Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates
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.
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Format: | Article/Letter to editor biblioteca |
Language: | English |
Subjects: | atmospheric inversions, carbon cycle, dynamic global vegetation models, global carbon budget, |
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dig-wur-nl-wurpubs-5629812024-10-30 Bastos, A. O'Sullivan, M. Ciais, P. Makowski, D. Sitch, S. Friedlingstein, P. Chevallier, F. Rödenbeck, C. Pongratz, J. Luijkx, I.T. Patra, P.K. Peylin, P. Canadell, J.G. Lauerwald, R. Li, W. Smith, N.E. Peters, W. Goll, D.S. Jain, A.K. Kato, E. Lienert, S. Lombardozzi, D.L. Haverd, V. Nabel, J.E.M.S. Poulter, B. Tian, H. Walker, A.P. Zaehle, S. Article/Letter to editor Global Biogeochemical Cycles 34 (2020) 2 ISSN: 0886-6236 Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates 2020 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. en application/pdf https://research.wur.nl/en/publications/sources-of-uncertainty-in-regional-and-global-terrestrial-cosub2s 10.1029/2019GB006393 https://edepot.wur.nl/518899 atmospheric inversions carbon cycle dynamic global vegetation models global carbon budget https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/ Wageningen University & Research |
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atmospheric inversions carbon cycle dynamic global vegetation models global carbon budget atmospheric inversions carbon cycle dynamic global vegetation models global carbon budget |
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atmospheric inversions carbon cycle dynamic global vegetation models global carbon budget atmospheric inversions carbon cycle dynamic global vegetation models global carbon budget Bastos, A. O'Sullivan, M. Ciais, P. Makowski, D. Sitch, S. Friedlingstein, P. Chevallier, F. Rödenbeck, C. Pongratz, J. Luijkx, I.T. Patra, P.K. Peylin, P. Canadell, J.G. Lauerwald, R. Li, W. Smith, N.E. Peters, W. Goll, D.S. Jain, A.K. Kato, E. Lienert, S. Lombardozzi, D.L. Haverd, V. Nabel, J.E.M.S. Poulter, B. Tian, H. Walker, A.P. Zaehle, S. Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates |
description |
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. |
format |
Article/Letter to editor |
topic_facet |
atmospheric inversions carbon cycle dynamic global vegetation models global carbon budget |
author |
Bastos, A. O'Sullivan, M. Ciais, P. Makowski, D. Sitch, S. Friedlingstein, P. Chevallier, F. Rödenbeck, C. Pongratz, J. Luijkx, I.T. Patra, P.K. Peylin, P. Canadell, J.G. Lauerwald, R. Li, W. Smith, N.E. Peters, W. Goll, D.S. Jain, A.K. Kato, E. Lienert, S. Lombardozzi, D.L. Haverd, V. Nabel, J.E.M.S. Poulter, B. Tian, H. Walker, A.P. Zaehle, S. |
author_facet |
Bastos, A. O'Sullivan, M. Ciais, P. Makowski, D. Sitch, S. Friedlingstein, P. Chevallier, F. Rödenbeck, C. Pongratz, J. Luijkx, I.T. Patra, P.K. Peylin, P. Canadell, J.G. Lauerwald, R. Li, W. Smith, N.E. Peters, W. Goll, D.S. Jain, A.K. Kato, E. Lienert, S. Lombardozzi, D.L. Haverd, V. Nabel, J.E.M.S. Poulter, B. Tian, H. Walker, A.P. Zaehle, S. |
author_sort |
Bastos, A. |
title |
Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates |
title_short |
Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates |
title_full |
Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates |
title_fullStr |
Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates |
title_full_unstemmed |
Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates |
title_sort |
sources of uncertainty in regional and global terrestrial co2 exchange estimates |
url |
https://research.wur.nl/en/publications/sources-of-uncertainty-in-regional-and-global-terrestrial-cosub2s |
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