, 195–210. Mahmood, R., Pielke, R.A., Hubbard, K.G., Niyogi, D., Bonan, G., Lawrence, P., McNider, R., McAlpine, C., Etter, A., Gameda, S., 2010. Impacts of land use/land cover change on climate and future research priorities. Bull. Am. Meteorol. Soc. 91, 37–46. Pielke, R.A., 2005. Land use and climate change. Science 310, 1625–1626.
11
Shukla, J., Nobre, C., Sellers, P., 1990. Amazon deforestation and climate change. Science 247, 1322–1325. Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X.Y., Wang, W., Powers, J.G., 2008. A Description of the Advanced Research WRF Version 3 NCAR Technical Note NCAR/TN-475+STR Boulder, Colorado, USA Vitousek, P.M., Mooney, H.A., Lubchenco, J., Melillo, J.M., 1997. Human domination of Earth’s ecosystems. Science 277, 494. Xu, Y., Gao, X.J., Shen, Y., 2009. A daily temperature dataset over China and its application in validating a RCM simulation. Adv. Atmos. Sci. 26, 763–772. Yatagai, A., Arakawa, O., Kamiguchi, K., Kawamoto, H., Nodzu, M., Hamada, A., 2009. A 44 Year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Sci. Online Lett. Atmos. 5, 137–140. Zhang, D.F., Gao, X.J., Shi, Y., Giorgi, F., Dong, W.J., 2010. Agricultural land use effects on climate over china as simulated by a regional climate model. Acta Meteorol. Sinica 24, 215–224.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
Contents lists available at ScienceDirect
Physics and Chemistry of the Earth journal homepage: www.elsevier.com/locate/pce
Modeling the climatic effects of the land use/cover change in eastern China Mingna Wang a,b,⇑, Zhe Xiong c, Xiaodong Yan d a
Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, Beijing, China College of Earth Science, University of Chinese Academy of Sciences, Beijing, China c Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China d State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China b
a r t i c l e
i n f o
Article history: Received 16 May 2015 Received in revised form 22 July 2015 Accepted 24 July 2015 Available online xxxx Keywords: Land use/land cover change WRF Regional climate change
a b s t r a c t This study aims to quantify the contribution of land use/cover change (LUCC) during the last three decades to climate change conditions in eastern China. The effects of farmland expansion in Northeast China, grassland degradation in Northwest China, and deforestation in South China were simulated using the Weather Research and Forecasting (WRF) model in addition to the latest actual land cover datasets. The simulated results show that when forestland is converted to farmland, the air temperature decreased owing to an increase in surface albedo in Northeast China. The climatic effect of grassland degradation on the Loess Plateau was insignificant because of the negligible difference in albedo between grassland and cropland. In South China, deforestation generally led to a decrease in temperature. Furthermore, the temperature decrease caused by the increase in albedo counteracted the warming effects of the evapotranspiration decrease, so the summer temperature change was not significant in South China. Excluding the effects of urbanization in the North China Plain, the LUCC effects across the entire region of East China presented an overall cooling trend. However, the variation in temperature scale and magnitude was less in summer than that in winter. This result is due mainly to the cooling caused by the increase in albedo offset partly by the increase in temperature caused by the decrease in evaporation in summer. Summer precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC, which was induced mainly by the decrease in surface roughness and cyclone circulations appearing northwest of Northeast China, in the middle of the Loess Plateau, and in Yunnan province at 700 hPa after forests were converted into farmland. All results will be instructive for understanding the influence of LUCC on regional climate and future land planning in practice. Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction Greenhouse gases and land use/cover change (LUCC) are the primary human impacts on global climate change (Feddema et al., 2005; Pielke, 2005; Mahmood et al., 2010). At least onethird of the Earth’s land surface has been directly impacted by human activities (Vitousek et al., 1997). LUCC activities can influence local, regional, and global climate through biogeochemical and biogeophysical processes. LUCC leads to changes of greenhouse gas emissions, which contribute to biogeochemical feedbacks. Biogeophysical feedbacks include the effects of surface albedo, roughness, and evapotranspiration changes (Bonan, 2008). Current international intergovernmental negotiations on ⇑ Corresponding author at: Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China. E-mail address: [email protected] (M. Wang).
