Abstract

The goal of this work is to answer the question of whether nonuniformity in the spatial distribution of sizes and positions of cloud droplets and/or variable vertical velocity in a turbulent medium can contribute to the broadening of the droplet size distribution. A numerical approach to simulate the growth and trajectory of several tens of thousands of cloud droplets in a turbulent environment whose properties vary from droplet to droplet is used. The finite inertia of particles in a turbulent fluid causes particles to diverge from regions of high vorticity and to converge preferentially in regions of low vorticity, thus creating strong deviations in particle concentration. As a first step, the inertia effect was examined in the context of nongrowing, sedimenting, or nonsedimenting droplets. It was found that statistically significant preferential concentration is possible in conditions typical of cloud droplets in cumulus clouds. In the absence of sedimentation, preferential concentration increases as a function of the Stokes number St. Allowing the droplets to sediment decreases preferential concentration to a degree that increases with the velocity ratio Sυ. A series of experiments including condensational growth of droplets was then performed. It was found that while the increasing preferential concentration of droplets, as a result of increasing eddy dissipation rate, does result in increases in the instantaneous dispersion of the supersaturation perturbation distribution, the width of the size distribution of droplets, which is a function of the dispersion in the time integral of the supersaturation perturbations, decreases. This result is a consequence of the decrease in decorrelation time of the supersaturation perturbations as the turbulence intensity increases. Comparison of the results herein with the observations made in quasi-adiabatic cloud cores leads one to the conclusion that the microscopic approach, even under the most favorable condition of no turbulence, produces too little broadening to explain the observations.

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