Optimal choice of proxy for cloud condensation nuclei reduces uncertainty in aerosol-cloud-climate forcing.
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Where this comes from
- Record sourced from PubMed, PMID 41706857.
- Also identified by DOI 10.1126/sciadv.aea4828 and PMC identifier 12915600.
- Licence recorded as CC BY-NC.
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Abstract
Aerosol-cloud interactions (ACI) remain the largest uncertainty in anthropogenic climate forcings. Observation-based estimates of instantaneous radiative forcing from ACI (RF<sub>aci</sub>; 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 RF<sub>aci</sub> (+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 RF<sub>aci</sub> with the optimal proxy reduces uncertainty from 66 to 43%, yielding a less negative RF<sub>aci</sub> (-1.0 W m<sup>-2</sup>) than the unconstrained case (-1.2 W m<sup>-2</sup>). Our findings highlight the crucial role of proxy constraint in reconciling and improving RF<sub>aci</sub> estimates.