Propagation of CAMS Aerosol Uncertainty to Clear-sky Solar Irradiance Estimates

Abstract. Atmospheric aerosols strongly influence surface solar radiation (SSR) through scattering and absorption processes, introducing substantial uncertainties into SSR estimates. Despite the increasing use of atmospheric reanalysis products for solar resource assessment, the propagation of aerosol-related uncertainty into SSR calculations remains insufficiently quantified. In this study, we derive aerosol optical depth (AOD) uncertainties for the fourth-generation ECMWF Atmospheric Composition Reanalysis 4 (EAC4) and investigate their propagation into clear-sky estimates of global horizontal irradiance (GHI) and direct normal irradiance (DNI) over the 60° S–60° N domain for the 2003–2024 period. Prognostic AOD uncertainties are calculated using collocated EAC4 and Aerosol Robotic Network (AERONET) observations, while the resulting global mean relative AOD uncertainty is approximately 47 %. Radiative kernels are subsequently used to quantify the sensitivity of clear-sky SSR to AOD perturbations, enabling the propagation of AOD uncertainty into GHI and DNI estimates. The results reveal pronounced spatial and seasonal variability, with the largest propagated uncertainties occurring over regions affected by persistent anthropogenic pollution, biomass burning, and desert dust. Relative GHI uncertainties generally remain below 5–6 %, whereas relative DNI uncertainties frequently exceed 18 % over major aerosol source regions and reach 25–35 % seasonally under elevated aerosol loading. Overall, the proposed framework provides a computationally efficient methodology for generating uncertainty-aware solar radiation products and supports future investigations of aerosol-driven dimming and brightening, as well as long-term solar energy resource assessments under changing atmospheric conditions.