Articles | Volume 13, issue 14
https://doi.org/10.5194/bg-13-4291-2016
https://doi.org/10.5194/bg-13-4291-2016
Research article
 | 
29 Jul 2016
Research article |  | 29 Jul 2016

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

Gianluca Tramontana, Martin Jung, Christopher R. Schwalm, Kazuhito Ichii, Gustau Camps-Valls, Botond Ráduly, Markus Reichstein, M. Altaf Arain, Alessandro Cescatti, Gerard Kiely, Lutz Merbold, Penelope Serrano-Ortiz, Sven Sickert, Sebastian Wolf, and Dario Papale

Related authors

Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements
Kukka-Maaria Kohonen, Roderick Dewar, Gianluca Tramontana, Aleksanteri Mauranen, Pasi Kolari, Linda M. J. Kooijmans, Dario Papale, Timo Vesala, and Ivan Mammarella
Biogeosciences, 19, 4067–4088, https://doi.org/10.5194/bg-19-4067-2022,https://doi.org/10.5194/bg-19-4067-2022, 2022
Short summary
Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020,https://doi.org/10.5194/bg-17-1343-2020, 2020
Short summary
Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017,https://doi.org/10.5194/bg-14-3685-2017, 2017
Short summary

Related subject area

Biogeochemistry: Modelling, Terrestrial
Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023,https://doi.org/10.5194/bg-20-4109-2023, 2023
Short summary
A modeling approach to investigate drivers, variability and uncertainties in O2 fluxes and O2 : CO2 exchange ratios in a temperate forest
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023,https://doi.org/10.5194/bg-20-4087-2023, 2023
Short summary
Modeling coupled nitrification–denitrification in soil with an organic hotspot
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023,https://doi.org/10.5194/bg-20-3895-2023, 2023
Short summary
A new method for estimating carbon dioxide emissions from drained peatland forest soils for the greenhouse gas inventory of Finland
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023,https://doi.org/10.5194/bg-20-3827-2023, 2023
Short summary
A global fuel characteristic model and dataset for wildfire prediction
Joe Ramu McNorton and Francesca Di Giuseppe
EGUsphere, https://doi.org/10.5194/egusphere-2023-1984,https://doi.org/10.5194/egusphere-2023-1984, 2023
Short summary

Cited articles

Alonso Fernández, J. R., Díaz-Muñiza, C., Garcia Nieto, P. J., de Cos, Juez, F. J., Sánchez, Lasheras, F., and Roqueñíc, M. N.: Forecasting the cyanotoxins presence in fresh waters: A new model based on genetic algorithms combined with the MARS technique, Ecol. Eng., 53, 68–78, https://doi.org/10.1016/j.ecoleng.2012.12.015, 2013.
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the land and ocean components of the global carbon cycle in the cmip5 earth system models, J. Climate, 26, 6801–6843, https://doi.org/10.1175/JCLI-D-12-00417.1, 2013.
Aubinet, M., Vesala, T., and Papale, D.: Eddy Covariance: A Practical Guide to Measurement and Data Analysis, Springer, Dordrecht Heidelberg London New York, 460 pp., 2012.
Baldocchi, D.: Breathing of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems, Aust. J. Bot., 56, 1–26, https://doi.org/10.1071/BT07151, 2008.
Download
Short summary
We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) and energy exchanges between land ecosystems and atmosphere. Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes. The results were good for all the ecosystems, with limitations to the ones in the extreme environments (cold, hot) or less represented in the training data (tropics).
Altmetrics
Final-revised paper
Preprint