1. Sources of Uncertainty in Regional and Global Terrestrial CO 2 Exchange Estimates
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Julia E. M. S. Nabel, Anthony P. Walker, Danica Lombardozzi, Naomi E. Smith, B. Poulter, Stephen Sitch, Christian Rödenbeck, Ingrid T. Luijkx, Sönke Zaehle, Frédéric Chevallier, Wei Li, J. G. Canadell, Atul K. Jain, Etsushi Kato, P. Ciais, Wouter Peters, P. Peylin, Sebastian Lienert, Daniel S. Goll, V. Haverd, Pierre Friedlingstein, Prabir K. Patra, Ronny Lauerwald, Hanqin Tian, Julia Pongratz, Michael O'Sullivan, David Makowski, Ana Bastos, College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, LUDWIG MAXIMILIANS UNIVERSITAT MUNCHEN DEPARTMENT OF GEOGRAPHY MUNICH DEU, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Agronomie, AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), College of Life and Environmental Sciences [Exeter], Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Max-Planck-Institut für Biogeochemie (MPI-BGC), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, WUR - Wageningen University and Research Centre [Wageningen], Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), CSIRO Oceans and Atmosphere, CISRO Oceans and Atmosphere, Department of Geosciences, Environment and Society, Université libre de Bruxelles (ULB), Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Wageningen University and Research [Wageningen] (WUR), Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], Department of Geography, University of Augsburg, Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Institute of Applied Energy (IAE), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], CLIMATE AND GLOBAL DYNAMICS LABORATORY NATIONAL CENTER FOR ATMOSPHERIC RESEARCH BOULDER USA, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Biospheric Sciences Laboratory, NASA Goddard Space Flight Center (GSFC), INTERNATIONAL CENTER FOR CLIMATE AND GLOBAL CHANGE RESEARCH AUBURN UNIVERSITY AUBURN USA, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Max Planck Institute for Biogeochemistry (MPI-BGC), European Comission. Grant Numbers: ASICA (649087), IMBALANCE-P European Space Agency (ESA). Grant Number: ESRIN/ 4000123002/18/I-NB National Science Foundation (NSF). Grant Number: AGS 12-43071 U.S. Department of Energy (DOE). Grant Number: DESC0016323, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), and Isotope Research
- Subjects
0106 biological sciences ,Meteorologie en Luchtkwaliteit ,FLUXES ,Atmospheric Science ,010504 meteorology & atmospheric sciences ,Meteorology and Air Quality ,Biome ,BURNED AREA PRODUCT ,atmospheric inversions ,01 natural sciences ,Carbon cycle ,DATA ASSIMILATION ,Data assimilation ,PLANT FUNCTIONAL TYPES ,global carbon budget ,carbon cycle ,Environmental Chemistry ,Land use, land-use change and forestry ,ATMOSPHERIC CO2 ,0105 earth and related environmental sciences ,General Environmental Science ,ddc:910 ,LAND-COVER CHANGE ,Global and Planetary Change ,WIMEK ,FOSSIL-FUEL ,Land use ,business.industry ,010604 marine biology & hydrobiology ,VEGETATION MODEL ORCHIDEE ,Fossil fuel ,Vegetation ,15. Life on land ,CARBON-DIOXIDE EMISSIONS ,13. Climate action ,Climatology ,[SDE]Environmental Sciences ,dynamic global vegetation models ,Environmental science ,business ,Scale (map) ,INCORPORATING SPITFIRE - Abstract
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.
- Published
- 2020
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