title: Reducing uncertainties in decadal variability of the global carbon budget with multiple datasets.
abstract: Conventional calculations of the global carbon budget infer the land sink as a residual between emissions, atmospheric accumulation, and the ocean sink. Thus, the land sink accumulates the errors from the other flux terms and bears the largest uncertainty. Here, we present a Bayesian fusion approach that combines multiple observations in different carbon reservoirs to optimize the land (B) and ocean (O) carbon sinks, land use change emissions (L), and indirectly fossil fuel emissions (F) from 1980 to 2014. Compared with the conventional approach, Bayesian optimization decreases the uncertainties in B by 41% and in O by 46%. The L uncertainty decreases by 47%, whereas F uncertainty is marginally improved through the knowledge of natural fluxes. Both ocean and net land uptake (B + L) rates have positive trends of 29 ± 8 and 37 ± 17 Tg C⋅y-2since 1980, respectively. Our Bayesian fusion of multiple observations reduces uncertainties, thereby allowing us to isolate important variability in global carbon cycle processes.
authors: Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives-CNRS-Université de Versailles Saint-Quentin, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France; wei.li@lsce.ipsl.fr.
authors: Wei
authors: W
authors: Li
authors: Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives-CNRS-Université de Versailles Saint-Quentin, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France.
authors: Philippe
authors: P
authors: Ciais
authors: Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives-CNRS-Université de Versailles Saint-Quentin, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France.
authors: Yilong
authors: Y
authors: Wang
authors: Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives-CNRS-Université de Versailles Saint-Quentin, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France.
authors: Shushi
authors: S
authors: Peng
authors: Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives-CNRS-Université de Versailles Saint-Quentin, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France.
authors: Grégoire
authors: G
authors: Broquet
authors: Department of Ecosystem and Conservation Science, University of Montana, Missoula, MT 59812.
authors: Ashley P
authors: AP
authors: Ballantyne
authors: Global Carbon Project, Commonwealth Scientific and Industrial Research Organization Oceans and Atmosphere, Canberra, ACT 2601, Australia.
authors: Josep G
authors: JG
authors: Canadell
authors: Department of Ecosystem and Conservation Science, University of Montana, Missoula, MT 59812.
authors: Leila
authors: L
authors: Cooper
authors: College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, United Kingdom.
authors: Pierre
authors: P
authors: Friedlingstein
authors: Tyndall Centre for Climate Change Research, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, United Kingdom.
authors: Corinne
authors: C
authors: Le Quéré
authors: Department of Earth and Environment, Boston University, Boston, MA 02215.
authors: Ranga B
authors: RB
authors: Myneni
authors: Center for International Climate and Environmental Research-Oslo, 0349 Oslo, Norway.
authors: Glen P
authors: GP
authors: Peters
authors: Department of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
authors: Shilong
authors: S
authors: Piao
authors: Max Planck Institute for Meteorology, 20146 Hamburg, Germany.
authors: Julia
authors: J
authors: Pongratz
keywords: Bayesian fusion; carbon cycle; decadal variations; global carbon budget