AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA
Abstract View
Exploring the Relation between Aerosol Mixing State Metrics and Droplet Number Concentration
RICARDO MORALES BETANCOURT, Athanasios Nenes, Georgia Institute of Technology
Abstract Number: 548 Working Group: Aerosols, Clouds, and Climate
Abstract Aerosol-cloud interactions remain as one of the largest contributors to the uncertainty in global radiative forcing estimates. Both, the characteristics of the aerosol population, i.e., its size distribution, size resolved chemical composition and mixing state, as well as dynamic factors involved in the aerosol activation process play an important role in determining the number of aerosol particles that activate into cloud droplets. The mixing state of an aerosol population is often size dependent and evolves over time, and can have an important impact on the CCN activity. Because of its complexity, the development of an effective metric able to quantify aerosol mixing state has been elusive. Some such metrics capable of quantifying the type and extent of the mixing state of atmospheric particles have been recently developed (Riemer and West, 2013) through the use of a particle diversity index and a mixing state index. In this work we explore the relationship between particle diversity and mixing state index to the CCN activity of an aerosol population. This is performed using two aerosol models of different complexity. Firstly, we utilized the size resolved, two-moment aerosol model (TOMAS) to simulate the temporal evolution of the mixing state index in the aging aerosol population. The resulting aerosol size distributions where then used as input to an aerosol activation parameterization (Morales and Nenes, 2014) to determine the relation between mixing state and droplet number concentrations. In order to evaluate the global changes in aerosol mixing state, we utilized the Community Atmospheric Model version 5.1 (CAM5.1) with the 3 mode lognormal aerosol model to quantify the regional distribution of the changes in the mixing state metrics between present day and pre industrial times. The simulation results show that the mixing state index has increased over continental regions, dominated by the injection of sulfate aerosol.