Understanding and Visualizing Droplet Distributions in Simulations of
  Shallow Clouds
Justus C. Will Andrea M. Jenney Kara D. Lamb Michael S. Pritchard Colleen Kaul Po-Lun Ma Kyle Pressel Jacob Shpund Marcus van Lier-Walqui Stephan Mandt
Thorough analysis of local droplet-level interactions is crucial to better
understand the microphysical processes in clouds and their effect on the global
climate. High-accuracy simulations of relevant droplet size distributions from
Large Eddy Simulations (LES) of bin microphysics challenge current analysis
techniques due to their high dimensionality involving three spatial dimensions,
time, and a continuous range of droplet sizes. Utilizing the compact latent
representations from Variational Autoencoders (VAEs), we produce novel and
intuitive visualizations for the organization of droplet sizes and their
evolution over time beyond what is possible with clustering techniques. This
greatly improves interpretation and allows us to examine aerosol-cloud
interactions by contrasting simulations with different aerosol concentrations.
We find that the evolution of the droplet spectrum is similar across aerosol
levels but occurs at different paces. This similarity suggests that
precipitation initiation processes are alike despite variations in onset times.