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It is commonly assumed that models are more prone to errors in predictedcloud condensation nuclei (CCN) concentrations when the aerosol populationsare externally mixed. In this work we investigate this assumption by usingthe mixing state index (χ) proposed by Riemer and West (2013) to quantifythe degree of external and internal mixing of aerosol populations. We combinethis metric with particle-resolved model simulations to quantify error in CCNpredictions when mixing state information is neglected, exploring a range ofscenarios that cover different conditions of aerosol aging. We show thatmixing state information does indeed become unimportant for more internallymixed populations, more precisely for populations with χ larger than75 %. For more externally mixed populations (χ below 20 %) therelationship of χ and the error in CCN predictions is not unique andranges from lower than −40 % to about 150 %, depending on theunderlying aerosol population and the environmental supersaturation. Weexplain the reasons for this behavior with detailed process analyses

Metrics to quantify the importance of mixing state for CCN activity