research article numerical simulation of the effects of...

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2013 Article ID 270192 9 pageshttpdxdoiorg1011552013270192

Research ArticleNumerical Simulation of the Effects of Grassland Degradationon the Surface Climate in Overgrazing Area of Northwest China

Yanfei Li1 Zhaohua Li1 Zhihui Li234 Xiaoli Geng1 and Xiangzheng Deng34

1 Faculty of Resources and Environmental Science Hubei University Wuhan Hubei 430062 China2University of Chinese Academy of Sciences Beijing 100049 China3 Institute of Geographic Science and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China4Center for Chinese Agricultural Policy Chinese Academy of Sciences Beijing 100101 China

Correspondence should be addressed to Xiangzheng Deng dengxzccapgmailcom

Received 17 July 2013 Accepted 26 September 2013

Academic Editor Burak Guneralp

Copyright copy 2013 Yanfei Li et alThis is an open access article distributed under the Creative Commons Attribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The climatic effects of LUCC have been a focus of current researches on global climate change The objective of this study is toinvestigate climatic effects of grassland degradation in Northwest China Based on the stimulation of the conversion from grasslandto other land use types during the next 30 years the potential effects of grassland degradation on regional climate in the overgrazingarea of Northwest China from 2010 to 2040 have been explored withWeather Research and Forecasting model (WRF)The analysisresults show that grassland will mainly convert into barren land croplands and urban land which accounts for 42 48 and10 of the total converted grassland area respectively The simulation results indicate that the WRF model is appropriate for thesimulation of the impact of grassland degradation on climate changeThe grassland degradation during the next 30 years will resultin the decrease of latent heat flux which will further lead to the increase of temperature in summer with an increment of 04ndash12∘Cand the decrease of temperature in winter with a decrement of 02∘C In addition grassland degradation will cause the decrease ofprecipitation in both summer and winter with a decrement of 4ndash20mm

1 Introduction

The influence of human activities on the climate systemhas become the focus of the academic community at homeand abroad in the context of global warming since the 20thcentury [1] The fourth assessment report of Intergovern-mental Panel on Climate Change (IPCC AR4) indicated thatthe human activities are an important influencing factor ofclimate change accounting for 90 of global warming [23] Some previous researches have showed that the human-induced land useland cover change (LUCC) was one ofthe major factors which influence the regional climate [4]The LUCC influences the climate change mainly throughchanging the underlying surface properties such as thesurface reflectivity roughness soil moisture leaf area andvegetation coverage [5 6] The effects of LUCC on the bio-geophysical processes vary from region to region which areclosely relatedwith the land-atmosphere interaction regionalsurface climate environmental background and vegetation

and so forth [7 8] Therefore it is of great significance tostudy the effects of LUCC on regional climate for adaptingto climate change

Grassland as one of the most widespread land use typecovers about 40 of the total land area of China [9 10]The grasslands provide various ecosystem services such asthe provision of the forage milk and meat Besides thegrasslands also provide some important ecosystem servicesthat regulate the regional climate for example the mitigationof greenhouse gas (GHG) emissions through soil organiccarbon (C) and nitrogen (N) sequestration [11 12]Thereforethe grassland change would be the import factor influencingthe climate changeTheovergrazing areas inNorthwestChinaare the most significant hinterlands The grassland degra-dation and desertification in overgrazing area of NorthwestChina has greatly intensified due to the irrational exploitationof the natural resources rapid population growth and theexpansion of road network in recent years [13 14] The meanrate of grassland degradation has accelerated overall in the

2 Advances in Meteorology

Tibet

Xinjiang

Qinghai

Inner Mongolia

Gansu

Sichuan

Yunnan

Jilin

Heilongjiang

Hunan

Hubei

Guangxi Guangdong

Henan

Hebei

Shaanxi

Jiangxi

Shanxi

AnhuiShanghai

Guizhou Fujian

Liaoning

Shandong

Jiangsu

ZhejiangChongqing

Ningxia

Taiwan

Hainan

BeijingTianjin

0 21001050(km)

Cultivated landForestry areaGrassland

Water areaBuilt-up areaUnused aera

39∘N

33∘N

36∘N

39∘N

33∘N

36∘N

105∘E 108

∘E 111∘E

105∘E 108

∘E 111∘E

114∘E

10∘N

20∘N

30∘N

40∘N

50∘N

20∘N

30∘N

40∘N

50∘N

70∘E 80

∘E 90∘E 100

∘E 110∘E 120

∘E

90∘E 100

∘E 110∘E 120

∘E

130∘E 140

∘E

Figure 1 Location of the study area and the distribution of land use type in the overgrazing areas of Northwest China

past 50 years and only decelerated in recent years Moreoverthe grassland degradation has led to the decline of grasslandproductivity and increased the frequency of extreme climateevents such as droughts and fierce freeze-up which haveseriously influenced the sustainable development of animalhusbandry [14] Therefore it is of great importance to studythe influence of grassland degradation on the climate in theovergrazing area of Northwest China