climate change tend to attribute global and regional climate change completely to greenhouse gas emissions caused by human activities, thus ignoring the biogeophysical process caused by land use change (Liu et al., 2011). Determining the contribution rate of large-scale land use change on climate warming can improve and deepen the understanding of climate change attribution, which can in turn provide an important scientific basis for climate warming mitigation through the regulation of human activity. The amount of vegetation produced after the founding of the People’s Republic of China has been heavily influenced by human activities due to population increases. Compared with those in the western region of China, human activities in the eastern monsoon region appear to be more prevalent. The rapid and most obvious change in land use occurred in Northeast China, North China, the Loess Plateau, South China, the middle and lower reaches of the Yangtze River, and the eastern coastal region during the
http://dx.doi.org/10.1016/j.pce.2015.07.009 1474-7065/Ó 2015 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
2
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 1. Simulation domains and the dominant land cover for datasets LU80 (left) and LU00 (right).
Table 1 Configuration of the physical parameterization schemes in the Weather Research and Forecasting (WRF) model. Physical process
Parameterization scheme
Microphysics scheme Cumulus scheme Surface-layer Land surface process Planetary boundary layer process Long-wave radiation Short-wave radiation
Lin et al. scheme Grell–Devenyi ensemble scheme Monin–Obukhov scheme Noah land-surface scheme YSU scheme CAM scheme CAM scheme
Fig. 2. The four sub-regions in eastern China analyzed in this study.
Fig. 3. Top three cell numbers showing the greatest grid changes in three subregions from the 1980s to 2000. The abscissa represents the corresponding conversion type.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
3
Fig. 4. Spatial distributions of (a) observed temperature, (b) simulated temperature, (c) observed precipitation, (d) simulated precipitation, (e) difference in air temperature between simulations and observations, and (f) difference in precipitation between simulations and observations. Units in (a), (b), and (e) are °C; those in (c) and (d) are mm; and those in (f) are%.
1990s (Liu et al., 2003, 2005). Therefore, eastern parts of China incurred the effects of significant LUCC during recent years, which makes the climate of the eastern region more complex. Thus, eastern China was selected as the research area in the present study. Early modeling of the climate effect on LUCC was generally based on the underlying surface-type data from the U.S. Geological Survey (USGS) compared with potential vegetation cover data (Fu and Yan, 2003; Gao et al., 2003, 2007; Zhang
et al., 2010). Other studies have conducted simulations by changing the underlying surface type to the other extreme land type, such as by replacing the underlying tropical forest with bare land or cropland (Shukla et al., 1990; Bonan et al., 1992), to estimate the effect of deforestation on climate. Although these experimental results can reflect the impact of historical and extreme LUCC on the global or regional climate, they cannot determine the contribution rate of the actual large-scale LUCC during the past several decades.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
4
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
eastern China by using the mesoscale Weather Research and Forecasting (WRF) model coupled with the latest actual land cover datasets. Moreover, the representative large-scale LUCC areas in eastern China are chosen as model domains to simulate for a long time with high resolution. The results will help to broaden our understanding of the attribution of regional climate change for planning future human activities in a reasonable and orderly fashion.
2. Data and model 2.1. Model design
Fig. 5. Differences in annual mean albedo between Case E and CTRL.
Although previous studies have focused on the historical LUCC effects in China, no research has used actual land cover datasets in a regional climate model (RCM) to simulate the regional climate effects of actual LUCC in modern China during the late 20th century. As previously mentioned, this study aims to quantify the contribution of LUCC over last three decades to climate change in
The model employed in this study is the Advanced Research WRF (ARW; version 3.3; Skamarock et al., 2008), which is a non-hydrostatic and compressible model with a mass coordinate system. The WRF model is suitable for a broad spectrum of applications across multiple spatial scales ranging from meters to thousands of kilometers, and its capacity extends from largeeddy to global climate simulations (http://www.wrf-model.org). The model is centered at 37°N, 117.5°E and extends 95 grid points west to east and 139 grid points north to south. The simulation domain is shown in Fig. 1 at a horizontal resolution of 30 km. The vertical grid contains 28 full sigma levels from the surface to 50 hPa. Both the initial and the boundary conditions are from the National Centers for Environmental Predictions (NCEP) operational Global Final (FNL) Analyses on a 1.0° 1.0° grid. The simulations were integrated from December 1, 2000 to December 31, 2010; the first month was used as the spin-up time and was not included in the analysis. We analyzed the result of 10 years from 2001 to 2010. The parameterization schemes used in the simulation are listed in Table 1. The Community Atmospheric Model (CAM) long-wave and short-wave radiation schemes, updated sea surface temperature (SST) and deep soil temperature were used for long-term simulation.
