the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Influence of common assumptions regarding aerosol composition and mixing state on predicted CCN concentration
Manasi Mahish
Anne Jefferson
Don Collins
Abstract. A 4-year record of aerosol size and hygroscopic growth factor distributions measured at the Department of Energy’s SGP ARM site in Oklahoma, U.S. were used to estimate supersaturation (S)-dependent cloud condensation nuclei concentrations (NCCN). Baseline or reference NCCN(S) spectra were estimated by using the data to create a matrix of size- and hygroscopicity-dependent number concentration (N) and then integrating for S > critical supersaturation (Sc) calculated for the same size and hygroscopicity pairs using κ-Köhler Theory. The accuracy of those estimates was assessed through comparison with the directly measured NCCN at the same site. Subsequently, NCCN was calculated using the same dataset but with an array of simplified treatments in which the aerosol was assumed to be either an internal or an external mixture and the hygroscopicity either assumed or based on averages derived from the growth factor distributions. The CCN spectra calculated using the simplified treatments were compared with those from the baseline approach to evaluate the impact of commonly used approximations. Among the simplified approaches, assuming the aerosol is an internal mixture with size-dependent hygroscopicity parameter (κ) resulted in estimates closest to those from the baseline approach over the range in S considered.
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Manasi Mahish et al.
Interactive discussion


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RC1: 'Manuscript Review', Anonymous Referee #1, 20 Jul 2017
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AC1: 'Response to first anonymous reviewer', Manasi Mahish, 26 Jul 2017
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AC1: 'Response to first anonymous reviewer', Manasi Mahish, 26 Jul 2017
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RC2: 'review', Anonymous Referee #2, 29 Aug 2017
Interactive discussion


-
RC1: 'Manuscript Review', Anonymous Referee #1, 20 Jul 2017
-
AC1: 'Response to first anonymous reviewer', Manasi Mahish, 26 Jul 2017
-
AC1: 'Response to first anonymous reviewer', Manasi Mahish, 26 Jul 2017
-
RC2: 'review', Anonymous Referee #2, 29 Aug 2017
Manasi Mahish et al.
Manasi Mahish et al.
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