Articles | Volume 25, issue 13
https://doi.org/10.5194/acp-25-7299-2025
https://doi.org/10.5194/acp-25-7299-2025
ACP Letters
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14 Jul 2025
ACP Letters | Highlight paper |  | 14 Jul 2025

Observational constraints suggest a smaller effective radiative forcing from aerosol–cloud interactions

Chanyoung Park, Brian J. Soden, Ryan J. Kramer, Tristan S. L'Ecuyer, and Haozhe He

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Cited articles

Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. 
Albright, A. L., Proistosescu, C., and Huybers, P.: Origins of a Relatively Tight Lower Bound on Anthropogenic Aerosol Radiative Forcing from Bayesian Analysis of Historical Observations, J. Climate, 34, 8777–8792, https://doi.org/10.1175/JCLI-D-21-0167.1, 2021. 
Bennartz, R. and Rausch, J.: Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations, Atmos. Chem. Phys., 17, 9815–9836, https://doi.org/10.5194/acp-17-9815-2017, 2017. 
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Executive editor
Before acceptance of this preprint as an ACP Letter, as Executive Editor I requested that the authors clarify that that the approach they have taken to estimating ERFaci is only one of several others. Several other studies have applied multiple constraints simultaneously and reached different conclusions about the tightness of constraint. Reliance on one or a small number of constraints might lead to over-constraint, which I was concerned may be the reason for the overly tight constraint that is presented. In particular, ignoring conflicting constraints can lead to over-constraint. I requested that the author make clear that the tightness of constraint is inconsistent with other approaches in which a larger number of constraining observation types are used. Based on those alternative approaches, a larger uncertainty range remains plausible. Based on the added text drawing comparisons with previous similar and alternative studies, I am happy to accept it as a Letter based on the novelty and advancement in our quantification of aerosol radiative forcing.
Short summary
This study addresses the long-standing challenge of quantifying the impact of aerosol–cloud interactions. Using satellite observations, reanalysis data, and a "perfect-model" cross-validation, we show that explicitly accounting for aerosol–cloud droplet activation rates is key to accurately estimating ERFaci (effective radiative forcing due to aerosol–cloud interactions). Our results indicate a smaller and less uncertain ERFaci than previously assessed, implying the reduced role of aerosol–cloud interactions in shaping climate sensitivity.
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