There have been many researches focusing on theimpacts of the grassland degradation in overgrazing areasin Northwest China on climate change Most of thoseresearches detected the interaction between the grasslanddegradation and the climate change by the selection ofregional climate model (RCMs) or global climate models(GCMs) and experiment designs [15] Xue and Fu et alidentified that grassland degradation over the Mongolianand the Inner Mongolian grassland could bring significantinfluence on surface climate [16 17] Zhang et al foundthat the grassland degradation could lead to the decreaseof precipitation and the increase of surface temperaturein Northwest China [18] Liu et al found that the grass-land desertification can lead to grand temperature increasein the daytime and decrease at night and the sensitiveheat flux increase and the latent heat flux decrease in theSource Regions of Three Rivers [19] All of these previousresearches with GCMs and RCMs have contributed to thecomprehensive understanding of the impacts of grasslandchange on the climate change at the regional and globalscales However because of the coarse resolution thereare some bias and uncertainties in the simulation of theregional climate change with GCMs [20ndash24] The weatherResearch and Forecasting (WRF)model represents the recent

advances of RCMs and is specifically designed for highresolution applications and provides an ideal tool for assess-ing the value of high resolution regional climate modelingand some researchers have identified the WRF model tobe superior to other RCMs such as RegCM2 RegCM3RAMS RIEMS RegCM-NCC and IPCR-RegCM [1 2526]

Some studies with the WRF model have shown thatgrassland degradation in overgrazing areas of NorthwestChina has obvious effect on the regional climate [19 24]However those previous researches about the effects ofgrassland degradation on the climate change have generallyfocused on the effects of land change during the historicalperiod with the numerical simulation models while therewere few researches on the impacts of predicted future landuse change on the climate Therefore this study aims toestimate the potential impacts of grassland degradation onclimate change in overgrazing area of Northwest China from2010 to 2040 with the WRF model

2 Data and Methodology

21 Study Area The overgrazing area of Northwest Chinais located in 104∘041015840sim114∘021015840E 32∘401015840sim41∘201015840N with a totalland area of 811856 km2 covering five provinces which includeNingxia Province the south east part of Gansu ProvinceShaanxi Province the west part of Shanxi Province and themiddle and south west part of Inner Mongolia AutonomousRegion (Figure 1) It is one of the largest grazing areas ofChina which is the major production base of the animalhusbandry industry in China

Advances in Meteorology 3

This region stretches across the eastern monsoon regionand northwest arid region and is close to the Qinghai-Tibet alpine region approximately located in the transitionzone of the three major natural zones of China It is thecontinental semiarid climate in this region with an annualaverage temperature of 5ndash10∘C and the annual precipitationof 200ndash800mm There is very limited water resource thespatiotemporal distribution of which is very imbalanced andthere are frequently meteorological disasters

The grassland and cultivated land are the dominant landuse types in this region accounting for 3619 and 29of the total area respectively The irrational utilization ofgrassland resources is very common due to overgrazing andoverreclamation under the influence of pursuit of economicbenefit since the 1980s It has led to the continual degradationof the grassland The proportion of grassland accountingfor the total area of Northwest China has decreased fromabout 36 in 1995 to 31 in 2008 and most of grasslanddegraded into barren land and croplands The intensivegrassland degradation has resulted in more and more acutecontradiction between the human and nature economicdevelopment and eco-environmental conservation in regionTherefore the exploration of the degree and mechanism ofgrassland degradationrsquos influence on regional climate andenvironment is of great significance to the policy making ofthe regional sustainable land use and management

22 Data Resource In this study the 1 km resolution landcover data of United States Geological Survey (USGS) clas-sification in 2010 were extracted from the MODIS datasetThe land conversion data with 1 km resolution used toforecast the information of land use change (land conversionamong different land cover types) during 2010ndash2040 weresimulated based on Representative Concentration Pathways60 (RCP60) using the Asia-Pacific Integrated Model (AIM)developed by the National Institute of Environmental Stud-ies (NIES) in Japan According to the requirement of theWRF model it is necessary to convert the 1 km resolu-tion land cover data of United States Geological Survey(USGS) classification in 2010 into the 30 km resolutiondata

The meteorological data used in this study includingthe near-surface temperature and precipitation were allfrom 84 meteorological stations in Ningxia Province InnerMongolia Autonomous Region Gansu Province ShanxiProvince and Shaanxi Province In order to analyze thesimulation accuracy of the WRF model the original data ofannual average temperature monthly average temperatureand annual precipitation in year 2010 were interpolatedinto 1 km resolution grid data with the Kriging interpo-lation method and then compared with the simulationresults

