Improving the representation of light-absorbing aerosol in large-scale atmospheric models through particle-resolved modeling

Description

One challenge in the simulation of light-absorbing aerosol is the representation of particle-scale variability in aerosol physical and chemical properties. Tracking the composition of individual particles is computationally expensive, so large-scale models simplify the representation of particle size, shape, and chemical composition. At the other extreme, the particle-resolved model PartMC-MOSAIC tracks the composition of individual particles as they evolve due to emission, dilution, condensation of semi-volatile gases, and coagulation. While the particle-resolved model is computationally too expensive to be implemented in large-scale atmospheric models, we show that series of particle-resolved simulations can be used to parameterize key aerosol processes that are not well constrained in large-scale models. Parametric relationships that represent the evolution of particle hygroscopic properties, which is important for predicting the lifetime and burden of light-absorbing aerosol, and to represent light absorption by populations of multicomponent particles will be presented. We show that climate-relevant aerosol properties are sensitive to the improved treatment of the aerosol evolution and optical properties, suggesting that parameterization through multi-scale modeling may be an effective method for improving the representation of aerosol processes in large-scale models.