Fig. 6. Effects of land use/cover change (LUCC) in Case NE on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 7. Same as Fig. 6, but for latent heat flux. Units: W m
Fig. 8. Same as Fig. 6, but for sensible heat flux. Units: W m
2.2. Land use data The default land use and land cover data used in the WRF model are based on 1992–1993 USGS data and cannot reflect the exact land surface conditions of the 2000s. Thus, we replaced this USGS data with new datasets developed by the Chinese Academy of Sciences for the late 1980s and 2000 having a spatial resolution of 1 km l km on the national scale (Liu et al., 2005, 2009). These land use and land cover datasets, derived from the interpretation of
5
2
.
2
.
high-resolution Landsat TM and CBERS-2 images, have been validated against extensive field surveys; thus, we are confident that our estimates show a significant improvement over previous estimates for land use and land cover change (Liu et al., 2005). To embed the high spatial resolution of the underlying surface data into the large-scale climate model with 30 km spatial resolution, the upscaling conversion method based on the rules of area equilibrium was employed. This method is more effective than the traditional upscaling method in maintaining the local spatial
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
6
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 9. Effects of land use/cover change (LUCC) in Case NW on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
Fig. 10. Effects of land use/cover change (LUCC) in Case S on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
distribution and plaque form. Therefore, we believe that the land use data used here can represent the actual LUCC in China. The two phases of land use/cover data used in this paper, the 1980s (LU80) and 2000s (LU00), are based on the USGS classification system. As shown in Fig. 1, the difference between LU80 and LU00 was only a slight difference in detail. The typical large-scale LUCC activities that occurred in the eastern monsoon area during the last 30 years were highly complex
and mainly include cultivation in Northeast China, reclamation and overgrazing in Northwest China, and deforestation in South China prior to 2000. However, between 2000 and 2010, the Chinese government implemented reforms and key projects to protect natural forests, return farmland to forest, and restore pasturage to natural grassland; thus, the vegetation is in the process of recovery under the guidance of the government. Liu et al. (2003, 2009, 2014) divided the research area of eastern China into four
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
7
were changed. The most significant change was from cropland/grassland mosaic to dryland cropland, followed by 25 grid cells from deciduous broadleaf forest to cropland/grassland mosaic and 24 grid cells from grassland to cropland/grassland mosaic. In NW, the top three changes were from grassland to cropland/grassland mosaic, from cropland/grassland mosaic to dryland cropland, and from deciduous broadleaf forest to cropland/grassland mosaic. Finally, the most significant changes in S were from evergreen broadleaf forest to cropland/grassland mosaic, followed by cropland/grassland mosaic converted to irrigated cropland and cropland/grassland mosaic converted to dryland cropland. From the 1980s to 2000, the main LUCCs were the conversions from forestland and grassland to farmland in Northeast China, from grassland to farmland in the Loess Plateau, and from forest to farmland in South China. Therefore, the simulation of LUCC in the present study includes the farmland expansion in Northeast China, grassland degradation in the Loess Plateau, and deforestation in South China.
