Passer à la navigation principale Passer à la recherche Passer au contenu principal

Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates

  • A. Bastos
  • , M. O'Sullivan
  • , P. Ciais
  • , D. Makowski
  • , S. Sitch
  • , P. Friedlingstein
  • , F. Chevallier
  • , C. Rödenbeck
  • , J. Pongratz
  • , I. T. Luijkx
  • , P. K. Patra
  • , P. Peylin
  • , J. G. Canadell
  • , R. Lauerwald
  • , W. Li
  • , N. E. Smith
  • , W. Peters
  • , D. S. Goll
  • , A. K. Jain
  • , E. Kato
  • S. Lienert, D. L. Lombardozzi, V. Haverd, J. E.M.S. Nabel, B. Poulter, H. Tian, A. P. Walker, S. Zaehle
  • Universität München
  • University of Exeter
  • Université Versailles-Saint Quentin
  • Université Paris-Saclay
  • CIRED
  • Max Planck Institute for Biogeochemistry
  • Max Planck Institute for Meteorology
  • Wageningen University & Research
  • JAMSTEC
  • Commonwealth Scientific and Industrial Research Organization
  • Université Libre de Bruxelles
  • Tsinghua University
  • ICS/University of Groningen
  • University of Augsburg
  • University of Illinois at Urbana-Champaign
  • Institute of Applied Energy (IAE)
  • University of Bern
  • National Center for Atmospheric Research
  • Université Paul Sabatier
  • GSFC Laboratory for Atmopsheres
  • Auburn University
  • Oak Ridge National Laboratory

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.

langue originaleAnglais
Numéro d'articlee2019GB006393
journalGlobal Biogeochemical Cycles
Volume34
Numéro de publication2
Les DOIs
étatPublié - 1 févr. 2020
Modification externeOui

SDG des Nations Unies

Ce résultat contribue à ou aux Objectifs de développement durable suivants

  1. SDG 15 - Vie sur terre
    SDG 15 Vie sur terre

Empreinte digitale

Examiner les sujets de recherche de « Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation