Mixed-phase direct numerical simulation: ice growth in cloud-top generating cells

Abstract

In this study, a state-of-the-art microphysical model using a Lagrangian-particle-based direct numerical simulation framework is presented to examine the growth of ice particles in turbulent mixed-phase clouds. By tracking the interactions between individual ice, droplets, and turbulence at the native scales, the model offers new insights into the microphysical processes taking place in mixed-phase clouds at sub-meter-length scales. This paper examines the conditions that favor effective ice growth in the cloud-top generating cells (GCs), which are small regions of enhanced radar reflectivity near cloud tops. GCs are commonly observed in many types of mixed-phase clouds and play a critical role in producing precipitation from rain or snow. Investigations over a range of environmental (macrophysical and turbulent) and microphysical conditions (ice number concentrations) that distinguish GCs from their surrounding cloudy air were conducted. Results show that high liquid water content (LWC) or high relative humidity (RH) is critical for effective ice growth and the maintenance of mixed-phase conditions. As a result, GCs with high LWC and high RH provide favorable conditions for rapid ice growth. When the ice number concentration is below 1 cm−3, which is typical in mixed-phase clouds, a high LWC is needed for the formation of large ice particles. The study also found that supersaturation fluctuations induced by small-scale turbulent mixing have a negligible effect on the mean particle radius, but they can substantially broaden the size spectra, affecting the subsequent collection process.