Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been...

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Bibliographic Details
Main Authors: G. Tramontana, M. Jung, C. R. Schwalm, K. Ichii, G. Camps-Valls, B. Ráduly, M. Reichstein, M. A. Arain, A. Cescatti, G. Kiely, L. Merbold, P. Serrano-Ortiz, S. Sickert, S. Wolf, D. Papale
Format: Article
Language:English
Published: Copernicus Publications 2016-07-01
Series:Biogeosciences
Online Access:http://www.biogeosciences.net/13/4291/2016/bg-13-4291-2016.pdf

Internet

http://www.biogeosciences.net/13/4291/2016/bg-13-4291-2016.pdf

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