Linking global terrestrial CO2 fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric models

Atmospheric Chemistry and Physics, Vol. 21 (2021)

  • Z. Chen
  • Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
  • J. Liu
  • Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • D. K. Henze
  • Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, USA
  • D. N. Huntzinger
  • School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA
  • K. C. Wells
  • Department of Soil, Water, and Climate, University of Minnesota Twin Cities, St. Paul, MN, USA
  • S. Sitch
  • College of Life and Environmental Sciences, University of Exeter, Exeter, UK
  • P. Friedlingstein
  • College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
  • E. Joetzjer
  • Centre National de Recherche Météorologique, Unité mixte de recherche 3589 Meteo-France/CNRS, 42 Avenue Gaspard Coriolis, 31100 Toulouse, France
  • V. Bastrikov
  • Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre-Simon Laplace, CEA-CNRS-UVSQ, CE Orme des Merisiers, 91191 Gif-sur-Yvette CEDEX, France
  • D. S. Goll
  • Université Paris-Saclay, CEA-CNRS-UVSQ, LSCE/IPSL, Gif-sur-Yvette, France
  • V. Haverd
  • CSIRO Oceans and Atmosphere, G.P.O. Box 1700, Canberra, ACT 2601, Australia
  • A. K. Jain
  • Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
  • E. Kato
  • Institute of Applied Energy (IAE), Minato-ku, Tokyo 105-0003, Japan
  • S. Lienert
  • Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • D. L. Lombardozzi
  • Terrestrial Sciences Section, Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
  • P. C. McGuire
  • Department of Meteorology, Department of Geography and Environmental Science, National Centre for Atmospheric Science, University of Reading, Reading, UK
  • J. R. Melton
  • Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
  • J. E. M. S. Nabel
  • Max Planck Institute for Meteorology, Hamburg, Germany
  • B. Poulter
  • NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, USA
  • H. Tian
  • International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL, USA
  • A. J. Wiltshire
  • Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK
  • S. Zaehle
  • Max Planck Institute for Biogeochemistry, P.O. Box 600164, Hans-Knöll-Str. 10, 07745 Jena, Germany
  • S. M. Miller
  • Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA


Observations from the Orbiting Carbon Observatory 2 (OCO-2) satellite have been used to estimate CO2 fluxes in many regions of the globe and provide new insight into the global carbon cycle. The objective of this study is to infer the relationships between patterns in OCO-2 observations and environmental drivers (e.g., temperature, precipitation) and therefore inform a process understanding of carbon fluxes using OCO-2. We use a multiple regression and inverse model, and the regression coefficients quantify the relationships between observations from OCO-2 and environmental driver datasets within individual years for 2015–2018 and within seven global biomes. We subsequently compare these inferences to the relationships estimated from 15 terrestrial biosphere models (TBMs) that participated in the TRENDY model inter-comparison. Using OCO-2, we are able to quantify only a limited number of relationships between patterns in atmospheric CO2 observations and patterns in environmental driver datasets (i.e., 10 out of the 42 relationships examined). We further find that the ensemble of TBMs exhibits a large spread in the relationships with these key environmental driver datasets. The largest uncertainty in the models is in the relationship with precipitation, particularly in the tropics, with smaller uncertainties for temperature and photosynthetically active radiation (PAR). Using observations from OCO-2, we find that precipitation is associated with increased CO2 uptake in all tropical biomes, a result that agrees with half of the TBMs. By contrast, the relationships that we infer from OCO-2 for temperature and PAR are similar to the ensemble mean of the TBMs, though the results differ from many individual TBMs. These results point to the limitations of current space-based observations for inferring environmental relationships but also indicate the potential to help inform key relationships that are very uncertain in state-of-the-art TBMs.

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