Model-based estimation of the global carbon budget and its uncertainty from carbon dioxide and carbon isotope records

Journal Article · Mon Dec 27 04:00:00 EST 1999 · Journal of Geophysical Research

DOI:https://doi.org/10.1029/1999JD900992· OSTI ID:20215609

Kheshgi, Haroon S ^[1]; Jain, Atul K ^[2]; Wuebbles, Donald J ^[2]

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1. Corporate Research Laboratories, Exxon Research and Engineering Company, Annandale, New Jersey (United States)
2. Department of Atmospheric Sciences, University of Illinois, Urbana (United States)

A global carbon cycle model is used to reconstruct the carbon budget, balancing emissions from fossil fuel and land use with carbon uptake by the oceans, and the terrestrial biosphere. We apply Bayesian statistics to estimate uncertainty of carbon uptake by the oceans and the terrestrial biosphere based on carbon dioxide and carbon isotope records, and prior information on model parameter probability distributions. This results in a quantitative reconstruction of past carbon budget and its uncertainty derived from an explicit choice of model, data-based constraints, and prior distribution of parameters. Our estimated ocean sink for the 1980s is 17{+-}7 Gt C (90% confidence interval) and is comparable to the estimate of 20{+-}8 Gt C given in the recent Intergovernmental Panel on Climate Change assessment [Schimel et al., 1996]. Constraint choice is tested to determine which records have the most influence over estimates of the past carbon budget; records individually (e.g., bomb-radiocarbon inventory) have little effect since there are other records which form similar constraints. (c) 1999 American Geophysical Union.

• OSTI ID: 20215609
• Journal Information: Journal of Geophysical Research, Journal Name: Journal of Geophysical Research Journal Issue: D24 Vol. 104; ISSN JGREA2; ISSN 0148-0227
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
ATMOSPHERIC CHEMISTRY
CARBON COMPOUNDS
CLIMATIC CHANGE
EXPERIMENTAL DATA
MATHEMATICAL MODELS
OCEANOGRAPHY
STATISTICS
THEORETICAL DATA