2.3. Case design
Fig. 11. Effects of land use/cover change (LUCC) in Case S on summer mean wind field. Units: m/s.
partitions representing typical areas (Fig. 2). Urbanization is dominant in the Huang–Huai–Hai Plain (Partition 4). However, because its numerical simulation requires significantly higher resolution, the urbanization effect in Partition 4 is not discussed in this paper. The LUCC effects in Partition 1 (NE), Partition 2 (NW), and Partition 3 (S) are covered in this study. Grid cell changes occurring through land use type conversion at 30 km spatial resolution are listed in Fig. 3. In NE, 160 grid cells
In this study, we used two sets of land use data and conducted four sets of experiment to thoroughly evaluate the LUCC impacts in eastern China, excluding the urbanization effects in the Huang– Huai–Hai Plain. Land use dataset LU80 was used in the control experiment (CTRL). Dataset LU00 was introduced in the four sensitivity tests, although all of the conditions of CTRL were maintained. LU00 was employed in the entire simulated domain (Case E); only the underlying surfaces of NE, NW, and S were replaced by LU00, respectively (Case NE, Case NW and Case S). Therefore, the differences in the output between Case E and CTRL were considered as the LUCC effects of the entire region of eastern China. Likewise, the outputs of experiments NE, NW, and S minus that of CTRL were considered as the climate effects of the farmland expansion in Northeast China, grassland degradation in the Loess Plateau, and deforestation in South China, respectively.
Fig. 12. Effects of land use/cover change (LUCC) in Case E on mean temperature in summer (left), winter (middle), and annual mean (right). Dark dots indicate changes significant at the 95% confidence level. Units: °C.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
8
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Fig. 13. Same as Fig. 12, but for latent heat flux. Units: W m
3. Result and discussion 3.1. Evaluation of the model performance The quality of the WRF model simulations was evaluated by comparing the output of the CTRL simulation against observations. The model output was interpolated to 0.5° 0.5° latitude–longitude grid points for comparison with the CN05 daily temperature dataset (Xu et al., 2009). The spatial distributions of simulated and observed annual mean temperature are shown in Fig. 4. The distribution pattern was generally well simulated, showing a gradual decreasing from south to north. The spatial correlation coefficient for temperature between observations and simulations was 0.98, and the root mean square error (RMSE) was 2.75. The model simulation results presented cold deviation with an error range of 1–3 °C; the largest errors occurred in southern part of Yunnan and the eastern part of Heilongjiang province. The simulations and observations (Yatagai et al., 2009) of precipitation are also shown in Fig. 4. Overall, the WRF model effectively simulated the decrease trend from southeast to northwest. The spatial correlation coefficient for precipitation between observations and simulations was 0.72, and the RMSE was 1.25. The simulations overestimated precipitation in part of northeast and northwest regions with relative deviation of 25–75%. However, precipitation was underestimated in the southeastern coastal areas with a relative deviation of more than 25%. The comparisons of annual mean temperature and precipitation with observations indicate that the model can reasonably simulate the spatial distribution of the temperature and precipitation characteristics. The simulation of temperature and precipitation was reasonable and reliable; thus so the WRF can be employed in the research of regional climate.
2
.
transformed to cropland in northeast Heilongjiang province led to an increase in albedo. The LUCC near the border of Inner Mongolia in the western parts of Jilin and Liaoning provinces changed from grassland to cropland; therefore, the albedo decreased (Fig. 5). Fig. 6 shows that a general decrease in temperature occurred after LUCC in NE. The annual mean temperature range was 0.7 °C to 0.5 °C, and the greatest decrease was 0.71 °C. The increase in albedo owing to the conversion from forest to cropland in northeast Heilongjiang province caused this temperature decrease. Similarly, the grid cell change from forest to grassland south of the Greater Hinggan Mountains also resulted in an albedo increase and subsequent temperature decrease. However, the latent heat flux of cropland and grassland in summer was larger than that of forest (Fig. 7), which would cause a temperature increase. Thus, the effects of both albedo and evapotranspiration resulted in insignificant changes in the temperature in northeast Heilongjiang province in summer, ranging from 0.36 °C to 0.2 °C. In winter, however, the evapotranspiration change in NE was weak
3.2. Effects of LUCC in NE As previously mentioned, the main LUCC in NE was from cropland/grassland mosaic to dryland cropland, although the albedo differences between them were not obvious. In addition, the forest
Fig. 14. Effects of land use/cover change (LUCC) in Case E on monthly mean temperature for three sub-regions: NE (48–50°N, 120–125°E), NW (35–40°N, 110– 115°E), and S (22.5–30°N, 110–117°E). Units: °C.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
9
between them were not obvious. Therefore, the seasonal and annual mean temperatures showed no significant changes (Fig. 9). Farmland reclaimed from extremely barren or sparse vegetation in the Loess Plateau decreased surface albedo, which caused an increase in temperature. Additionally, forest was converted to cropland on the eastern part of the Loess Plateau near the Taihang Mountains, resulting in an increase in albedo that reduced the temperature. In summer, the evapotranspiration of forest was stronger than that of cropland; thus, considering the effects of both albedo and evapotranspiration, the temperature showed no significant changes at the same locations. 3.4. Effects of LUCC in S
(Fig. 7). Therefore, the increase in surface albedo and decrease in net radiation (Fig. 8) resulted in a decrease in temperature, with cooling generally greater than 1.96 °C. Farmland reclaimed from barren or sparse vegetation at the border of northwest Jilin province and southwest Heilongjiang province caused an increase in surface albedo. However, the evapotranspiration was significantly greater than barren or sparsely vegetated land in summer (Fig. 7); therefore, the temperature decreased significantly in summer (Fig. 6). Conversely, the change in temperature in this area in winter was insignificant (Fig. 6) owing to minor evapotranspiration (Fig. 7).
