Broadening of Cloud Droplet Spectra through Eddy Hopping: Turbulent Entraining Parcel Simulations

• Published in: Journal of the atmospheric sciences Vol. 75; no. 10; pp. 3365 - 3379
• Main Authors: Abade, Gustavo C., Grabowski, Wojciech W., Pawlowska, Hanna
• Format: Journal Article
• Language: English
• Published: Boston American Meteorological Society 01.10.2018
• Subjects: Aerodynamics; aerosol indirect effect; aerosol nucleation; Air; Air entrainment; Cloud condensation nuclei; Cloud droplet size; Cloud droplet spectra; Cloud droplets; Cloud microphysics; Clouds; Condensation; Condensation nuclei; cumulus clouds; Droplets; Dry air; Eddies; Entrainment; ENVIRONMENTAL SCIENCES; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Investigations; Large eddy simulation; Large eddy simulations; meteorology & atmospheric sciences; Microphysics; Oceanic eddies; Particle size distribution; Random processes; Random variables; Simulation; Size distribution; Spectra; Statistical methods; stochastic models; subgrid-scale processes; Supersaturation; