Interactions between aerosols, clouds, and radiation remain one of the largest sources of uncertainty in effective radiative forcing (ERF), limiting the accuracy of climate projections. Despite progress, key sources of parametric and structural uncertainty in aerosol–cloud and aerosol–radiation interactions remain poorly quantified. This study addresses this gap using a perturbed parameter ensemble (PPE) of 221 simulations with the ECHAM6.3-HAM2.3 climate model, varying 23 aerosol-related parameters that control emissions, removal, chemistry, and microphysics. The resulting global mean aerosol ERF is -1.24 Wm<sup>-2</sup> (5–95 percentile: -1.56 to -0.89 Wm<sup>-2</sup>). We find that uncertainty in aerosol ERF is dominated by sulfate-related processes, biomass burning, size, and natural emissions. Here, for Aerosol-Cloud Interactions, DMS and biomass burning emissions are important, whereas for Aerosol-Radiation Interactions, sulfate chemistry and dry deposition are important. Despite structural differences across models, the leading causes of ERF uncertainty identified here align with findings from other PPEs.</p> <p>Comparison with satellite retrievals from POLDER-3/PARASOL reveals persistent model biases in aerosol optical depth (AOD), Ångström exponent (AE), and single-scattering albedo (SSA), many of which fall within the parametric uncertainty bounds of the PPE. Sulfate-related processes account for over 40 % of AOD uncertainty, while AE and SSA uncertainties are strongly influenced by DMS, sea salt, and black carbon properties. PPEs can reduce some structural model biases through parameter adjustments, but others persist. These results highlight the need for combined efforts in parameter perturbation and structural model development to improve confidence in aerosol-forcing estimates and future climate projections.