Structural and Parametric Contributions to Aerosol Effective Radiative Forcing Uncertainty in a Two-Model Perturbed Parameter Ensemble

Aerosol–cloud and aerosol–radiation interactions remain among the dominant sources of uncertainty in estimates of effective radiative forcing (ERF). Perturbed parameter ensembles (PPEs) are now increasingly used to evaluate climate model forcings and to diagnose sources of uncertainty. PPEs systematically sample uncertainty by performing large sets of simulations in which key model parameters are perturbed, allowing the sensitivity of model outcomes to individual processes to be quantified. When combined with Gaussian process emulators, PPE outputs can be efficiently extended to millions of model surrogates, enabling robust statistical assessments of model uncertainty. Here, we focus on aerosol-related sources of uncertainty in ERF.

This work applies a PPE–emulator framework in a two-model, one-to-one configuration to study both parametric and structural uncertainties in two Earth system models: OpenIFS/AC cycle48r1 (EC-Earth4) and ECHAM6.3-HAM2.3. Parameters are selected based on aerosol ERF uncertainty analyses in ECHAM6-HAM (Bhatti et al., 2026), with corresponding perturbations applied in OpenIFS/AC using identical parameter ranges.
Both model ensembles are evaluated against satellite observations from MODIS/Terra and POLDER-3/PARASOL for the year 2010, focusing on annual mean aerosol optical depth, single-scattering albedo, and Ångström exponent as key observables linking aerosol microphysics to ERF. 
In addition to the two-model comparison, we perform a detailed evaluation of the OpenIFS/AC PPE in its own right. This includes an assessment of regional patterns in aerosol properties and ERF, as well as a quantification of the relative contributions of individual parameters to model uncertainty. From the parametric uncertainty within OpenIFS/AC, we can identify model-specific sensitivities and regional responses for parameter constraining and model development.

Despite identical parameter perturbations, the two models exhibit systematic differences in their climate responses, associated with differences in aerosol life-cycle representation, cloud microphysics, and radiative coupling. Initial results indicate that sea-salt emissions contribute significantly to the largest global uncertainties in AOD at 550 nm in both models. The ERF uncertainties are driven by a more diverse set of parameters between the models, with fossil fuel, SO₂, dimethylsulfide (DMS), and biomass-burning emissions among the dominant contributors. The resulting inter-model spread can provide a quantitative measure of structural uncertainty that is not captured by single-model PPE studies. This two-model framework adds a structural dimension to previous PPE approaches by isolating structural effects under controlled parametric sampling.

 

Bhatti, Y. A., Watson-Parris, D., Regayre, L. A., Jia, H., Neubauer, D., Im, U., Svenhag, C., Schutgens, N., Tsikerdekis, A., Nenes, A., Irfan, M., van Diedenhoven, B., Arifi, A., Fu, G., and Hasekamp, O. P.: Uncertainty in aerosol effective radiative forcing from anthropogenic and natural aerosol parameters in ECHAM6.3-HAM2.3, Atmos. Chem. Phys., 26, 269–293, https://doi.org/10.5194/acp-26-269-2026, 2026.