The climatic effects of LUCC have been a focus of current researches on global climate change. The objective of this study is to investigate climatic effects of grassland degradation in Northwest China. Based on the stimulation of the conversion from grassland to other land use types during the next 30 years, the potential effects of grassland degradation on regional climate in the overgrazing area of Northwest China from 2010 to 2040 have been explored with Weather Research and Forecasting model (WRF). The analysis results show that grassland will mainly convert into barren land, croplands, and urban land, which accounts for 42%, 48%, and 10% of the total converted grassland area, respectively. The simulation results indicate that the WRF model is appropriate for the simulation of the impact of grassland degradation on climate change. The grassland degradation during the next 30 years will result in the decrease of latent heat flux, which will further lead to the increase of temperature in summer, with an increment of 0.4–1.2°C, and the decrease of temperature in winter, with a decrement of 0.2°C. In addition, grassland degradation will cause the decrease of precipitation in both summer and winter, with a decrement of 4–20 mm.
The influence of human activities on the climate system has become the focus of the academic community at home and abroad in the context of global warming since the 20th century [
Grassland as one of the most widespread land use type covers about 40% of the total land area of China [
There have been many researches focusing on the impacts of the grassland degradation in overgrazing areas in Northwest China on climate change. Most of those researches detected the interaction between the grassland degradation and the climate change by the selection of regional climate model (RCMs) or global climate models (GCMs) and experiment designs [
Some studies with the WRF model have shown that grassland degradation in overgrazing areas of Northwest China has obvious effect on the regional climate [
The overgrazing area of Northwest China is located in 104°04′~114°02′E, 32°40′~41°20′N with a total land area of 811856 km2 covering five provinces which include Ningxia Province, the south east part of Gansu Province, Shaanxi Province, the west part of Shanxi Province, and the middle and south west part of Inner Mongolia Autonomous Region (Figure
Location of the study area and the distribution of land use type in the overgrazing areas of Northwest China.
This region stretches across the eastern monsoon region and northwest arid region and is close to the Qinghai-Tibet alpine region, approximately located in the transition zone of the three major natural zones of China. It is the continental semiarid climate in this region, with an annual average temperature of 5–10°C and the annual precipitation of 200–800 mm. There is very limited water resource, the spatiotemporal distribution of which is very imbalanced, and there are frequently meteorological disasters.
The grassland and cultivated land are the dominant land use types in this region, accounting for 36.19% and 29% of the total area, respectively. The irrational utilization of grassland resources is very common due to overgrazing and overreclamation under the influence of pursuit of economic benefit since the 1980s. It has led to the continual degradation of the grassland. The proportion of grassland accounting for the total area of Northwest China has decreased from about 36% in 1995 to 31% in 2008, and most of grassland degraded into barren land and croplands. The intensive grassland degradation has resulted in more and more acute contradiction between the human and nature, economic development and eco-environmental conservation in region. Therefore, the exploration of the degree and mechanism of grassland degradation’s influence on regional climate and environment is of great significance to the policy making of the regional sustainable land use and management.
In this study, the 1 km resolution land cover data of United States Geological Survey (USGS) classification in 2010 were extracted from the MODIS dataset. The land conversion data with 1 km resolution used to forecast the information of land use change (land conversion among different land cover types) during 2010–2040 were simulated based on Representative Concentration Pathways 6.0 (RCP6.0) using the Asia-Pacific Integrated Model (AIM) developed by the National Institute of Environmental Studies (NIES) in Japan. According to the requirement of the WRF model, it is necessary to convert the 1 km resolution land cover data of United States Geological Survey (USGS) classification in 2010 into the 30 km resolution data.
The meteorological data used in this study, including the near-surface temperature and precipitation, were all from 84 meteorological stations in Ningxia Province, Inner Mongolia Autonomous Region, Gansu Province, Shanxi Province, and Shaanxi Province. In order to analyze the simulation accuracy of the WRF model, the original data of annual average temperature, monthly average temperature and annual precipitation in year 2010 were interpolated into 1 km resolution grid data with the Kriging interpolation method and then compared with the simulation results.
The atmospheric forcing data such as air temperature, specific humidity, sea level pressure, eastward wind, northward wind, and geopotential height from 2010 to 2040 used in this study were from a state-of-the-art multimodel dataset produced by the fifth phase of the Coupled Model Intercomparison Project (CMIP5) [
The WRF model is a next-generation forecast model developed by the scientific research center, atmospheric administration (NOAA), research institutions and universities in the United States. Two motive power cores were included in the WRF model, that is, ARW (Advanced Research WRF) developed by NCAR and used in scientific research and nonhydrostatic Mesoscale Model (MMM) developed by NCEP and widely used in the business system. This study has mainly used the ARW model [
The parameterization scheme of physical processes in the WRF model in this study is as follows (Table
Parameterization scheme of physical processes in the WRF model.
Classification of schemes | Scheme option |
---|---|
Physics parameterization scheme | WSM3-class simple ice |
Cumulus parameterization scheme | Grell-Devenyi ensemble |
Boundary layer process scheme | YSU |
Radiation scheme | CAM 3 radiation |
Land surface process scheme | Noah land surface model |
In this study, two numerical simulation tests, including the control test and sensitivity test, were designed and performed with the same horizontal resolution and parameterization scheme in order to analyze the effects of grassland degradation on the regional climate more accurately, unlike other previous experiment studies in which the entire grassland was replaced by other land covers. The control test as a reference case used the land cover data of 2010, while the sensitivity test used the land cover data from 2010 to 2040, in which part of grassland converted into bare land, croplands, and urban land. The climate forcing data in both the control test and sensitivity test were all from 2010 to 2040. The center of the simulated area is located at 37°53′N, 109°1′E with two standard parallels of 39°N and 35°N, including 27 grid points in the east-west direction and 48 grid points in the north-south direction. The simulation period is 30 years from January 1st, 2010, to December 31th, 2040.
