气候变化领域集成服务门户(CCPortal): A Global High-Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling

CCPortal

DOI	10.1029/2019MS001784
	A Global High-Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling
	Dai Y.; Xin Q.; Wei N.; Zhang Y.; Shangguan W.; Yuan H.; Zhang S.; Liu S.; Lu X.
发表日期	2019
ISSN	19422466
起始页码	2996
结束页码	3023
卷号	11 期号:9
英文摘要	Modeling land surface processes requires complete and reliable soil property information to understand soil hydraulic and heat dynamics and related processes, but currently, there is no data set of soil hydraulic and thermal parameters that can meet this demand for global use. In this study, we propose a fitting approach to obtain the optimal soil water retention parameters from ensemble pedotransfer functions (PTFs), which are evaluated using the global coverage National Cooperative Soil Survey Characterization Database and show better performance for global applications than our original ensemble estimations (median values of PTFs) as done in Dai et al. (2013, https://doi.org/10.1175/JHM-D-12-0149.1). Soil hydraulic conductivities are still estimated as the median values of multiple PTFs, and the results are shown to perform comparably to the estimates from the existing precision-advanced models. Soil thermal properties are estimated following the schemes identified by Dai et al. (2019a, http://arxiv.org/abs/1908.04579), which evaluated several highly recommended schemes based on their land modeling applications. Using these approaches, we develop two global high-resolution data sets of soil hydraulic and thermal parameters based on Global Soil Dataset for Earth System Models (GSDE) and SoilGrids soil composition databases. The delivered variables include six basic soil properties, four soil hydraulic parameters in the Campbell (1974, https://doi.org/10.1097/00010694-197406000-00001) model, five soil hydraulic parameters in the van Genuchten (1980, https://doi.org/10.2136/sssaj1980.03615995004400050002x) model, and four soil thermal properties. The delivered data sets are available at a 30″ × 30″ geographical spatial resolution and provide four sets of vertical profiles following the resolutions of SoilGrids, Noah-Land Surface Models (LSM), Joint UK Land Environment Simulator (JULES), and Common Land Model/Community Land Model (CoLM/CLM). The data sets can be used in both regional and global applications. ©2019. The Authors.
英文关键词	global land surface modeling; high-resolution global soil data sets; soil hydraulic properties; soil thermal properties
语种	英语
scopus关键词	HTTP; Soil moisture; Soil surveys; Surface measurement; Global land surface; Land surface modeling; Pedotransfer functions; Soil data; Soil hydraulic conductivity; Soil hydraulic parameters; Soil hydraulic properties; Soil thermal properties; Thermodynamic properties; data set; hydraulic conductivity; hydraulic property; land surface; pedotransfer function; soil property; soil survey; soil water; spatial resolution; water retention
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156861
作者单位	Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China; School of Geography and Planning, Sun Yat-sen University, Guangzhou, China; Institute of Surface-Earth System Science, Tianjin University, Tianjin, China
推荐引用方式 GB/T 7714	Dai Y.,Xin Q.,Wei N.,et al. A Global High-Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling[J],2019,11(9).
APA	Dai Y..,Xin Q..,Wei N..,Zhang Y..,Shangguan W..,...&Lu X..(2019).A Global High-Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling.Journal of Advances in Modeling Earth Systems,11(9).
MLA	Dai Y.,et al."A Global High-Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling".Journal of Advances in Modeling Earth Systems 11.9(2019).