The greatest LUCC in S was from the USGS type of evergreen broadleaf forest to cropland/grassland mosaic, which caused an albedo increase and evapotranspiration decrease. Therefore, as was expected, minor changes were detected in annual mean temperature in the range of 0.2 °C to 0.2 °C. In summer, the vegetation conversion from evergreen broadleaf forest to cropland resulted in a decrease in evapotranspiration that led to an increase in temperature. However, this effect was offset by a decrease in temperature resulting from an increase in albedo. As a result, the local summer temperature change in S was small. However, the temperature decreased owing to an increase in northwest wind in Northeast China (Figs. 10 and 11). In winter, the farmland albedo was significantly larger than that in summer; therefore, the temperature decreased with a maximum cooling of 0.42 °C (Fig. 10). The roughness was greatly reduced after the conversion from forest to cropland, resulting in an increase in wind speed in South China as well as that in parts of Northeast and North China in summer (Fig. 11). In particular, a cyclone circulation anomaly appeared in summer in the Bohai Rim region, which would have enhanced the atmospheric convergence in this area to strengthen the north wind in Northeast China. Therefore, northwest cold air advection resulted in a decrease in temperature in Northeast China (Fig. 10).
3.3. Effects of LUCC in NW
3.5. Effects of LUCC in E
The main LUCC in NW was from the USGS type of grassland to cropland/grassland mosaic, although the albedo differences
The temperature change in eastern China after modifying the underlying surface data in all three regions to LU00 is shown in Fig. 12.
Fig. 15. Effects of land use/cover change (LUCC) in Case E on summer mean precipitation. Units: mm.
Fig. 16. Effects of land use/cover change (LUCC) in Case E on summer wind field at the surface 10 m (left), 700 hPa (middle), and 500 hPa (right). Units: m/s.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
10
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx
Excluding that in the North China Plain, a general cooling present in eastern China after LUCC resulted mainly from the type conversion from forest to cropland, as previously discussed. The intensity and amplitude of the temperature change in summer was much less than that in winter, mainly because part of the cooling caused by the albedo increase was offset by the warming effect caused by the reduced evaporation in summer (Fig. 13). The largest cooling, 1.22 °C, occurred in summer; that in winter was 1.93 °C. The effects of eastern LUCC on the monthly mean temperature are presented in Fig. 14. The seasonal changes in temperature differences were obvious for all three sub-regions. The LUCC effects in NE and S were similar, and both presented cooling in winter and warming in summer. The temperature change in NW was opposite, showing a decrease in summer and an increase in winter. In NE (48–50°N, 120–125°E) and S (22.5–30°N, 110–117°E), the main type conversion from frost to cropland caused an albedo increase and evaporation decrease, resulting in temperature increases in summer and decreases in winter. In NW, the albedo of cropland was smaller than that of grass; therefore, the grassland conversion to cropland resulted in temperature increases in winter and decreases in summer owing to the greater evaporation in farmland. The LUCC impact on winter precipitation and wind field was minor. In summer, the main rainy season in China, precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC (Fig. 15). As shown in Fig. 16, the surface roughness decreased after forests were converted into farmland, which caused an increase in prevailing surface wind at 10 m in summer. The surface north wind increased in Northeast China and in the Loess Plateau area, and the south wind was enhanced in South China. At 700 hPa, cyclone-type circulations appeared in the northwest region of Northeast China, in the middle of the Loess Plateau, and in Yunnan province. All of these phenomena enhanced the local atmospheric convergence, resulting in precipitation increases in these three sub-regions. 