Articles | Volume 17, issue 5
https://doi.org/10.5194/bg-17-1343-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-1343-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach
Martin Jung
CORRESPONDING AUTHOR
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Christopher Schwalm
Woods Hole Research Center, Falmouth, MA 02540-1644, USA
Mirco Migliavacca
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Sophia Walther
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Gustau Camps-Valls
Image Processing Laboratory (IPL), Universitat de València,
Paterna, 46980, Spain
Sujan Koirala
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Peter Anthoni
Institute of Meteorology and Climate Research – Atmospheric
Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany
Simon Besnard
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Laboratory of Geo-Information Science and Remote Sensing, Wageningen
University and Research, Wageningen, 6708 PB, the Netherlands
Paul Bodesheim
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Computer Vision Group Mathematics and Computer Science, Friedrich Schiller University Jena, 07743 Jena, Germany
Nuno Carvalhais
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Departamento de Ciências e Engenharia do Ambiente (DCEA),
Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa,
Caparica, 2829-516, Portugal
Frédéric Chevallier
Laboratoire des Sciences du Climat et de l'Environnement (LSCE/IPSL),
Université Paris-Saclay, Gif-sur-Yvette, 91198, France
Fabian Gans
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Daniel S. Goll
Department of Geography, University of Augsburg, 86159 Augsburg,
Germany
Vanessa Haverd
Department Continental Biogeochemical Cycles, CSIRO Oceans and
Atmosphere, Canberra, 2601, Australia
Philipp Köhler
Division of Geological and Planetary Sciences, California Institute
of Technology, Pasadena, CA, USA
Kazuhito Ichii
Center for Environmental Remote Sensing (CEReS), Chiba University,
Chiba, 263-8522, Japan
Center for Global Environmental Research, National Institute for
Environmental Studies, Tsukuba, 305-8506, Japan
Atul K. Jain
Department of Atmospheric Science, University of Illinois, Urbana, IL 61801, USA
Junzhi Liu
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
School of Geography, Nanjing Normal University, Nanjing, 210023,
China
Danica Lombardozzi
Climate and Global Dynamics Laboratory, National Center for
Atmospheric Research, Boulder, CO 80307, USA
Julia E. M. S. Nabel
Department Land in the Earth System (LES), Max Planck Institute for
Meteorology, 20146 Hamburg, Germany
Jacob A. Nelson
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Michael O'Sullivan
College of Life and Environmental Sciences, University of Exeter,
Exeter, EX4 4QE, UK
Martijn Pallandt
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Dario Papale
Department of Innovation in Biology, Agri-food and Forest systems
(DIBAF), Tuscia University, Viterbo, 01100, Italy
Impacts on Agriculture, Forests and Ecosystem Services (IAFES),
Euro-Mediterranean Center on Climate Change (CMCC), Lecce, 01100, Italy
Wouter Peters
Department of Meteorology and Air Quality, Wageningen University and
Research, Wageningen, 6700 AA, the Netherlands
Julia Pongratz
Department of Geography, Ludwig-Maximilians-Universität
München, 80333 Munich, Germany
Department Land in the Earth System (LES), Max Planck Institute for
Meteorology, 20146 Hamburg, Germany
Christian Rödenbeck
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter,
Exeter, EX4 4QE, UK
Gianluca Tramontana
Department of Innovation in Biology, Agri-food and Forest systems
(DIBAF), Tuscia University, Viterbo, 01100, Italy
Image Processing Laboratory (IPL), Universitat de València,
Paterna, 46980, Spain
Anthony Walker
Climate Change Science Institute, Oak Ridge National Laboratory, Oak
Ridge, TN, USA
Ulrich Weber
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Markus Reichstein
Department of Biogeochemical Integration, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
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- Methodological advancement in deriving primary productivity and ecosystem respiration fluxes across different biomes A. Ravi et al. 10.1016/j.mex.2024.102773
- Vegetation Index‐Based Models Without Meteorological Constraints Underestimate the Impact of Drought on Gross Primary Productivity X. Chen et al. 10.1029/2023JG007499
- Direct measurement forest carbon protocol: a commercial system-of-systems to incentivize forest restoration and management B. Marino et al. 10.7717/peerj.8891
- Estimating carbon emissions from thermal power plants based on thermal characteristics K. Li et al. 10.1016/j.jag.2024.103768
Latest update: 13 Dec 2024
Short summary
We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
We test the approach of producing global gridded carbon fluxes based on combining machine...
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