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<p>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.</p> <p>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.</p> <p>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<span class="inline-formula">⁻³</span>, 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.</p>