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Toward Reduced Representation of Mixing State for Simulating Aerosol Effects on Climate

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  • 1 Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York
  • | 2 Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois
  • | 3 Department of Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois
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Abstract

Atmospheric aerosols affect Earth’s energy budget, and hence its climate, by scattering and absorbing solar radiation and by altering the radiative properties and the lifetime of clouds. These two major aerosol effects depend on the optical properties and the cloud-nucleating ability of individual particles, which, in turn, depend on the distribution of components among individual particles, termed the “aerosol mixing state.” Global models have moved toward including aerosol schemes to represent the evolution of particle characteristics, but individual particle properties cannot be resolved in global-scale simulations. Instead, models approximate the aerosol mixing state. The errors in climate-relevant aerosol properties introduced by such approximations may be large but have not yet been well quantified. This paper quantitatively addresses the question of to what extent the aerosol mixing state must be resolved to adequately represent the optical properties and cloud-nucleating properties of particle populations. Using a detailed benchmarking model to simulate gas condensation and particle coagulation, we show that, after the particles evolve in the atmosphere, simple mixing-state representations are sufficient for modeling cloud condensation nuclei concentrations, and we quantify the mixing time scale that characterizes this transformation. In contrast, a detailed representation of the mixing state is required to model aerosol light absorption, even for populations that are fully mixed with respect to their hygroscopic properties.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Laura Fierce, lfierce@bnl.gov

A supplement to this article is available online (10.1175/BAMS-D-16-0028.2).

Abstract

Atmospheric aerosols affect Earth’s energy budget, and hence its climate, by scattering and absorbing solar radiation and by altering the radiative properties and the lifetime of clouds. These two major aerosol effects depend on the optical properties and the cloud-nucleating ability of individual particles, which, in turn, depend on the distribution of components among individual particles, termed the “aerosol mixing state.” Global models have moved toward including aerosol schemes to represent the evolution of particle characteristics, but individual particle properties cannot be resolved in global-scale simulations. Instead, models approximate the aerosol mixing state. The errors in climate-relevant aerosol properties introduced by such approximations may be large but have not yet been well quantified. This paper quantitatively addresses the question of to what extent the aerosol mixing state must be resolved to adequately represent the optical properties and cloud-nucleating properties of particle populations. Using a detailed benchmarking model to simulate gas condensation and particle coagulation, we show that, after the particles evolve in the atmosphere, simple mixing-state representations are sufficient for modeling cloud condensation nuclei concentrations, and we quantify the mixing time scale that characterizes this transformation. In contrast, a detailed representation of the mixing state is required to model aerosol light absorption, even for populations that are fully mixed with respect to their hygroscopic properties.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Laura Fierce, lfierce@bnl.gov

A supplement to this article is available online (10.1175/BAMS-D-16-0028.2).

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