the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Systematic Observation-Based Estimate of Effective Radiative Forcing from Aerosol–Cloud Interactions
Abstract. The change in Earth's energy budget caused by anthropogenic aerosols interacting with clouds is the most uncertain contributor to the historical energy budget trend, with important implications for future climate projections. Recent studies estimating the effective radiative forcing from aerosol-cloud interactions (ERFaci) using satellite observations and a Cloud-Controlling Factor (CCF) analysis have produced a large spread of results, ranging from approximately -0.3 to -1.5 Wm-2. This spread is comparable to the full IPCC AR6 uncertainty range, reflecting the use of different datasets and methodological choices across studies, often without a systematic basis for selecting among them. Here we develop a unified framework to rigorously evaluate these methodological choices across multiple reanalysis datasets, using both climate model simulations and observed regional aerosol trends as independent validation tests. Applying model based bias-correction to the best configuration yields a best-estimate global ERFaci of -0.84 Wm-2 (66% confidence interval: -1.21 to -0.47 Wm-2) and an implied Equilibrium Climate Sensitivity of 3.33K (66% confidence interval: 2.65 to 4.22K), both consistent with IPCC AR6 and WCRP 2019 assessments but different from previous CCF-based estimates.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
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Status: open (until 22 Aug 2026)
- RC1: 'Comment on egusphere-2026-3075', Anonymous Referee #1, 10 Jul 2026 reply
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CC1: 'Comment on egusphere-2026-3075', Chanyoung Park, 23 Jul 2026
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Dear Omer Roi-Cohen and co-authors,
Thank you for this interesting and timely paper. I found the systematic comparison of CCF-based ERFaci methodologies very useful. I have a few comments on the perfect-model comparison and have attached here.
Best regards,
Chanyoung Park
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- 1
Omer Roi-Cohen
Gaea Hadary
Casey J. Wall
Paulo Ceppi
Overall, this is an important contribution to the literature on this topic of ERFaci which is still hotly debated. I appreciate the effort to reconcile various recent estimates of ERFaci, or at least document which analytic decisions lead to the major differences. While it is unsatisfying that the uncertainty range of the final report estimate is still just as large as in AR6, it is useful to know how smaller or larger estimates of the forcing have emerged. I have two major comments.
1. Regarding the use or not of the activation function (dNd/dA): Is this not more physical? You show that it performs worse against the RFMIP “ground truth”. But do you have a physical interpretation for why?
A very relevant reference for your discussion on aerosol proxy:
Hailing Jia et al., Optimal choice of proxy for cloud condensation nuclei reduces uncertainty in aerosol-cloud-climate forcing. Sci. Adv. 12, eaea4828(2026)..DOI:10.1126/sciadv.aea4828
2. Does ERFaci_low dominante? Is the ERFaci from non-low clouds really negligible? A lot rests on this one sentence caveat in L401.
These references all suggest that ACI in cold clouds can be substantial.
Zelinka, M. D., T. Andrews, P. M. Forster, and K. E. Taylor (2014), Quantifying components of aerosol-cloud-radiation interactions in climate models, J. Geophys. Res. Atmos., 119, 7599–7615, doi:10.1002/2014JD021710.
Alexandri, F., Müller, F., Choudhury, G., Achtert, P., Seelig, T., and Tesche, M.: A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations, Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, 2024.
Duran, B. M., N. J. Lutsko, and C. J. Wall, 2026: Aerosol–Ice–Cloud Interactions in a Perturbed Parameter Ensemble. J. Climate, 39, 4183–4203, https://doi.org/10.1175/JCLI-D-25-0724.1.
In particular, Duran et al. 2026 quantifies this ERFaci_ice = -0.43 W/m2. This is about 50% of the ERFaci_low you quantify. If you add these together it substantially increases the ERFaci (more negative) and the ECS (more positive). Your results currently do not really deviate from AR6 at all, but if there is a nonnegligible ERFaci_cold that may not be true at all.
The authors should at the very least substantially expand this one-sentence caveat. Preferably you would provide a more detailed quantification of either why you now believe this to be small or what the total low+non-low ERFaci actually is.
Minor comments:
L66: There is also considerable uncertainty on the total pre-industrial to present-day aerosol changes. This is worth emphasizing.
L149: Is the surface albedo calculated with clear-sky surface fluxes or TOA fluxes? This was unclear.
L309: Over Eastern North America, I would argue that MERRA and CAMS capture these trends at significantly different magnitudes. Why?
Fig 4b: Why is the largest ∆AI over the Arabian Peninsula?