Quantifying the impact of unresolved particle properties on light absorption by carbonaceous aerosol

Abstract:

Radiative absorption by carbonaceous aerosol depends on internal mixing within individual particles, but the composition and morphology of aerosol particles is necessarily approximated in large-scale atmospheric models. In this study, we introduce a parameterization that predicts the absorption coefficient of particle populations containing black and brown carbon, while also representing uncertainty in absorption from unresolved particle properties. The parameterization is a Bayesian linear regression model that was trained using ensembles of simulations with the particle-resolved model PartMC-MOSAIC. PartMC-MOSAIC is the only aerosol scheme that tracks per-particle composition of many thousands of particles in evolving aerosol populations, but this detailed model is computationally expensive. As an alternative to resolving per-particle properties in large-scale models, this study presents a hierarchical modeling framework for approximating key processes, such as aerosol water uptake and the impact of inter- and intra-particle mixing, in terms of variables that many large-scale models already carry.