Metrics to quantify the importance of mixing state for CCN activity

Ping Pui CHING, Jerome FAST, Matthew WEST, Nicole RIEMER

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29 Citations (Scopus)

Abstract

It is commonly assumed that models are more prone to errors in predicted cloud condensation nuclei (CCN) concentrations when the aerosol populations are externally mixed. In this work we investigate this assumption by using the mixing state index (χ) proposed by Riemer and West (2013) to quantify the degree of external and internal mixing of aerosol populations. We combine this metric with particle-resolved model simulations to quantify error in CCN predictions when mixing state information is neglected, exploring a range of scenarios that cover different conditions of aerosol aging. We show that mixing state information does indeed become unimportant for more internally mixed populations, more precisely for populations with χ larger than 75%. For more externally mixed populations (χ below 20%) the relationship of χ and the error in CCN predictions is not unique and ranges from lower than -40% to about 150%, depending on the underlying aerosol population and the environmental supersaturation. We explain the reasons for this behavior with detailed process analyses. Copyright © 2017 Author(s).

Original languageEnglish
Pages (from-to)7445-7458
JournalAtmospheric Chemistry and Physics
Volume17
Issue number12
DOIs
Publication statusPublished - Jun 2017

Citation

Ching, J., Fast, J., West, M., & Riemer, N. (2017). Metrics to quantify the importance of mixing state for CCN activity. Atmospheric Chemistry and Physics, 17(12), 7445-7458. https://doi.org/10.5194/acp-17-7445-2017

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