Lagrangian Particle–Based Simulation of Aerosol-Dependent Vertical Variation of Cloud Microphysics in a Laboratory Convection Cloud Chamber
Abstract. We investigate the vertical variability of cloud microphysics in a turbulent convection cloud chamber through large-eddy simulations coupled with a Lagrangian super-droplet (SD) model. Numerical experiments mimic the convection chamber under construction at the Korea Institute of Science and Technology (KIST), employing realistic aerosol size distributions derived from field measurements (VOCALS campaign and Seoul, South Korea). Simulations show that cloud water mixing ratio generally increases with altitude due to continuous droplet activation and growth during ascent, but this vertical gradient weakens significantly as aerosol concentration increases. Enhanced aerosol loading intensifies competition for water vapor, shortening phase relaxation times and suppressing supersaturation variability, resulting in more vertically uniform cloud water mixing ratio profiles. Lagrangian trajectory analyses reveal that upward motion substantially influences droplet growth and activation under clean conditions, but this influence diminishes sharply in polluted environments where rapid vapor depletion limits supersaturation buildup. Furthermore, droplets experiencing sustained upward motion activate more readily, although this effect is weakened considerably in polluted conditions. In a turbulent convection-chamber setting, we quantify how aerosol loading modulates the vertical distribution of cloud-water mixing ratio using LES model with Lagrangian super-droplet tracking, thereby clarifying the coupled roles of vapor competition and vertical transport. Our results emphasize the critical role of aerosol loading in shaping vertical microphysical structures and highlight the interplay between vapor competition and vertical dynamics. These findings provide important insights for improving cloud parameterizations and understanding aerosol-cloud interactions in both controlled laboratory and atmospheric contexts.