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

L. Regayre,Léa M. C. Prévost,Kunal Ghosh,Jill S. Johnson,Jeremy E. Oakley,Jonathan Owen,Iain Webb,K. Carslaw

Published 2026 in Atmospheric Chemistry and Physics

ABSTRACT

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.

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