The scenario-based variations and causes of future surface soil moisture across China in the twenty-first century

被引:15
作者
Fan, Keke [1 ,2 ,3 ]
Zhang, Qiang [1 ,2 ,3 ]
Li, Jianping [4 ]
Chen, Deliang [5 ]
Xu, Chong-Yu [6 ]
机构
[1] Beijing Normal Univ, Minist Educ, Key Lab Environm Change & Nat Disaster, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
[3] Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Fac Geog Sci, Beijing 100875, Peoples R China
[4] Ocean Univ China, Minist Educ, Key Lab Phys Oceanog, Qingdao 266100, Peoples R China
[5] Univ Gothenburg, Dept Earth Sci, Reg Climate Grp, Box 460, SE-40530 Gothenburg, Sweden
[6] Univ Oslo, Dept Geosci & Hydrol, POB 1047, N-016 Oslo, Norway
基金
美国国家科学基金会;
关键词
surface soil moisture; spatiotemporal evolution; climate scenarios; hydrological cycle; AIR-TEMPERATURE; LAND; CLIMATE; REGIONS; TRENDS; PRECIPITATION; ASSIMILATION; AGRICULTURE; DROUGHT;
D O I
10.1088/1748-9326/abde5e
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Surface soil moisture (SSM) is a key factor for water and heat exchanges between land surface and the atmosphere. It is also important to water resources, agriculture, and ecosystems. In the backdrop of global warming, SSM variations and potential causes are not well-known at regional scales. Based on soil moisture (SM) data from GLDAS-Noah and 16 global climate models (GCMs) selected from 25 GCMs in CMIP5, we analyzed spatial distribution and temporal changes of SSM in China and quantified fractional contributions of four meteorological factors to the SSM variations. The selected models have the same direction of historic trends in SSM during 1981-2005 as those in the GLDAS SSM data which were also further used to calibrate the trends simulated by the 16 GCMs. Based on the calibration results for the 16 GCMs, future SSMs for nine regions were analyzed in mainland China under four Intergovernmental Panel on Climate Change emission scenarios. No significant changes were identified in SSM across most regions of mainland China under RCP2.6 scenario. However, there is a general wetting tendency in the arid regions and drying tendency across the humid regions under all the scenarios except RCP2.6. In general, the higher the global temperature raises, the more grids with significant increase or significant decrease in SSM. These findings contradicted prevailing view that wet regions get wetter and dry regions get drier. Attribution analysis indicates that precipitation acts as the major driver for SSM variations and contributes up to 43.4% of SSM variations across China. These results provide new insights into future SSM response to climate warming and a scientific basis to mitigation and adaptation works related to SSM in the future.
引用
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页数:14
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