Analysis of Self-Organization in Shallow Cumulus Using a Simple Cloud Model

The organization of shallow cumulus continues to be a complex and not-well-understood process. In order to focus on the internal physics and local processes behind pattern formation, we have developed a simple cloud model based on predator-prey-like dynamics using a system of four nonlinear partial differential equations. In this model, cloud water and cloud drop number concentration represent the “prey” while rain water represents the “predator”. Feedbacks exist via vertical velocity and virga. These simple cloud models are coupled across a horizontal grid, in which the vertical motions force horizontal circulations and further feedbacks that result in recognizable patterns in the maritime trades. This coupled system is capable of simulating three of these common patterns: sugar, the small and randomly dispersed cumulus with little precipitation; gravel, small cumulus with frequent precipitation most associated with an open cell structure; and flowers, large clusters of cumulus surrounded by clear air. We find that clouds begin to cluster as the environment grows more stable, the boundary layer deepens, latent heating increases, and clouds more strongly interact with their neighbors. We will discuss how these external factors generate the circulations and patterns and compare with both observed data and large eddy simulations to gain a deeper understanding of the circulations driving this clustering effect.