The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Less than 2 °C warming by 2100 unlikely
Open accessAbstract
The recently published Intergovernmental Panel on Climate Change (IPCC) projections to 2100 give likely ranges of global temperature increase in four scenarios for population, economic growth and carbon use1. However these projections are not based on a fully statistical approach. Here we use a country-specific version of Kaya’s identity to develop a statistically-based probabilistic forecast of CO2 emissions and temperature change to 2100. Using data for 1960-2010, including the UN’s probabilistic population projections for all countries2–4, we develop a joint Bayesian hierarchical model for GDP per capita and carbon intensity. We find that the 90% interval for cumulative CO2 emissions includes the IPCC’s two middle scenarios but not the extreme ones. The likely range of global temperature increase is 2.0–4.9°C, with median 3.2°C and a 5% (1%) chance that it will be less than 2°C (1.5°C). Population growth is not a major contributing factor. Our model is not a “business as usual” scenario, but rather is based on data which already show the effect of emission mitigation policies. Achieving the goal of less than 1.5°C warming will require carbon intensity to decline much faster than in the recent past.
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Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Paris Agreement climate proposals need a boost to keep warming well below 2 °C
Rogelj, J., den Elzen, M., Höhne, N., Fransen, T., Fekete, H., Winkler, H., Schaeffer, R., Sha, F., Riahi, K., & Meinshausen, M. (2016) · Nature · doi:10.1038/nature18307 · Cited by 3,637
Long-term economic growth projections in the Shared Socioeconomic Pathways
Dellink, R., Chateau, J., Lanzi, E., & Magné, B. (2017) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.06.004 · Cited by 893 · cited 7×
“Our predictive distribution of future world GDP per capita largely spans the range of scenarios used by the IPCC 20–22 , although there are large differences on a country-by-country basis.”
InfluentialBayesian probabilistic population projections for all countries
Raftery, A. E., Li, N., Ševčíková, H., Gerland, P., & Heilig, G. K. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211452109 · Cited by 298
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Biskaborn, B. K., Smith, S. L., Noetzli, J., Matthes, H., Vieira, G., Streletskiy, D. A., Schoeneich, P., Romanovsky, V. E., Lewkowicz, A. G., Abramov, A., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-08240-4 · Cited by 2,064
Comprehensive evidence implies a higher social cost of CO2
Rennert, K., Errickson, F., Prest, B. C., Rennels, L., Newell, R. G., Pizer, W., Kingdon, C., Wingenroth, J., Cooke, R., Parthum, B., et al. (2022) · Nature · doi:10.1038/s41586-022-05224-9 · Cited by 1,067
Self-citationGlobal Changes in Drought Conditions Under Different Levels of Warming
Naumann, G., Alfieri, L., Wyser, K., Mentaschi, L., Betts, R. A., Carrao, H., Spinoni, J., Vogt, J., & Feyen, L. (2018) · Geophysical Research Letters · doi:10.1002/2017gl076521 · Cited by 829
Anthropogenic warming exacerbates European soil moisture droughts
Samaniego, L., Thober, S., Kumar, R., Wanders, N., Rakovec, O., Pan, M., Zink, M., Sheffield, J., Wood, E. F., & Marx, A. (2018) · Nature Climate Change · doi:10.1038/s41558-018-0138-5 · Cited by 745
Recent responses to climate change reveal the drivers of species extinction and survival
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Metadata
- Authors
- Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R., & Liu, P.
- Venue
- Nature Climate Change
- Published
- 2017-07-31
- Volume
- 7
- Issue
- 9
- Pages
- 637-641
- ISSN
- 1758-678X (ISSN-L)
- 1758-6798
- OpenAlex
- W2740128796
- Cited by
- 711
- References
- 4
- FWCI
- 152.35
- Type
- journal article
- Language
- en
- Open access
- green
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- Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R., & Liu, P. (2017). Less than 2 °C warming by 2100 unlikely. Nature Climate Change. https://doi.org/10.1038/nclimate3352
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