The atmospheric forcing data such as air temperaturespecific humidity sea level pressure eastward wind north-ward wind and geopotential height from 2010 to 2040used in this study were from a state-of-the-art multimodeldataset produced by the fifth phase of the Coupled ModelIntercomparison Project (CMIP5) [27]

Table 1 Parameterization scheme of physical processes in theWRFmodel

Classification of schemes Scheme optionPhysics parameterization scheme WSM3-class simple iceCumulus parameterization scheme Grell-Devenyi ensembleBoundary layer process scheme YSURadiation scheme CAM 3 radiationLand surface process scheme Noah land surface model

23 Description of the WRF Model The WRF model isa next-generation forecast model developed by the scien-tific research center atmospheric administration (NOAA)research institutions and universities in the United StatesTwo motive power cores were included in the WRF modelthat is ARW(AdvancedResearchWRF) developed byNCARand used in scientific research and nonhydrostatic MesoscaleModel (MMM) developed by NCEP and widely used in thebusiness systemThis study has mainly used the ARWmodel[28]

The parameterization scheme of physical processes inthe WRF model in this study is as follows (Table 1) Itmainly includes theWSM3-Class simple ice physical schemeensemble cumulus convection schemes of Grell-Devenyiensemble YSU CAM3 radiation schemes and consolidatedNOAH land surface parameterization scheme [29 30]

24 Test Design In this study two numerical simulationtests including the control test and sensitivity test weredesigned and performed with the same horizontal resolu-tion and parameterization scheme in order to analyze theeffects of grassland degradation on the regional climate moreaccurately unlike other previous experiment studies in whichthe entire grassland was replaced by other land covers Thecontrol test as a reference case used the land cover data of2010 while the sensitivity test used the land cover data from2010 to 2040 in which part of grassland converted into bareland croplands and urban land The climate forcing datain both the control test and sensitivity test were all from2010 to 2040 The center of the simulated area is locatedat 37∘531015840N 109∘11015840E with two standard parallels of 39∘N and35∘N including 27 grid points in the east-west direction and48 grid points in the north-south direction The simulationperiod is 30 years from January 1st 2010 to December 31th2040

3 Result

31 Forecast of Future Grassland Degradation in OvergrazingAreas of Northwest China during 2010ndash2040 The grasslandin the study mainly concentrates in the south and middlepart of Inner Mongolia and Ningxia Province the northeastof Gansu Province and south part of Shaanxi Provinceaccounting for about 35 of the total area of overgrazingareas in Northwest ChinaThis study stimulates the grasslandchange of overgrazing areas in Northwest China from 2010to 2040 The stimulation result indicated that with the


Grassland converts to barren or sparsely vegetated landGrassland converts to dryland cropland and pastureGrassland converts to urban and built-up land

Urban and built-up landDryland cropland and pastureGrasslandOthers

Barren or sparsely vegetated land

40∘N

38∘N

36∘N

34∘N

40∘N

38∘N

36∘N

34∘N

114∘E112

∘E110∘E108

∘E106∘E

112∘E110

∘E108∘E106

∘E

Figure 2 Conversion from grassland to other land use typesbetween 2010 and 2040 of the overgrazing areas inNorthwest China

increasing population and unreasonable use of the grasslandthe grassland degradation is still severe in the future 30 yearsthe conclusion will be coherent with that of previous study[31] There will be mainly the conversion between grasslandand croplands bare land and urban land

This study also statistically analyzed the number of gridcells converting from grassland into other land types between2010 and 2040 The result indicates that there will be 55grids converting from grassland into other land types from2010 to 2040 in the study area (Figure 2) About 48 ofthe converted grassland will convert into croplands whichmainly distributed in the southeast part of Inner MongoliaAutonomous Region northwest part of Shaanxi Provinceand northeast part of Gansu Province The obvious con-version from grassland into barren land will mainly occurin south and central part of Inner Mongolia and ShanxiProvince south part of Ningxia Province and southeast partof Gansu Province accounting for 42 of the total numberof converted grids There will be 9 grids converting fromgrassland into urban land accounting for about 10 of thetotal number of converted grids In summary the grasslandin overgrazing areas in Northwest China will mainly convertinto barren land and croplands

32 Result of the Control Test It is necessary to investigatewhether the WRF model can well simulate the climate

change in the overgrazing areas of Northwest China since theperformance of theWRFmodel in different regionsmay varygreatly In this study the simulation ability ofWRFmodel wastested through comparing the stimulated temperature andprecipitation with the observation data

The result indicates that the WRF model can simulatethe temporal change of temperature very well (Figures 3(a)and 4(a)) According to the monthly temperature change inthe entire study area the simulated temperature is roughlyconsistent with the observed value in the spring and winterand the difference between them ranges from 0∘C to 05∘C(Figure 3(a)) However the temperature is obviously lowerthan the observed value in both the summer and autumnwith the difference between them ranging from 05∘C to25∘C As can be seen from Figure 4(a) the stimulated annualaverage temperature is lower than the observed value andthe difference between them ranges from 02∘C to 14∘Cindicating that there is only slight difference between thestimulated and observed annual average temperature

