Aerosol-cloud-precipitation interactions in deep convective clouds are investigated through numerical simulations of a heavy precipitation event over South Korea on 15–16 July 2017. The Weather Research and Forecasting model with a bin microphysics scheme is used, and various aerosol number concentrations in the range N0 = 50–12,800 cm−3 are considered. Precipitation amount changes non-monotonically with increasing aerosol loading, with a maximum near a moderate aerosol loading (N0 = 800 cm−3). Up to this optimal value, an increase in aerosol number concentration results in a greater quantity of small droplets formed by nucleation, increasing the number of ice crystals. Ice crystals grow into snow particles through deposition and riming, leading to enhanced melting and precipitation. Beyond the optimal value, a greater aerosol loading enhances generation of ice crystals while the overall growth of ice hydrometeors through deposition stagnates. Subsequently, the riming rate decreases because of the smaller size of snow particles and supercooled drops, leading to a decrease in ice melting and a slight suppression of precipitation. As aerosol loading increases, cold pool and low-level convergence strengthen monotonically, but cloud development is more strongly affected by latent heating and convection within the system that is non-monotonically reinforced.

The evolution of cloud drop size distribution due to the collision‐coalescence process is generally described by a quasi‐stochastic model that solves the stochastic collection equation in a deterministic way. In this study, an improved quasi‐stochastic (IQS) model, which is derived by rigorously considering a finite model time step, is examined in the context of comparison with the normal quasi‐stochastic (NQS) model. The IQS model allows a large collector drop to collide with a small collected drop more than one time in a model time step even if the collision probability is small. The number distribution of collector drops then follows the Poisson distribution with respect to the number of collisions. Using a box model that takes turbulence‐induced collision enhancement into account, it is found that large drops in the IQS model tend to have larger sizes than those in the NQS model and that the IQS model accelerates large‐drop formation by a few minutes compared to the NQS model. The effects of the IQS model depend on the model time step and the shape of initial drop size distribution. The IQS model is incorporated into a detailed bin microphysics scheme that is coupled with the Weather Research and Forecasting model, and a single warm cloud is simulated under idealized environmental conditions. It is found that the onset of surface precipitation is accelerated in the IQS model.

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