Open AccessDOI
Technical Description of version 4.0 of the Community Land Model (CLM)
W. Oleson,Mark Lawrence,B. Bonan,G. Flanner,Erik Kluzek,J. Lawrence,Samuel Levis,C. Swenson,E. Thornton,Aiguo Dai,Mark Decker,Robert E. Dickinson,Johannes J. Feddema,L. Heald,Forrest M. Hoffman,Jean-Francois Lamarque,Natalie M. Mahowald,Guo Yue Niu,Taotao Qian,James T. Randerson,S. W. Running,Koichi Sakaguchi,Andrew G. Slater,Reto Stöckli,Aihui Wang,Zong-Liang Yang,Xiaodong Zeng,Xubin Zeng +27 more
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The article was published on 2010-01-01 and is currently open access. It has received 1104 citations till now.read more
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Spatiotemporal variations in frozen ground and their impacts on hydrological components in the source region of the Yangtze River
Ruijie Shi,Hanbo Yang,Dawen Yang +2 more
TL;DR: In this paper, the authors evaluated the spatiotemporal variations in frozen ground and hydrological components by utilizing a geomorphology-based eco-hydrological model (GBEHM).
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On the Role of Land Surface Temperature as Proxy of Soil Moisture Status for Drought Monitoring in Europe
Carmelo Cammalleri,Jürgen Vogt +1 more
TL;DR: The analysis of the contingency matrix shows that the LST model is skillful in capturing extreme dry SM events, and it has a good overall capability to correctly detect the dry events in 66% of the cases, with an average probability of false alarm of about 30%.
Journal ArticleDOI
CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments
Bian He,Yimin Liu,Guoxiong Wu,Qing Bao,Tianjun Zhou,Xiaofei Wu,Lei Wang,Jiandong Li,Xiaocong Wang,Jinxiao Li,Wenting Hu,Xiaoqi Zhang,Xiaoqi Zhang,Chen Sheng,Yiqiong Tang,Yiqiong Tang +15 more
TL;DR: In this paper, the authors presented the results of the Coupled Model Intercomparison Project (CMIP6) Global Monsoon System (GMMIP) Tier-1 and Tier-3 experiments, and the model descriptions, experimental design and model outputs are demonstrated.
Journal ArticleDOI
A prognostic pollen emissions model for climate models (PECM1.0)
TL;DR: In this article, the authors developed a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters.
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