Parameterization of cloud droplet size distributions: Comparison with parcel models and observations

This work examines the efficacy of various physically based approaches derived from one-dimensional adiabatic parcel model frameworks (a numerical model and a simplified parameterization) to parameterize the cloud droplet distribution characteristics for computing cloud effective radius and autoconversion rate in regional/global atmospheric models. Evaluations are carried out for integrations with single (average) and distributions of updraft velocity, assuming that (1) conditions at s_(max) are reflective of the cloud column or (2) cloud properties vary vertically, in agreement with one-dimensional parcel theory. The predicted droplet distributions are then compared against in situ cloud droplet observations obtained during the CRYSTAL-FACE and CSTRIPE missions. Good agreement of droplet relative dispersion between parcel model frameworks indicates that the parameterized parcel model essentially captures one-dimensional dynamics; the predicted distributions are overly narrow, with relative dispersion being a factor of 2 lower than observations. However, if conditions at cloud maximum supersaturation are used to predict relative dispersion and applied throughout the cloud column, better agreement is seen with observations, especially if integrations are carried out over the distribution of updraft velocity. When considering the efficiency of the method, calculating cloud droplet spectral dispersion at s_(max) is preferred for linking aerosol with droplet distributions in large-scale models.