Andrea M. Jenney | Searcharxiv

arXiv2023

Understanding and Visualizing Droplet Distributions in Simulations of Shallow Clouds

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.

cs.LG↗

arXiv2023

Improving stratocumulus cloud amounts in a 200-m resolution multi-scale modeling framework through tuning of its interior physics

High-Resolution Multi-scale Modeling Frameworks (HR) -- global climate models that embed separate, convection-resolving models with high enough resolution to resolve boundary layer eddies -- have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over-entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present-day climate, limiting their scientific utility. We report new results showing that this over-entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small-scale momentum fluctuations associated with the formulation of the momentum solver of the embedded LES. By considering the sedimentation process adjacent to default one-moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that is able to produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub-cloud eddy spectrum are observed. We report these sensitivities in multi-week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5 degree exterior resolution. The result is a new HR having desired improvements in the baseline present-day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation.

physics.ao-ph↗