Understanding how entrainment and mixing shape the cloud droplet size distribution (DSD) is crucial for understanding the optical properties and precipitation efficiency of clouds. Different mixing scenarios, mainly homogeneous and inhomogeneous, shape the DSD in a distinct way and alter the cloud’s impact on climate. However, the prevalence of these mixing scenarios and how they vary in space and time is still uncertain, as underlying processes are commonly unresolved by conventional numerical models. To overcome this challenge, we employ the $L^3$ model, which considers supersaturation fluctuations and turbulent mixing down to the finest relevant lengthscales, making it possible to represent different mixing scenarios realistically. We investigate the spatial and temporal evolution of mixing scenarios over the life cycle of shallow cumulus clouds for varying boundary layer humidities and aerosol concentrations. Our findings suggest homogeneous mixing is generally predominant in cumulus clouds, while different mixing scenarios occur concurrently in the same cloud. Notably, inhomogeneous mixing increases over the cloud life cycle across all analyzed cases. The mean and standard deviation of supersaturation are found to be the most capable indicators of this evolution, providing a comprehensive insight into the characteristics of mixing scenarios. Finally, we show inhomogeneous mixing is more prevalent in drier boundary layers and for higher aerosol concentrations, underscoring the need for a more comprehensive investigation of how these mixing dynamics evolve in a changing climate.

The small-scale mixing of clouds with their environment is an essential cloud process. Following an entrainment event, turbulent mixing breaks down the entrained air and homogenizes it with the cloud, covering multiple orders of magnitude in lengthscales from the entraining eddies (∼ 100 m) down to the Kolmogorov length (∼ 1 mm). The character of this process, traditionally categorized into homogeneous and inhomogeneous mixing scenarios, can affect the microphysical composition of clouds, with commensurate impacts on large-scale cloud properties such as the cloud albedo and cloud lifetime. Based on the current physical understanding of the small-scale mixing of cloudy and cloud-free air, this chapter will summarize the basic theories describing this process. By considering the wide range of involved scales, we will outline different observational and numerical approaches used to investigate this process in clouds, as well as methods to parameterize it in large-scale numerical models. Finally, we will review the impacts of the small-scale mixing process, focusing on microscale changes in the droplet size distribution as well as macroscale effects relevant to our understanding of clouds in the climate system.