10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
Investigation of Spatial and Temporal Variations in Aerosol Mixing State Using a Particle-Resolved Regional Aerosol Model
JEFFREY H. CURTIS, Nicole Riemer, Matthew West, University of Illinois at Urbana-Champaign
Abstract Number: 563 Working Group: Aerosol Transport and Transformation
Abstract The aerosol mixing state is critical for determining the microphysical interactions of particles with the large-scale atmospheric system, yet accurately capturing mixing state continues to be a major challenge for regional and global models. One of the aspects contributing to this challenge is that numerical models resort to simplified aerosol representations (modal or sectional) to reduce computational costs. These types of models greatly simplify the aerosol mixing state, and the assumptions made can result in errors in computed cloud and optical properties.
To quantify the importance of representing aerosol mixing state, the particle-resolved model PartMC-MOSAIC was coupled with the WRF model. The resulting model not only explicitly resolves and tracks the size and composition of individual particles as they undergo transformations by coagulation and condensation in the atmosphere, but also resolves the 3D spatial distribution of aerosols and trace gases, based on meteorological fields predicted by the WRF model. The novel computational methods developed for this purpose include a particle-resolved emission inventory and stochastic transport algorithms. Particle-resolved emissions are constructed using source apportionment in SMOKE. This source-oriented aerosol emission approach allows for different emission sectors to have varying aerosol composition rather than assuming all emissions of a given grid cell are internally mixed at the point of emission. Stochastic transport algorithms sample a small fraction of particles in each grid cell to be transported at each time step, allowing efficient advection and turbulent diffusion while maintaining numerical accuracy. With its fully-resolved mixing state representation, WRF-PartMC-MOSAIC allows for direct intermodel comparisons with aerosol schemes used in regional models (e.g., the sectional 4 or 8 bin MOSAIC), and climate models (e.g., MAM3/MAM4/MAM7).
We used WRF-PartMC-MOSAIC to simulate the spatial and temporal variations in aerosol composition over northern California during the CARES campaign in June 2010. Using the unique 3D particle-resolved aerosol data from the simulation, we directly compute 3D distributions of mixing state metrics and quantify the impact of mixing state on CCN and optical properties of the aerosol as it varies throughout the domain.