Preprints
https://doi.org/10.5194/egusphere-2026-2811
https://doi.org/10.5194/egusphere-2026-2811
19 Jun 2026
 | 19 Jun 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Base-state dependence of parameter sensitivity for the Twomey effect in a perturbed parameter ensemble

Sophie Wynn, Duncan Watson-Parris, Brandon M. Duran, and Johannes Mülmenstädt

Abstract. A major source of uncertainty in the effective radiative forcing due to aerosol-cloud interactions (ERFaci) arises from parameters that represent unresolved sub-grid-scale processes in global climate models. Constraining parametric uncertainty requires identifying parameters driving the largest spread in ERFaci. Perturbed parameter ensembles (PPE) address this by systematically varying parameters related to aerosol emission, cloud microphysics, and associated small-scale processes. We perform a global sensitivity analysis of the three components of ERFaci from liquid clouds, the Twomey effect, liquid water path (LWP), and cloud fraction (CF) adjustments, in a PPE with and without constraining to the model's present-day base state. Under uniform prior sampling, autoconversion parameters unrelated to aerosol activation counterintuitively dominate the Twomey effect. Only after constraining the base state are aerosol emission and activation parameters revealed as controlling parameters for the Twomey effect. The apparent control of autoconversion parameters over the Twomey effect arises because these parameters control the cloud base state, which in turn affects the strength of the Twomey effect. The dominant parameters for LWP and CF adjustments remain related to autoconversion before and after the constraint. Constraining to the base state is therefore essential to inferring the correct parameters and processes controlling the model’s climate responses.

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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Sophie Wynn, Duncan Watson-Parris, Brandon M. Duran, and Johannes Mülmenstädt

Status: open (until 19 Jul 2026)

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Sophie Wynn, Duncan Watson-Parris, Brandon M. Duran, and Johannes Mülmenstädt
Sophie Wynn, Duncan Watson-Parris, Brandon M. Duran, and Johannes Mülmenstädt
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Short summary
Climate models use uncertain parameters to represent aerosol–cloud processes. To identify which parameters are most important, commonly scientists a multitude of simulations where these parameters are varied uniformly. We show that restricting our analysis to simulations matching the base cloud state gives a different and more meaningful answer about which parameters drive the forcing related to aerosol-cloud interactions.  
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