Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning
出版年份 2016 全文链接
标题
Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning
作者
关键词
-
出版物
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 121, Issue 22, Pages 13,218-13,235
出版商
American Geophysical Union (AGU)
发表日期
2016-10-19
DOI
10.1002/2016jd024821
参考文献
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- Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling
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- Land-Surface-Atmosphere Coupling in Observations and Models
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- TURNER REVIEW No. 15.'Breathing' of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems
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