Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

Resolving variability in particle physical and chemical properties requires tracking high-dimensional probability density functions, which is not practical in large-scale atmospheric simulations. Reduced representations of atmospheric aerosol are needed for efficient regional-and global-scale chemical transport models.

Although the aerosol size-composition distribution is described by a high-dimensional probability density function, here we show that cloud condensation nuclei activity of aerosol populations can be represented with high accuracy using an optimized set of representative particles. The sparse representation of the aerosol mixing state, designed for use in quadrature-based moment models, is constructed from a linear program that is combined with an entropy-inspired cost function.