Mikkel Bennedsen, Eric Hillebrand, Morten Ørregaard Nielsen
arXiv 12 Dec 2024 · Statistics — Applications
arXiv:2412.09226 · PDF · DOI · OpenAlex · Extracted main text
The Global Carbon Budget, maintained by the Global Carbon Project, summarizes Earth's global carbon cycle through four annual time series beginning in 1959: atmospheric CO$_2$ concentrations, anthropogenic CO$_2$ emissions, and CO$_2$ uptake by land and ocean. We analyze these four time series as a multivariate (cointegrated) system. Statistical tests show that the four time series are cointegrated with rank three and identify anthropogenic CO$_2$ emissions as the single stochastic trend driving the nonstationary dynamics of the system. The three cointegrated relations correspond to the physical relations that the sinks are linearly related to atmospheric concentrations and that the change in concentrations equals emissions minus the combined uptake by land and ocean. Furthermore, likelihood ratio tests show that a parametrically restricted error-correction model that embodies these physical relations and accounts for the El Ni\~no/Southern Oscillation cannot be rejected on the data. The model can be used for both in-sample and out-of-sample analysis. In an application of the latter, we demonstrate that projections based on this model, using Shared Socioeconomic Pathways scenarios, yield results consistent with established climate science.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Bennedsen, Mikkel and Hillebrand, Eric and Koopman, Siem Jan (2023) A multivariate dynamic statistical model of the global carbon budget 1959–2020 self | 1.000 | 8 | 4 | 100% |
| 2 | Friedlingstein, P. and O'Sullivan, M. and Jones, M. W. and Andrew, R… (2023) Global Carbon Budget 2023 | 0.811 | 4 | 2 | 100% |
| 3 | Johansen, Søren (1995) Likelihood-Based Inference in Cointegrated Vector Autoregressive Models | 0.737 | 3 | 3 | 67% |
| Riahi2017 | unmatched citation key Riahi2017 | 0.737 | 3 | 2 | 100% |
| 5 | Canadell, Josep G. and Pataki, Diane E. and Gifford, Roger and Hough… (2007) Saturation of the Terrestrial Carbon Sink | 0.644 | 2 | 2 | 100% |
| 6 | Juselius, Katarina (2006) The Cointegrated VAR Model: Methodology and Applications | 0.644 | 2 | 2 | 100% |
| 7 | Le Quéré, Corinne and Rödenbeck, Christian and Buitenhuis, Erik T. a… (2007) Saturation of the Southern Ocean CO$_2$ Sink Due to Recent Climate Change | 0.644 | 2 | 2 | 100% |
| 8 | R. Bacastow and C. D. Keeling (1973) Atmospheric carbon dioxide and radiocarbon in the natural cycle: II. Changes from A. D. 1700 to 2070 as deduced from a geochemic… | 0.511 | 2 | 1 | 100% |
| 9 | P. Friedlingstein (2015) Carbon cycle feedbacks and future climate change | 0.511 | 2 | 1 | 100% |
| 10 | Feely, R. A. and Wanninkhof, R. and Takahashi, T. and Tans, P (1999) Influence of El Niño on the equatorial Pacific contribution to atmospheric CO$_2$ accumulation | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 41 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.