As can be seen from Figure 3(b) the stimulated precip-itation in the spring and autumn of 2010 is lower than theobserved value and the difference between them ranges from5mm to 40mm in most months except June Figure 4(b)reveals that the annual precipitation of 2010 in overgrazingareas in Northwest China especially the southeast part ofGansu Province and northwest of Shaanxi Province is lowerthan the observed value and the difference between themgenerally ranges from 5mm to 30mm In summary thedifference between the simulated and observed monthly andannual change of precipitation is not very obviousThereforethe WRF model can well simulate the monthly and annualchange of precipitation very well

33 Effects of GrasslandDegradation on LatentHeat Flux Theland cover change can influence the energy balance of theearth-gas system through changing the underlying surfaceparameters such as the land surface albedo roughness andsoil water content [26] Latent heat flux is the indispens-able element of energy exchange between land surface andatmosphere [32] The grassland degradation could decreasethe roughness which would lead to the decrease of latentheat exchange in the earth-gas system As can be seen fromFigure 5 the grassland degradation would result in theobvious decrease of the average monthly latent heat flux fromMarch to July and the maximum decrement reaches about10Wm2

34 Effects of GrasslandDegradation on the Land Surface Tem-perature The land usecover change influences the regionalsurface temperature through altering the land roughness andsoil hydrological and thermal features which lead to furtherchange of the land surface energy balance long wave radia-tion fluxes of momentum sensible heat and latent heat andso forth [33] While the impacts of grassland degradation onthe temperature in overgrazing areas of Northwest China canbe analyzed through calculating the difference in the annualaverage near-surface temperature (air temperatures at twometers above the ground) between the results of the control


0

05

1

15

2

25

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12

ObservedSimulatedObserved-simulated

Obs

erve

dsti

mul

ated

val

ue (∘

C)

Obs

erve

d-sti

mul

ated

val

ue (∘

C)

minus05minus10

minus5

(a)

05101520253035404550

0

200

400

600

800

1000

1200

1400

Obs

erve

dsti

mul

ated

val

ue (m

m)

Obs

erve

d-sti

mul

ated

val

ue (m

m)

1 2 3 4 5 6 7 8 9 10 11 12


(b)

Figure 3 Difference between the observed and simulated monthly temperature ((a) unit ∘C) and precipitation ((b) unit mm) of 2010 inthe overgrazing areas of Northwest China

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 14

gt minus 02minus14ndash10minus10ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 30

gt minus 5

minus30ndash25minus25ndash20


(b)

Figure 4 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

test and sensitivity test on the basis of the simulation in thecontrol test and sensitivity test the simulation result indicatesthat there will be different climate effects of the grasslanddegradation in different areas and seasons from 2010 to 2040in the overgrazing areas of Northwest China (Figure 6)Besides the results of the two tests showed that the grasslanddegradation would increase the land surface albedo whichcould lead to the decrease of near-surface temperature in the

winter in the middle part of Inner Mongolia AutonomousRegion southwest of Ningxia Province and northwest ofShanxi Province due to the conversion from grassland tobarren land and urban land with the decrement reaching02∘C (Figure 6(a)) Although the near-surface temperatureof thewinter increased in themiddle part of Shaanxi Provinceand north part of Shanxi Province due to the decrease ofland surface albedo caused by conversion from grassland to


0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12

Control experimentSensitive experiment

Late

nt h

eat fl

ux (W

m2)

Figure 5 Average monthly change of latent heat flux (unit Wm2) in the overgrazing area of Northwest China from 2010 to 2040

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 02

gt06minus02ndash002ndash04

04ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 04

gt120ndash0404ndash08

08ndash12

(b)

Figure 6 Difference in the annual average temperature (unit ∘C) in the winter (a) and summer (b) from 2010 to 2040 in the overgrazingareas in Northwest China between the sensitivity test and the control test

croplands the grassland degradation can mainly result inthe decrease of the near-surface temperature of winter in thestudy area

The impacts of grassland degradation on the near-surface temperature are more complicated and widespreadin the summer than that in the winter The grasslanddegradation can decrease the surface albedo which willresult in the increase of the near-surface temperature inthe overgrazing areas of Northwest China with an incre-ment of about 04∘Cndash12∘C (Figure 6(b)) The temperaturerise most obviously in the southwest of Inner Mongolia

and middle part of Shaanxi which are in the overgrazingareas of Northwest China with the increment of about12∘C