The grassland in the study mainly concentrates in the south and middle part of Inner Mongolia and Ningxia Province, the northeast of Gansu Province, and south part of Shaanxi Province, accounting for about 35% of the total area of overgrazing areas in Northwest China. This study stimulates the grassland change of overgrazing areas in Northwest China from 2010 to 2040. The stimulation result indicated that with the increasing population and unreasonable use of the grassland, the grassland degradation is still severe, in the future 30 years; the conclusion will be coherent with that of previous study [
This study also statistically analyzed the number of grid cells converting from grassland into other land types between 2010 and 2040. The result indicates that there will be 55 grids converting from grassland into other land types from 2010 to 2040 in the study area (Figure
Conversion from grassland to other land use types between 2010 and 2040 of the overgrazing areas in Northwest China.
It is necessary to investigate whether the WRF model can well simulate the climate change in the overgrazing areas of Northwest China since the performance of the WRF model in different regions may vary greatly. In this study, the simulation ability of WRF model was tested through comparing the stimulated temperature and precipitation with the observation data.
The result indicates that the WRF model can simulate the temporal change of temperature very well (Figures
Difference between the observed and simulated monthly temperature ((a), unit: °C) and precipitation ((b), unit: mm) of 2010 in the overgrazing areas of Northwest China.
Difference between the simulated and observed annual average temperature ((a), unit: °C) and annual precipitation ((b), unit: mm) in the overgrazing areas of Northwest China in 2010.
As can be seen from Figure
The land cover change can influence the energy balance of the earth-gas system through changing the underlying surface parameters such as the land surface albedo, roughness, and soil water content [
Average monthly change of latent heat flux (unit: W/m2) in the overgrazing area of Northwest China from 2010 to 2040.
The land use/cover change influences the regional surface temperature through altering the land roughness, and soil hydrological and thermal features, which lead to further change of the land surface energy balance, long wave radiation, fluxes of momentum, sensible heat and latent heat, and so forth [
Difference in the annual average temperature (unit: °C) in the winter (a) and summer (b) from 2010 to 2040 in the overgrazing areas in Northwest China between the sensitivity test and the control test.
The impacts of grassland degradation on the near-surface temperature are more complicated and widespread in the summer than that in the winter. The grassland degradation can decrease the surface albedo, which will result in the increase of the near-surface temperature in the overgrazing areas of Northwest China, with an increment of about 0.4°C–1.2°C (Figure
Although surface temperature of summer decrease in the south part of Inner Mongolia, the south part of Shaanxi Province, and south east of Gansu Province with the drop scale of about 0.4°C (Figure
The land cover change can influence the precipitation through modifying both the energy balance and water balance [
The simulation result indicates that the grassland degradation can cause the decrease of precipitation in the winter in most part of the overgrazing areas of Northwest China, with a decrement from about 0 mm to 12 mm (Figure
Difference in the annual precipitation (unit: mm) in the winter (a) and summer (b) from 2010 to 2040 in overgrazing areas of Northwest China between the sensitivity test and control test.
The abovementioned numerical simulation of temperature and precipitation in the next 30 years shows that the grassland degradation in the overgrazing areas of Northwest China will make the climate change show a dry-warm trend according to the results of both the control test and sensitivity test. The results are consistent with theoretical analysis results that the vegetation degradation will cause the increase of surface albedo, surface sensible heat, and the decrease of latent heat and thereby lead to the decrease of precipitation and increase of temperature [
Based on the analysis of grassland change in the future, this study analyzed the impacts of grassland degradation on the regional climate in the overgrazing areas of Northwest China through implementing the numerical simulation with the WRF model. The conclusions of this study are as follows.
The result indicates that the WRF model can well simulate the spatial pattern and change of temperature and precipitation, although the simulated value is a bit lower than the observed value. Besides, the grassland of Northwest China would mainly degrade into croplands, bare land, and urban land over the next 30 years. The most obvious grassland change will occur in the central part of Inner Mongolia Autonomous Region and northwest part of Shaanxi Province.
The simulation result indicates that the grassland degradation will make the climate change in the overgrazing areas of Northwest China show a dry-warm trend in the future 30 years. The grassland degradation will lead to the decrease of latent heat flux through influencing the phase change of water in the atmosphere and the surface-air heat exchange. The impacts of grassland degradation on the climate will vary in different seasons. In the summer, the grassland degradation will lead to the increase of surface temperature and decrease of precipitation. While in the winter, it will lead to the decrease of both the precipitation and temperature.
There are generally various impacts of land cover change on the climate change. However, this study has only analyzed the effects of grassland degradation on the temperature and precipitation; therefore, more influencing factors of the climate change should be taken into account in the future research. In addition, there are various factors that influence the regional climate, but in this paper, only the land cover change is used to analyze the impacts of grassland degradation on the regional climate, which leads to some uncertainties of the results. Therefore, more efforts should be made in the future research on the sensitivity test to reduce the uncertainties of the results.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This study is supported by the China National Natural Science Funds for Distinguished Young Scholar (Grant no. 71225005), National Key Program for Developing Basic Science in China (Grant no. 2012CB955700), and Key Projects in the National Science & Technology Pillar Program (Grant no. 2013BAC03B03).