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.
Original language | English |
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Article number | e2019GB006393 |
Journal | Global Biogeochemical Cycles |
Volume | 34 |
Issue number | 2 |
DOIs | |
State | Published - Feb 1 2020 |
Funding
This work was partly supported by the European Space Agency Climate Change Initiative ESA-CCI RECCAP2 project (ESRIN/ 4000123002/18/I-NB). P. K. P. is partly supported by the Environment Research and Technology Development Fund (2-1701) of the Ministry of the Environment, Japan. A. J.'s effort was supported in part by the Department of Energy (DESC0016323) and NSF (NSF AGS 12-43071). P. C. acknowledges support from the European Research Council Synergy Project SyG-2013-610028 IMBALANCE-P, and P. C. and D. M. the ANR CLAND Convergence Institute. W. P. received funding from the European Research Council (ERC) for the Airborne Stable Isotopes of Carbon from the Amazon (ASICA) project, Contract 649087. N. E. S. received funding from the Netherlands Organisation for Scientific Research (NWO) for the Ruisdael Observatory. I. T. L. received funding from NWO under Contract 016.Veni.171.095. CT Europe simulations were performed using a grant for computing time (SH-312, 16666) from NWO. The CESM project is supported primarily by the National Science Foundation (NSF). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement 1852977. Computing and data storage resources, including the Cheyenne supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. Oak Ridge National Laboratory is operated by UT-Battelle, LLC, under Contract DE-AC05-00OR22725 with the U.S. Department of Energy. The authors would like to thank Corinne Le Quéré and Johannes Winckler for constructive comments in the preparation of this study and the ESA Soil Moisture CCI and the Fire-CCI teams for producing and maintaining the data sets used. The GRACE reconstructed data set was kindly provided by V. Humphrey.
Keywords
- atmospheric inversions
- carbon cycle
- dynamic global vegetation models
- global carbon budget