Although surface temperature of summer decrease in thesouth part of Inner Mongolia the south part of ShaanxiProvince and south east of Gansu Province with the dropscale of about 04∘C (Figure 6(b)) which would be causedby the conversion from grassland to croplands since there isobvious difference between the surface albedo of croplandsand grassland and the higher evapotranspiration of the crop-lands the grassland degradation would mainly lead to the


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20


minus12ndash8gt minus 4

(b)

Figure 7 Difference in the annual precipitation (unit mm) in the winter (a) and summer (b) from 2010 to 2040 in overgrazing areas ofNorthwest China between the sensitivity test and control test

increase of surface temperature of summer in the overgrazingareas of Northwest China

35The Effect of Grassland Degradation on Precipitation Theland cover change can influence the precipitation throughmodifying both the energy balance and water balance [2633]There are very complex impacts of grassland degradationon the precipitation Due to the complicated interactionsbetween land surface and atmosphere such as the inter-actions between land surface albedo soil moisture sandtemperature the grassland degradation will increase surfacealbedo reduce roughness and weaken the regulation func-tion of vegetation cover in the water cycle [26]

The simulation result indicates that the grassland degra-dation can cause the decrease of precipitation in the winterin most part of the overgrazing areas of Northwest Chinawith a decrement from about 0mm to 12mm (Figure 7(a))Particularly the annual precipitation in the northwest partof Shanxi Province and south part of Inner MongoliaAutonomous Region will decline most obviously due tothe serious grassland desertification with a decrement ofabout 12mm Besides in the summer the conversion fromgrassland to barren land can result in the obvious decreaseof precipitation in north and central part of Shanxi Provincenorth part of InnerMongolia andNingxia Province with thedecrement ranging from about 4mm to 20mm (Figure 7(b))

The abovementioned numerical simulation of tempera-ture and precipitation in the next 30 years shows that thegrassland degradation in the overgrazing areas of Northwest

China will make the climate change show a dry-warm trendaccording to the results of both the control test and sensitivitytestThe results are consistent with theoretical analysis resultsthat the vegetation degradation will cause the increase ofsurface albedo surface sensible heat and the decrease oflatent heat and thereby lead to the decrease of precipitationand increase of temperature [34]

4 Conclusion and Discussion

Based on the analysis of grassland change in the future thisstudy analyzed the impacts of grassland degradation on theregional climate in the overgrazing areas of Northwest Chinathrough implementing the numerical simulation with theWRF model The conclusions of this study are as follows

The result indicates that theWRFmodel canwell simulatethe spatial pattern and change of temperature and precipi-tation although the simulated value is a bit lower than theobserved value Besides the grassland of Northwest Chinawould mainly degrade into croplands bare land and urbanland over the next 30 years The most obvious grasslandchange will occur in the central part of Inner MongoliaAutonomous Region and northwest part of Shaanxi Province

The simulation result indicates that the grassland degra-dation will make the climate change in the overgrazing areasof Northwest China show a dry-warm trend in the future30 years The grassland degradation will lead to the decreaseof latent heat flux through influencing the phase change ofwater in the atmosphere and the surface-air heat exchange


The impacts of grassland degradation on the climate willvary in different seasons In the summer the grasslanddegradation will lead to the increase of surface temperatureand decrease of precipitation While in the winter it will leadto the decrease of both the precipitation and temperature

There are generally various impacts of land cover changeon the climate change However this study has only analyzedthe effects of grassland degradation on the temperatureand precipitation therefore more influencing factors ofthe climate change should be taken into account in thefuture research In addition there are various factors thatinfluence the regional climate but in this paper only theland cover change is used to analyze the impacts of grasslanddegradation on the regional climate which leads to someuncertainties of the results Therefore more efforts should bemade in the future research on the sensitivity test to reducethe uncertainties of the results

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by theChinaNationalNatural ScienceFunds forDistinguishedYoung Scholar (Grant no 71225005)National Key Program for Developing Basic Science inChina (Grant no 2012CB955700) and Key Projects in theNational Science amp Technology Pillar Program (Grant no2013BAC03B03)

References

[1] X Deng C Zhao and H Yan ldquoSystematic modeling of impactsof land use and land cover changes on regional climate areviewrdquo Advances in Meteorology vol 2013 Article ID 31767810 pages 2013

[2] M Jin and S Liang ldquoAn improved land surface emissivityparameter for land surface models using global remote sensingobservationsrdquo Journal of Climate vol 19 no 12 pp 2867ndash28812006

[3] S Solomon D Qin MManning et al Contribution ofWorkingGroup I to the FourthAssessment Report of the IntergovernmentalPanel on Climate Change IPCC Cambridge UK 2007

[4] M Cai and E Kalnay ldquoImpact of land-use change on climatecommentaryrdquo Nature vol 427 no 6971 p 214 2004

[5] X Gao Y Luo W Lin Z Zhao and F Giorgi ldquoSimulation ofeffects of land use change on climate in China by a regionalclimate modelrdquo Advances in Atmospheric Sciences vol 20 no4 pp 583ndash592 2003

