The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
How Well Do We Understand and Evaluate Climate Change Feedback Processes?
Open accessAbstract
Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.
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Cites
Radiative forcing and climate response
Hansen, J., Sato, M., & Ruedy, R. (1997) · Journal of Geophysical Research: Atmospheres · doi:10.1029/96jd03436 · Cited by 2,241
Quantification of modelling uncertainties in a large ensemble of climate change simulations.
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., & Stainforth, D. A. (2004) · Nature · doi:10.1038/nature02771 · Cited by 1,655
Self-citationEmanuel, K. A. (1994) · doi:10.1093/oso/9780195066302.001.0001 · Cited by 1,205
Thermodynamic constraint on the cloud liquid water feedback in climate models
Betts, A. K., & Harshvardhan (1987) · Journal of Geophysical Research: Atmospheres · doi:10.1029/jd092id07p08483 · Cited by 160
Cited by
Challenges in combining projections from multiple climate models.
Knutti, R., Furrer, R., Tebaldi, C., Cermak, J., & Meehl, G. A. (2010) · Journal of Climate · doi:10.1175/2009jcli3361.1 · Cited by 1,270
Increase in hourly precipitation extremes beyond expectations from temperature changes
Lenderink, G., & van Meijgaard, E. (2008) · Nature Geoscience · doi:10.1038/ngeo262 · Cited by 1,072
Evaluation of climate models using palaeoclimatic data
Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte, V., Abe-Ouchi, A., Otto-Bliesner, B., & Zhao, Y. (2012) · Nature Climate Change · doi:10.1038/nclimate1456 · Cited by 1,013
The role of social and decision sciences in communicating uncertain climate risks
Pidgeon, N., & Fischhoff, B. (2011) · Nature Climate Change · doi:10.1038/nclimate1080 · Cited by 680
The equilibrium sensitivity of the Earth's temperature to radiation changes
Knutti, R., & Hegerl, G. C. (2008) · Nature Geoscience · doi:10.1038/ngeo337 · Cited by 490
Metadata
- Authors
- Bony, S., Colman, R., Kattsov, V. M., Allan, R. P., Bretherton, C. S., Dufresne, J.-L., Hall, A., Hallegatte, S., Holland, M. M., Ingram, W., Randall, D. A., Soden, B. J., Tselioudis, G., & Webb, M. J.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2006-08-01
- Volume
- 19
- Issue
- 15
- Pages
- 3445-3482
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W2052115269
- Cited by
- 1,038
- References
- 4
- FWCI
- 40.47
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bony, S., Colman, R., Kattsov, V. M., Allan, R. P., Bretherton, C. S., Dufresne, J.-L., Hall, A., Hallegatte, S., Holland, M. M., Ingram, W., Randall, D. A., Soden, B. J., Tselioudis, G., & Webb, M. J. (2006). How Well Do We Understand and Evaluate Climate Change Feedback Processes? Journal of Climate. https://doi.org/10.1175/jcli3819.1
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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.
