Quantifying Cloud Feedbacks for Climate Sensitivity


One of the more challenging aspects of climate science today is quantifying the cloud feedbacks to better constrain estimates for equilibrium climate sensitivity (ECS). It’s long been understood that low clouds generally have a cooling influence, while higher clouds increase warming via the greenhouse effect. Previous attempts at quantifying the net feedback have produced results where the confidence interval is larger than the estimate. For instance, Andrew Dessler’s estimates[1][2] were +0.50 ± 0.75 W/m^2/K over a 10 year period. Zhou’s estimate[3] was −0.16 ±0.83 W/m^2/K. Attempts at simulating clouds in some of the CMIP6 models have produced ECS values that are likely too high,[4] though many of these issues have since been largely resolved.[5][6][7].

A new study,[8] however, has succeeded at quantifying these cloud feedbacks at 0.43 ± 0.35 W/m^2/K. This means that for every 1 C warming, we can expect an additional 0.43 W/m^2, amplifying warming. Given these results, there is just a 2.5% chance that the net cloud feedback has a negative sign. These findings also help constrain values for ECS. The study estimates ECS to be 3.2 C, and argues that the chance that ECS is less than 2 C is about 0.5%. “Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m−2⋅K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K.” The paper is currently behind a paywall, but you can read a summary of it on CarbonBrief.[9]

References:

[1] Dessler, A. E. (2010), A determination of the cloud feedback from climate variations over the past decade, Science, 330, 1523– 1527, doi:10.1126/science.1192546.

[2] Dessler, A. E., and Loeb, N. G. (2013), Impact of dataset choice on calculations of the short‐term cloud feedback, J. Geophys. Res. Atmos., 118, 2821– 2826, doi:10.1002/jgrd.50199.

[3] Zhou, C., M. D. Zelinka, A. E. Dessler, and P. Yang, 2013: An Analysis of the Short-Term Cloud Feedback Using MODIS Data. J. Climate, 26, 4803–4815, https://doi.org/10.1175/JCLI-D-12-00547.1.

[4] Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M., Ceppi, P., et al. (2020). Causes of higher climate sensitivity in CMIP6 models. Geophysical Research Letters, 47, e2019GL085782. https://doi.org/10.1029/2019GL085782
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL085782

[5] Myers, T.A., Scott, R.C., Zelinka, M.D. et al. Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity. Nat. Clim. Chang. 11, 501–507 (2021). https://doi.org/10.1038/s41558-021-01039-0

[6] Mülmenstädt, J., Salzmann, M., Kay, J.E. et al. An underestimated negative cloud feedback from cloud lifetime changes. Nat. Clim. Chang. 11, 508–513 (2021). https://doi.org/10.1038/s41558-021-01038-1

[7] Stephens, G.L. The cooling of light rains in a warming world. Nat. Clim. Chang. 11, 468–470 (2021). https://doi.org/10.1038/s41558-021-01056-z

[8] Paulo Ceppi, Peer Nowack. Observational evidence that cloud feedback amplifies global warming. Proceedings of the National Academy of Sciences Jul 2021, 118 (30) e2026290118; DOI: 10.1073/pnas.2026290118 https://www.pnas.org/content/118/30/e2026290118

[9] Ayesha Tandon.Clouds study finds that low climate sensitivity is ‘extremely unlikely.’ CarbonBrief. July 21 2021. https://www.carbonbrief.org/clouds-study-finds-that-low-climate-sensitivity-is-extremely-unlikely?fbclid=IwAR225L6aKkDv4IVx-U6-t1qQeHJ01yEkF5NwAMULkJM_N51qugi9clbplSc


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