[6] J J Feddema K W Oleson G B Bonan et al ldquoAtmosphericscience the importance of land-cover change in simulatingfuture climatesrdquo Science vol 310 no 5754 pp 1674ndash1678 2005

[7] P SellersW Shut and J Dorman ldquoCalibration of the simplifiedsimple biosphere model (SSiB) for Amazonian pasture andforest sites using LBA datardquo Acta Amazonian vol 35 no 2 pp729ndash759 1989

[8] J Jin and L Wen ldquoEvaluation of snowmelt simulation in theweather research and forecastingmodelrdquo Journal of GeophysicalResearch vol 117 2012

[9] T Akiyama and K Kawamura ldquoGrassland degradation inChinaGrassland degradation inChinamethods ofmonitoringmanagement and restorationrdquo Japanese Society of GrasslandScience vol 53 pp 1ndash17 2007

[10] J Jin S Lu S Li and N L Miller ldquoImpact of land use changeon the local climate over the Tibetan Plateaurdquo Advances inMeteorology vol 2010 Article ID 837480 6 pages 2010

[11] J Fan H Zhong W Harris et al ldquoCarbon storage in thegrasslands of China based on field measurements of above- andbelow-ground biomassrdquo Climatic Change vol 86 no 3-4 pp375ndash396 2008

[12] F Barthold M Wiesmeier L Breuer H Frede J Wua and FBlank ldquoLand use and climate control the spatial distribution ofsoil types in the grasslands of Inner Mongoliardquo Journal of AridEnvironments vol 88 pp 194ndash205 2012

[13] G Xu M Kang and Y Jiang ldquoAdaptation to the policy-oriented livelihood change in Xilingol grassland NorthernChinardquo Procedia Environmental Sciences vol 13 pp 1668ndash16832012

[14] X Deng J Huang Q Huang S Rozelle and J Gibson ldquoDoroads lead to grassland degradation or restoration A casestudy in InnerMongolia ChinardquoEnvironment andDevelopmentEconomics vol 16 no 6 pp 751ndash773 2011

[15] J Charney W J Quirk S-H Chow and J Kornfield ldquoAcomparative study of the effects of albedo change on drought insemi-arid regionrdquo Journal of the Atmospheric Sciences vol 34no 9 pp 1366ndash1385 1977

[16] Y Xue ldquoThe impact of desertification in the Mongolian and theInner Mongolian grassland on the regional climaterdquo Journal ofClimate vol 9 no 9 pp 2173ndash2189 1996

[17] C Fu H Wei and W Zheng ldquoSensitivity test of surfacecoverage types of mainland China in mesoscale modelrdquo inGlobal Change and the Environment in Our Country in theFuture Meteorological Press Beijing China 1996 (Chinese)

[18] J Zhang W Dong and C Fu ldquoImpact of land surface degra-dation in northern China and southern Mongolia on regionalclimaterdquo Chinese Science Bulletin vol 50 no 1 pp 75ndash81 2005

[19] Y Liu and S Lv ldquoNumerical simulation of the impact ofthe grassland desertification on local climate in the SourceRegion of Three Riversrdquo Journal of Arid Land Resources andEnvironment vol 6 no 21 pp 131ndash135 2007 (Chinese)

[20] Y Xue and J Shukla ldquoThe influence of land surface propertieson Sahel climate Part I desertificationrdquo Journal of Climate vol6 no 12 pp 2232ndash2245 1993

[21] B Fu L Wei and W Zhen Sensitivity Test of MesoscaleModel to Surface Cover Type of the Chinese Mainland ChinaMeteorological Press Beijing China 1996

[22] H Mao X Yan Z Xiong and H Tian ldquoModeled impact ofirrigation on regional climate in Indiardquo Acta Ecologica Sinicavol 31 no 4 pp 1038ndash1045 2011 (Chinese)

[23] J Jin M L Miller and N Schlegel ldquoSensitivity study offour land surface schemes in the WRF modelrdquo Advances inMeteorology vol 2010 Article ID 167436 11 pages 2010

[24] M Wang X Zhang and X Yan ldquoModeling the climatic effectsof urbanization in the Beijing-Tianjin-Hebei metropolitanareardquoTheoretical and Applied Climatology p 9 2012 (Chinese)

[25] P Caldwell H-N S Chin D C Bader andG Bala ldquoEvaluationof a WRF dynamical downscaling simulation over CaliforniardquoClimatic Change vol 95 no 3-4 pp 499ndash521 2009


[26] C V Srinivas D Hariprasad D V Bhaskar Rao Y AnjaneyuluR Baskaran and B Venkatraman ldquoSimulation of the Indiansummer monsoon regional climate using advanced researchWRF modelrdquo International Journal of Climatology vol 33 no5 pp 1195ndash1210 2013

