@article{Jia:2026:10.1126/sciadv.aea4828,
author = {Jia, H and Quaas, J and Kroese, W and van, Diedenhoven B and Gryspeerdt, E and Böhm, C and Block, K and Hasekamp, O},
doi = {10.1126/sciadv.aea4828},
journal = {Science Advances},
title = {Optimal choice of proxy for cloud condensation nuclei reduces uncertainty in aerosol-cloud-climate forcing},
url = {http://dx.doi.org/10.1126/sciadv.aea4828},
volume = {12},
year = {2026}
}

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TY  - JOUR
AB  - Aerosol-cloud interactions (ACI) remain the largest uncertainty in anthropogenic climate forcings. Observation-based estimates of instantaneous radiative forcing from ACI (RFaci; the Twomey effect) rely on the choice of aerosol quantities as proxies for cloud condensation nuclei (CCN) concentrations, which differ in their ability to represent cloud-base CCN and data accuracy. Using diverse observations and aerosol-climate models, we evaluate the utility of different proxies with two independent approaches. Both approaches reveal that surface CCN exhibits the smallest bias in predicting RFaci (+5%), followed by aerosol index, surface sulfate and column CCN with similar biases of +25%, while aerosol optical depth and column sulfate show the largest biases (−60% and +92%). Constraining RFaci with the optimal proxy reduces uncertainty from 66 to 43%, yielding a less negative RFaci (−1.0 W m−2) than the unconstrained case (−1.2 W m−2). Our findings highlight the crucial role of proxy constraint in reconciling and improving RFaci estimates.
AU  - Jia,H
AU  - Quaas,J
AU  - Kroese,W
AU  - van,Diedenhoven B
AU  - Gryspeerdt,E
AU  - Böhm,C
AU  - Block,K
AU  - Hasekamp,O
DO  - 10.1126/sciadv.aea4828
PY  - 2026///
SN  - 2375-2548
TI  - Optimal choice of proxy for cloud condensation nuclei reduces uncertainty in aerosol-cloud-climate forcing
T2  - Science Advances
UR  - http://dx.doi.org/10.1126/sciadv.aea4828
UR  - https://doi.org/10.1126/sciadv.aea4828
VL  - 12
ER  - 

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