Preprints
https://doi.org/10.5194/egusphere-2025-3755
https://doi.org/10.5194/egusphere-2025-3755
10 Sep 2025
 | 10 Sep 2025
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Remaining aerosol forcing uncertainty after observational constraint and the processes that cause it

Leighton A. Regayre, Léa M. C. Prévost, Kunal Ghosh, Jill S. Johnson, Jeremy E. Oakley, Jonathan Owen, Iain Webb, and Ken S. Carslaw

Abstract. Aerosol radiative forcing remains a major source of climate model uncertainty, limiting climate model projection skill and slowing global action on addressing climate risks. Observations only modestly constrain the magnitude of aerosol radiative forcing despite advances in model fidelity, resolution and availability of observations. Our goals are to understand where aerosol-cloud forcing uncertainty resists efforts to reduce (or constrain) it and to identify the processes that cause the remaining uncertainty, to guide future observation campaigns and model constraint efforts. We map the aerosol forcing uncertainty in a global climate model perturbed parameter ensemble before and after constraint to satellite observations of several cloud, aerosol and radiative properties. Original uncertainty falls by more than 80 % in Northern Hemisphere marine regions and by 70 % for globally averaged aerosol forcing. However, the uncertainty remains large (more than 70 % of the original uncertainty) in Southern Hemisphere marine environments where stratocumulus clouds transition to cumulus, as well as in some highly populated industrialized areas. Regional clusters of shared causes of model uncertainty highlight common processes as targets for future observational constraint. Our findings highlight the value in re-evaluating the remaining causes of ΔFaci uncertainty during the constraint process and provide actionable information for prioritizing existing observations that should be included as constraints. Additionally, our results highlight targeted observations in persistent uncertainty hotspots where novel and process-specific data could further constrain aerosol forcing. This work provides a framework for model evaluation and development that prioritises aerosol forcing constraint to improve model skill at making climate projections.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Leighton A. Regayre, Léa M. C. Prévost, Kunal Ghosh, Jill S. Johnson, Jeremy E. Oakley, Jonathan Owen, Iain Webb, and Ken S. Carslaw

Status: open (until 22 Oct 2025)

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Leighton A. Regayre, Léa M. C. Prévost, Kunal Ghosh, Jill S. Johnson, Jeremy E. Oakley, Jonathan Owen, Iain Webb, and Ken S. Carslaw
Leighton A. Regayre, Léa M. C. Prévost, Kunal Ghosh, Jill S. Johnson, Jeremy E. Oakley, Jonathan Owen, Iain Webb, and Ken S. Carslaw

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Short summary
Tiny particles called aerosols affect how much sunlight the Earth reflects back into space – one of the biggest climate uncertainties. We use a large set of climate model simulations and find that uncertainty drops in some regions, but persists in other areas, after comparing models to observations. By identifying the specific processes that cause the remaining uncertainty, we guide future efforts to reduce the aerosol forcing uncertainty so we can make more reliable climate predictions.
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