4. Conclusion This study investigates the effects of actual land use and land cover change on the regional climate in eastern China by using the WRF model and the latest actual land cover data. Three representative large-scale LUCC areas are chosen as model domains for long-term simulation with high resolution. Two sets of land use data for the late 1980s and 2000 were used in four sets of experiments to thoroughly evaluate the climate effects of the farmland expansion in Northeast China, grassland degradation in the Loess Plateau region, deforestation in South China, and all LUCC in the entire region of eastern China, respectively. The main conclusions are presented in this section. The latest data from the Chinese Academy of Sciences showed that the main LUCC from the 1980s to 2000 was the conversion from forestland and grassland to farmland in Northeast China, from grassland to farmland in the Loess Plateau, and from forest to farmland in South China. Therefore, the simulations of actual LUCC phenomenon conducted in this study include the farmland expansion in Northeast China, the grassland degradation in the Loess Plateau, and the deforestation in South China. The WRF model is shown to reasonably simulate the spatial distribution and magnitude of the temperature and precipitation. Therefore, this model can be effectively employed in research of the regional climate effects of LUCC. The scale and intensity of temperature change for the main LUCC effects in the three sub-regions are shown to be more significant in winter than those in summer. The farmland expansion in Northeast China resulted in a general reduction in temperature, which was strongly affected by the albedo change. The grassland degradation in the Loess Plateau had a less significant effect on
temperature change. The deforestation in South China generally led to a decrease in temperature. However, the temperature change in summer was not obvious under the effects of both surface albedo increase and evaporation decrease in that season. We can see that LUCC grids are sparsely distributed in the simulated area, and LUCC effect is mainly limited to local on the temperature. Furthermore, different types of LUCC exert positive and negative effects on the temperature, and they cancel each other when calculating regional temperature change on average, so the magnitude of temperature change from LUCC is really smaller in comparison to the regional climate change. Excluding the urbanization effects in the Huang–Huai–Hai Plain, the LUCC climate effects in eastern China showed an overall cooling trend caused mainly by an increase in albedo from forest to farmland. The changes in temperature scale were less in summer than those in winter, because cooling caused by an increase in albedo was offset by an increase in temperature resulting from a decrease in evaporation in summer. The seasonal changes in monthly mean temperature differences caused by the LUCC were significant for all three sub-regions. The LUCC effects in NE and S were similar, both presenting cooling in winter and warming in summer. However, the temperature change in NW was opposite, owing mainly to the different conversion type of LUCC. Summer precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC. This phenomenon was induced mainly by a decrease in surface roughness after forests were converted into farmland in addition to the occurrence of cyclone-type circulations in the northwest region of Northeast China, in the middle of the Loess Plateau, and in Yunnan province at 700 hPa. This paper used the WRF model to simulate the main climate effects caused by vegetation albedo, evaporation, roughness, and other physical changes. However, analysis of additional biogeochemical factors such as the forcing of greenhouse gases and aerosols is needed in future work to thoroughly evaluate the regional climate effects of LUCC. And for WRF, in the future