[27] K Taylor R Stouffer andGMeehl ldquoAn overview ofCMIP5 andthe experiment designrdquo Bulletin of the American MeteorologicalSociety vol 93 no 4 pp 485ndash498 2012

[28] M Mohan and S Bhati ldquoAnalysis of WRF model performanceover subtropical region of Delhi Indiardquo Advances in Meteorol-ogy vol 2011 Article ID 621235 13 pages 2011

[29] S-Y Hong and H-L Pan ldquoNonlocal boundary layer verticaldiffusion in a medium-range forecast modelrdquoMonthly WeatherReview vol 124 no 10 pp 2322ndash2339 1996

[30] G A Grell andD Devenyi ldquoA generalized approach to parame-terizing convection combining ensemble and data assimilationtechniquesrdquoGeophysical Research Letters vol 29 no 14 pp 38ndash1 2002

[31] F Wu X Deng F Yin and Y Yuan ldquoProjected changes ofgrassland productivity along the representative concentrationpathways during 2010ndash2050 inChinardquoAdvances inMeteorologyvol 2013 Article ID 812723 9 pages 2013

[32] J L Schedlbauer S F Oberbauer G Starr and K L JimenezldquoControls on sensible heat and latent energy fluxes from a short-hydroperiod Florida Everglades marshrdquo Journal of Hydrologyvol 411 no 3-4 pp 331ndash341 2011

[33] L Lian and J Shu ldquoSimulation of effects of grassland degrada-tion on regional climate over sanjiangyuan region in Qinghai-Tibet plateaurdquo Acta Meteorologica Sinica vol 23 no 3 pp 350ndash362 2009

[34] M V K Sivakumar ldquoInteractions between climate and deserti-ficationrdquo Agricultural and Forest Meteorology vol 142 no 2ndash4pp 143ndash155 2007

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


Tibet

Xinjiang

Qinghai

Inner Mongolia

Gansu

Sichuan

Yunnan

Jilin

Heilongjiang

Hunan

Hubei

Guangxi Guangdong

Henan

Hebei

Shaanxi

Jiangxi

Shanxi

AnhuiShanghai

Guizhou Fujian

Liaoning

Shandong

Jiangsu

ZhejiangChongqing

Ningxia

Taiwan

Hainan

BeijingTianjin

0 21001050(km)

Cultivated landForestry areaGrassland

Water areaBuilt-up areaUnused aera

39∘N

33∘N

36∘N

39∘N

33∘N

36∘N

105∘E 108

∘E 111∘E

105∘E 108

∘E 111∘E

114∘E

10∘N

20∘N

30∘N

40∘N

50∘N

20∘N

30∘N

40∘N

50∘N

70∘E 80

∘E 90∘E 100

∘E 110∘E 120

∘E

90∘E 100

∘E 110∘E 120

∘E

130∘E 140

∘E

Figure 1 Location of the study area and the distribution of land use type in the overgrazing areas of Northwest China

past 50 years and only decelerated in recent years Moreoverthe grassland degradation has led to the decline of grasslandproductivity and increased the frequency of extreme climateevents such as droughts and fierce freeze-up which haveseriously influenced the sustainable development of animalhusbandry [14] Therefore it is of great importance to studythe influence of grassland degradation on the climate in theovergrazing area of Northwest China

There have been many researches focusing on theimpacts of the grassland degradation in overgrazing areasin Northwest China on climate change Most of thoseresearches detected the interaction between the grasslanddegradation and the climate change by the selection ofregional climate model (RCMs) or global climate models(GCMs) and experiment designs [15] Xue and Fu et alidentified that grassland degradation over the Mongolianand the Inner Mongolian grassland could bring significantinfluence on surface climate [16 17] Zhang et al foundthat the grassland degradation could lead to the decreaseof precipitation and the increase of surface temperaturein Northwest China [18] Liu et al found that the grass-land desertification can lead to grand temperature increasein the daytime and decrease at night and the sensitiveheat flux increase and the latent heat flux decrease in theSource Regions of Three Rivers [19] All of these previousresearches with GCMs and RCMs have contributed to thecomprehensive understanding of the impacts of grasslandchange on the climate change at the regional and globalscales However because of the coarse resolution thereare some bias and uncertainties in the simulation of theregional climate change with GCMs [20ndash24] The weatherResearch and Forecasting (WRF)model represents the recent

advances of RCMs and is specifically designed for highresolution applications and provides an ideal tool for assess-ing the value of high resolution regional climate modelingand some researchers have identified the WRF model tobe superior to other RCMs such as RegCM2 RegCM3RAMS RIEMS RegCM-NCC and IPCR-RegCM [1 2526]

