From Clouds to Precipitation: Multiscale Dynamics-Microphysics Interactions in Cumulus Clouds

Abstract

Microphysical processes leading to the formation of drizzle and rain in warm (ice-free) cumulus clouds are still not well understood, and their representation is a key uncertainty in climate models. From a theoretical point of view, cloud droplets can grow by water vapor diffusion only to sizes where collisional growth is still inefficient. This is often referred to as the condensation-coalescence bottleneck, between approximately 15 and 40 microns in droplet radius. In this project, we will apply theory, observations, and numerical modeling to study processes occurring in natural clouds that push droplets through the condensation-coalescence bottleneck.

We will use in-situ high- resolution observations from recent Atmospheric Radiation Measurement airborne field campaigns targeting convective clouds. The focus will be on droplet spectral width and its relationship to cloud parameters (e.g., mean radius, adiabatic fraction, local turbulence intensity, and presence or absence of droplets in the bottleneck size range, as well as the spatial variability of these parameters along-the-flight-path vicinity of the observation location) and environmental conditions (location in cloud, vertical velocity, synoptic conditions and origins of air masses). We will also combine high-resolution droplet spectral information with scale-dependent estimates of the vertical velocity fluctuations derived from the turbulent kinetic energy and aircraft gust probe data to provide for the first time estimates of the supersaturation fluctuation at scales of meters to tens of meters within convective clouds. These fluctuations have been argued in the past to play a critical role in the evolution of the droplet spectra.

On the modeling side we will apply a novel Lagrangian modeling approach referred to as the “super-droplet method” that allows unprecedented fidelity for simulating cloud microphysics. This novel approach mitigates numerical problems facing traditional Eulerian bin microphysics that lead to artificial droplet spectral broadening. Moreover, the Lagrangian approach allows truly multiscale cloud simulations by incorporating a physically-based stochastic subgrid-scale droplet growth scheme. These simulations will employ the Weather Research and Forecasting model in large eddy simulation mode with environmental conditions obtained from field observations. Statistical techniques developed with our previous funding will be used to evaluate model simulations with the observational data.