it is necessary to in-depth analysis how the background field simulation deviation influenced simulation results of LUCC, so we could better evaluate the uncertainty. Acknowledgments This research was sponsored by the National Basic Research Program of China (973 Program, No. 2014CB954300) and the National Natural Science Foundation of China (Nos. 41405072 and 91425304). References Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449. Bonan, G.B., Pollard, D., Thompson, S.L., 1992. Effects of boreal forest vegetation on global climate. Nature 359, 716–718. Feddema, J.J., Oleson, K.W., Bonan, G.B., Mearns, L.O., Buja, L.E., Meehl, G.A., Washington, W.M., 2005. The importance of land-cover change in simulating future climates. Science 310, 1674–1678. Fu, C., Yan, X., 2003. Preface. Global Planet. Change 37, 169. Gao, X.J., Luo, Y., Lin, W.T., Zhao, Z.C., Giorgi, F., 2003. Simulation of effects of land use change on climate in China by a regional climate model. Adv. Atmos. Sci. 20, 583–592. Gao, X.J., Zhang, D.F., Chen, Z.X., Pal, J.S., Giorgi, F., 2007. Land use effects on climate in china as simulated by a regional climate model. Sci. China (Series D): Earth Sci. 50, 620–628. Liu, J.Y., Liu, M.L., Zhuang, D.F., Zhang, Z.X., Deng, X.Z., 2003. Study on spatial pattern of land-use change in China during 1995–2000. Sci. China (Series D): Earth Sci. 32 (12), 373–384. Liu, J.Y., Tian, H.Q., Liu, M.L., Zhuang, D.F., Melillo, J.M., Zhang, Z.X., 2005. China’s changing landscape during the 1990s: large-scale land transformations estimated with satellite data. Geophys. Res. Lett. 32, L02405. Liu, J.Y., Zhang, Z.X., Xu, X.L., Kuang, W.H., Zhou, W.C., Zhang, S.W., Li, R.D., Yan, C.Z., Yu, D.S., Wu, S.X., Ning, J., 2009. Spatial patterns and driving forces of land use
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009
M. Wang et al. / Physics and Chemistry of the Earth xxx (2015) xxx–xxx change in china in the early 21st century. Acta Geograph. Sinica 64, 1411–1420 (in Chinese). Liu, J.Y., Shao, Q.Q., Yan, X.D., Fan, J.W., Deng, X.Z., Zhan, J.Y., Gao, X.J., Huang, L., Xu, X.L., Hu, Y.F., W, J.B., Kuang, W.H., 2011. An overview of the progress and research framework on the effects of landuse change upon global climate. Adv. Earth Sci. 26 (10), 1015–1022 (in Chinese). Liu, J.Y., Kuang, W.H., Zhang, Z.X., Xu, X.L., Qin, Y.W., Ning, J., Zhou, W.C., Zhang, S. W., Li, R.D., Yan, C.Z., Wu, S.X., Shi, X.Z., Jiang, N., Yu, D.S., Pan, X.Z., Chi, W.F., 2014. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. J. Geograph. Sci. 24, 195–210. Mahmood, R., Pielke, R.A., Hubbard, K.G., Niyogi, D., Bonan, G., Lawrence, P., McNider, R., McAlpine, C., Etter, A., Gameda, S., 2010. Impacts of land use/land cover change on climate and future research priorities. Bull. Am. Meteorol. Soc. 91, 37–46. Pielke, R.A., 2005. Land use and climate change. Science 310, 1625–1626.
11
Shukla, J., Nobre, C., Sellers, P., 1990. Amazon deforestation and climate change. Science 247, 1322–1325. Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X.Y., Wang, W., Powers, J.G., 2008. A Description of the Advanced Research WRF Version 3 NCAR Technical Note NCAR/TN-475+STR Boulder, Colorado, USA Vitousek, P.M., Mooney, H.A., Lubchenco, J., Melillo, J.M., 1997. Human domination of Earth’s ecosystems. Science 277, 494. Xu, Y., Gao, X.J., Shen, Y., 2009. A daily temperature dataset over China and its application in validating a RCM simulation. Adv. Atmos. Sci. 26, 763–772. Yatagai, A., Arakawa, O., Kamiguchi, K., Kawamoto, H., Nodzu, M., Hamada, A., 2009. A 44 Year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Sci. Online Lett. Atmos. 5, 137–140. Zhang, D.F., Gao, X.J., Shi, Y., Giorgi, F., Dong, W.J., 2010. Agricultural land use effects on climate over china as simulated by a regional climate model. Acta Meteorol. Sinica 24, 215–224.
Please cite this article in press as: Wang, M., et al. Modeling the climatic effects of the land use/cover change in eastern China. J. Phys. Chem. Earth (2015), http://dx.doi.org/10.1016/j.pce.2015.07.009