Abstract
Atmospheric aerosols are evolving mixtures of chemical species. In global climate models (GCMs), this “aerosol mixing state” is represented in a highly simplified manner. This can introduce errors in the estimates of climate-relevant aerosol properties, such as the concentration of cloud condensation nuclei. The goal for this study is to determine a global spatial distribution of aerosol mixing state with respect to hygroscopicity, as quantified by the mixing state metric χ . In this way, areas can be identified where the external or internal mixture assumption is more appropriate. We used the output of a large ensemble of particle-resolved box model simulations in conjunction with machine learning techniques to train a model of the mixing state metric χ . This lower-order model for χ uses as inputs only variables known to GCMs, enabling us to create a global map of χ based on GCM data. We found that χ varied between 20% and nearly 100%, and we quantified how this depended on particle diameter, location, and time of the year. This framework demonstrates how machine learning can be applied to bridge the gap between detailed process modeling and a large-scale climate model.
Highlights
Field measurements show that individual aerosol particles are a complex mixture of a wide variety of species, such as soluble inorganic salts and acids, insoluble crustal materials, trace metals, and carbonaceous materials [1,2]
Given a population of N aerosol particles, each consisting of some amounts of A distinct aerosol species, the mixing state metrics can be determined if the masses of species a in particle i are known, denoted by μia, for i = 1, . . . , N, and a = 1, . . . , A
Note that χ was calculated based on the entire size range of aerosol particles and if coarse-mode particles and fine-mode particles have different compositions, this would result in a lower χ value, even if the course and fine modes each had higher χ values
Summary
Field measurements show that individual aerosol particles are a complex mixture of a wide variety of species, such as soluble inorganic salts and acids, insoluble crustal materials, trace metals, and carbonaceous materials [1,2]. To characterize this mixture, the term “aerosol mixing state” is frequently used. This, in general, comprises both the distribution of chemical compounds across the aerosol population (“population mixing state”) and the distribution of chemical compounds within and on the surface of each particle (“morphological mixing state”). We will focus here exclusively on the population mixing state, and refer to it for brevity as “mixing state”
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