Kinematic and dynamic pair collision statistics of sedimenting inertial particles relevant to warm rain initiation

Abstract

In recent years, direct numerical simulation (DNS) approach has become a reliable tool for studying turbulent collision-coalescence of cloud droplets relevant to warm rain development. It has been shown that small-scale turbulent motion can enhance the collision rate of droplets by either enhancing the relative velocity and collision efficiency or by inertia-induced droplet clustering. A hybrid DNS approach incorporating DNS of air turbulence, disturbance flows due to droplets, and droplet equation of motion has been developed to quantify these effects of air turbulence. Due to the computational complexity of the approach, a major challenge is to increase the range of scales or size of the computation domain so that all scales affecting droplet pair statistics are simulated. Here we discuss our on-going work in this direction by improving the parallel scalability of the code, and by studying the effect of large-scale forcing on pair statistics relevant to turbulent collision. New results at higher grid resolutions show a saturation of pair and collision statistics with increasing flow Reynolds number, for given Kolmogorov scales and small droplet sizes. Furthermore, we examine the orientation dependence of pair statistics which reflects an interesting coupling of gravity and droplet clustering.