Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations. Issue 18 (21st September 2017)

• Record Type: Journal Article
• Authors: Fierce, Laura; McGraw, Robert L.
• Is Part Of: Journal of geophysical research. Volume 122:Issue 18(2017)
• Page Start: 9867
• Page End: 9878
• Publication Date: 2017-09-21
• Subjects: aerosol modeling -- cloud condensation nuclei -- particle‐based modeling -- quadrature method of moments; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2016JD026335
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Atmospheric aerosol is composed of distinct multicomponent particles that are continuously modified as they are transported in the atmosphere. 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. Unlike reduced representations common to large‐scale atmospheric models, such as modal and sectional schemes, the maximum‐entropy approach described here is not confined to predetermined size bins or assumed distribution shapes. This study is a first step toward a quadrature‐based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large‐scale simulations. Key Points: Key features of complex aerosol populations are accurately resolved using a reduced representation that employs numerical quadrature Continuous CCN activation spectra are accurately reconstructed from the sparse particles using constrained maximum entropy distributions