1,2,4,3- 1University of Exeter, Mathematics and Statistics, Exeter, United Kingdom of Great Britain – England, Scotland, Wales (f.h.lambert@exeter.ac.uk)
- 2Imperial College, London, Physics, London, United Kingdom of Great Britain – England, Scotland, Wales (p.ceppi@imperial.ac.uk)
- 3Lawrence Livermore National Laboratory, Livermore, CA, United States (chao5@llnl.gov)
- 4University of Reading, Meteorology, Reading, United Kingdom of Great Britain – England, Scotland, Wales (S.J.Ferrett@reading.ac.uk)
- 5Met Office, Hadley Centre, Exeter, United Kingdom of Great Britain – England, Scotland, Wales (mark.webb@metoffice.gov.uk)
The Sherwood et al. assessment [1] of Earth's climate sensitivity to a doubling of atmospheric carbon dioxide concentration broke new ground in providing estimates of radiative feedback and its components through the use of multiple lines of evidence. The assessment combined evidence from Global Climate Models (GCMs) with evidence from observations and process models that are able to produce more defensible estimates of small-scale and poorly-understood processes. However, by treating estimates of the different components of feedbacks as independent of one another, Sherwood ignored correlations between different feedbacks, which could impact the uncertainty affecting the estimate of overall feedback. The exception to this was the well-known water vapour-lapse rate anti-correlation, which they did consider.
In this study, we first undertake a perfect model experiment with the CMIP5 and CMIP6 ensembles that demonstrates the effects of considering correlations between components of feedbacks on estimates of net radiative feedback in a Sherwood-type analysis. Second, we explore correlations between contemporary estimates of feedback components from observed climate variability and cloud controlling factor analysis. Correlations between components have a similar structure for both perfect model and contemporary estimates. It is found that introducing feedback correlations into the Sherwood framework increases the standard deviation of the net feedback uncertainty by about 30 %. Impacts on estimates of climate sensitivity are smaller, because the process-based estimate of radiative feedback is only one part of the sensitivity estimate.
Prospects for future feedback and sensitivity estimates are discussed. The caveat to our results is that Sherwood's estimates of feedback components come from different sources. Although our results suggest that at least some of these show similar correlation structures, there is a need for future work that aims to understand the physical and statistical relationships between estimates of different components of feedback.
Reference
[1] Sherwood et al., 2020, Rev. Geophys., https://doi.org/10.1029/2019RG000678.
How to cite: Lambert, H., Ceppi, P., Chao, L.-W., Ferrett, S., Webb, M., and Zelinka, M.: Relationships between feedback components alter estimates of total radiative feedback and climate sensitivity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13799, https://doi.org/10.5194/egusphere-egu26-13799, 2026.
