A model study of the effect of clustering on the last stage of drizzle formation

Abstract

In the final stage of growth, settling cloud drops become drizzle by collision and coalescence with the smaller droplets in their path. We study the impact of droplet clustering on the growth of settling collector drops by modelling it as an exponentially decaying correlation. Enhancement in collector drop growth is measured by the reduction in time needed for drizzle formation in the last stage. The effect of clustering is characterized by two dimensionless parameters C = δλL and K = (λ0L)−1, where δλ is the enhancement in the collision rate inside the clusters, L is the cluster size perceived by the settling collector drop and λ0 is the initial collision rate. Increasing C or K reduces the time needed for drizzle formation compared to the unclustered case. We find that for K ≥ 5, C ≤ 2 even a small increase in droplet concentration inside clusters can cause a significant enhancement in the collector drop growth. Further even for low turbulence intensities (low K) significant reduction in the time for drizzle formation is achieved for moderate values of C. These findings are relevant to the debate on the intensity of clustering needed to explain rapid drizzle formation.