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Received:September 07, 2016  Revised:February 13, 2017  Click here to download the full text
Citation of this paper:,2017..Sciences in Cold and Arid Regions,9(2):127~141.
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Author NameAffiliationE-mail
HongYan Bao Key Laboratory of Arid Climate Change and Disaster Reduction of Gansu Province, College of Atmospheric Sciences, Lanzhou University, Lanzhou, Gansu 730000, China  
Kai Yang Key Laboratory of Arid Climate Change and Disaster Reduction of Gansu Province, College of Atmospheric Sciences, Lanzhou University, Lanzhou, Gansu 730000, China  
ChengHai Wang Key Laboratory of Arid Climate Change and Disaster Reduction of Gansu Province, College of Atmospheric Sciences, Lanzhou University, Lanzhou, Gansu 730000, China wch@lzu.edu.cn 
基金项目:This work is supported by the National Science Foundation of China (Nos. 91437217, 41275061, 41471034, and 41661144017) and the China National Basic Research Program (2013CBA01800).
 
Abstract:In this paper, the applicability of soil-moisture (SM) datasets of GLDAS (Global Land Data Assimilation System) in an alpine region (Tibet Plateau, TP) is investigated. The relations and discrepancies between the GLDAS-NOAH SM (0~10 cm) and the observations are compared; the possible reasons for errors over the TP are explored. The results show that GLDAS SM biases mainly show up in errors of values in the nonfrozen period (April to October) and changes of SM along with the temperature, especially during the freezing-thawing process in the frozen period (November to March). The biases of GLDAS SM in the nonfrozen period are mainly caused by the GLDAS precipitation-forcing data. The errors of GLDAS SM in the frozen period are speculated to be induced by the freeze-thaw parameterization scheme in the land-surface model.
keywords:soil moisture  GLDAS  Tibet Plateau  error analysis
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