A numerical study of aerosol effects on cloud microphysical processes of hailstorm clouds

Abstract

The Regional Atmospheric Modeling System (RAMS) was used to investigate the effects of varied cloud condensation nuclei (CCN) concentrations on microphysical processes of spring hailstorm clouds in a semiarid region of China. The comparison between the model analyses and the observations reveals that the simulation generally performed well in forecasting the precipitation, the pressure field, and the radar reflectivity. The simulation result shows that the variation of aerosol concentrations had significant effects on the cloud microphysical processes, as well as on hail precipitation at the surface. As CCN concentrations increased, mixing ratios of small liquid particles (i.e., cloud1) increased, while that of large liquid particles (i.e., cloud2 and rain) decreased; mixing ratios of small ice-phase particles (i.e., pristine ice and snow) decreased, while that of the large ice-phase hydrometeor particles (i.e., aggregates and graupel) increased. The number concentration, mixing ratio, and melting mixing ratio of hail tended to decrease, but the mean diameter of hail increased with greater CCN concentrations. The surface precipitation of hail in polluted clouds was greater than that in clean clouds and heavily polluted clouds. In this simulation, the relative contributions of hydrometeor particles to hail varied with different CCN backgrounds. Higher CCN concentrations resulted in the decrease in the contribution of cloud1 to hail formation, while aggregates made more of a contribution to hail generation. The addition of CCN concentrations led to the decrease of total surface accumulated precipitation. However, the contribution of ice-phase precipitation to the total precipitation increased with greater CCN concentrations.