PNNL

Abstract

In numerical weather prediction and climate models, boundary-layer clouds are controlled by a wide range of subgrid-scale processes. However, understanding the nature of these processes and their role in the evolution of the cloud size distribution as a whole has been elusive. To address this issue, we adopt a novel empirical framework from the field of population dynamics to model the evolution of cloud size statistics by using the shallow cumulus properties obtained from a large-eddy simulations (LES). Our approach involves representing the cloud size distribution and total cloudy area using a revised Lotka-Volterra model and ridge linear model, respectively. The physical interpretation of the coefficients obtained from the optimization of the models reveals three distinct stages characterized by the dominant processes: the formation of new clouds, single-cloud growth, and a steady state with organized transitions involving the growth and decay of multiple clouds. Furthermore, we showcase the potential of this framework to serve as a component of scale-aware parameterizations of shallow-convective clouds in atmospheric models.