Roles of Drop Size Distribution and Turbulence in Autoconversion Based on Lagrangian Cloud Model Simulations

Abstract

AbstractThe roles of the drop size distribution (DSD) and turbulence in the autoconversion rate A are investigated by analyzing Lagrangian cloud model (LCM) data for shallow cumulus clouds. The correlations of DSD and turbulence with other cloud parameters are estimated, and they are applied to parameterize their effects on A. A new parameterization of A based on this analysis is proposed: with , where is the cloud water mixing ratio, and are the number concentration and the volume mean radius of cloud droplets, is the dissipation rate, is the threshold value of , H is the Heaviside step function, and X, , and b are constants. Here, represents the effect of DSD via its correlation with and , while represents the effect of gravitational collisional growth for a given DSD and turbulence. The correlation between turbulence and DSD makes b larger than expected from turbulence‐induced collision enhancement only. The effects of DSD and turbulence and their correlations with and explain a wide range of exponent values of and in many existing parameterizations of A. The new parameterization is compared with the LCM data and applied to a bulk cloud model (BCM) while clarifying the difference between the cloud droplet mixing processes in the LCM and BCM. The importance of DSD and turbulence in raindrop formation in shallow cumulus clouds is shown by comparing the A results with and without these effects.