Some studies with the WRF model have shown thatgrassland degradation in overgrazing areas of NorthwestChina has obvious effect on the regional climate [19 24]However those previous researches about the effects ofgrassland degradation on the climate change have generallyfocused on the effects of land change during the historicalperiod with the numerical simulation models while therewere few researches on the impacts of predicted future landuse change on the climate Therefore this study aims toestimate the potential impacts of grassland degradation onclimate change in overgrazing area of Northwest China from2010 to 2040 with the WRF model

2 Data and Methodology

21 Study Area The overgrazing area of Northwest Chinais located in 104∘041015840sim114∘021015840E 32∘401015840sim41∘201015840N with a totalland area of 811856 km2 covering five provinces which includeNingxia Province the south east part of Gansu ProvinceShaanxi Province the west part of Shanxi Province and themiddle and south west part of Inner Mongolia AutonomousRegion (Figure 1) It is one of the largest grazing areas ofChina which is the major production base of the animalhusbandry industry in China












3 Result






40∘N

38∘N

36∘N

34∘N

40∘N

38∘N

36∘N

34∘N

114∘E112

∘E110∘E108

∘E106∘E

112∘E110

∘E108∘E106

∘E











0

05

1

15

2

25

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12


Obs

erve

dsti

mul

ated

val

ue (∘

C)

Obs

erve

d-sti

mul

ated

val

ue (∘

C)

minus05minus10

minus5

(a)

05101520253035404550

0

200

400

600

800

1000

1200

1400

Obs

erve

dsti

mul

ated

val

ue (m

m)

Obs

erve

d-sti

mul

ated

val

ue (m

m)

1 2 3 4 5 6 7 8 9 10 11 12


(b)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 14


(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 30

gt minus 5



(b)





0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12


Late

nt h

eat fl

ux (W

m2)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 02


04ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 04


08ndash12

(b)







Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20



(b)
















Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in












3 Result






40∘N

38∘N

36∘N

34∘N

40∘N

38∘N

36∘N

34∘N

114∘E112

∘E110∘E108

∘E106∘E

112∘E110

∘E108∘E106

∘E











0

05

1

15

2

25

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12


Obs

erve

dsti

mul

ated

val

ue (∘

C)

Obs

erve

d-sti

mul

ated

val

ue (∘

C)

minus05minus10

minus5

(a)

05101520253035404550

0

200

400

600

800

1000

1200

1400

Obs

erve

dsti

mul

ated

val

ue (m

m)

Obs

erve

d-sti

mul

ated

val

ue (m

m)

1 2 3 4 5 6 7 8 9 10 11 12


(b)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 14


(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 30

gt minus 5



(b)





0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12


Late

nt h

eat fl

ux (W

m2)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 02


04ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 04


08ndash12

(b)







Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20



(b)
















Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in





40∘N

38∘N

36∘N

34∘N

40∘N

38∘N

36∘N

34∘N

114∘E112

∘E110∘E108

∘E106∘E

112∘E110

∘E108∘E106

∘E











0

05

1

15

2

25

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12


Obs

erve

dsti

mul

ated

val

ue (∘

C)

Obs

erve

d-sti

mul

ated

val

ue (∘

C)

minus05minus10

minus5

(a)

05101520253035404550

0

200

400

600

800

1000

1200

1400

Obs

erve

dsti

mul

ated

val

ue (m

m)

Obs

erve

d-sti

mul

ated

val

ue (m

m)

1 2 3 4 5 6 7 8 9 10 11 12


(b)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 14


(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 30

gt minus 5



(b)





0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12


Late

nt h

eat fl

ux (W

m2)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 02


04ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 04


08ndash12

(b)







Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20



(b)
















Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0

05

1

15

2

25

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12


Obs

erve

dsti

mul

ated

val

ue (∘

C)

Obs

erve

d-sti

mul

ated

val

ue (∘

C)

minus05minus10

minus5

(a)

05101520253035404550

0

200

400

600

800

1000

1200

1400

Obs

erve

dsti

mul

ated

val

ue (m

m)

Obs

erve

d-sti

mul

ated

val

ue (m

m)

1 2 3 4 5 6 7 8 9 10 11 12


(b)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 14


(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 30

gt minus 5



(b)





0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12


Late

nt h

eat fl

ux (W

m2)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 02


04ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 04


08ndash12

(b)







Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20



(b)
















Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0102030405060708090

100

1 2 3 4 5 6 7 8 9 10 11 12


Late

nt h

eat fl

ux (W

m2)


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 02


04ndash06

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 04


08ndash12

(b)







Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20



(b)
















Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 12

gt80ndash44ndash8

(a)

Shaanxi

Shanxi

Inner Mongolia

Gansu

Henan

Ningxia

HubeiSichuan

106∘E 108

∘E 110∘E 112

∘E

106∘E 108

∘E 110∘E 112

∘E

34∘N

36∘N

38∘N

40∘N

34∘N

36∘N

38∘N

40∘N

lt minus 20



(b)
















Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in






Acknowledgments


References













































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in




















Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

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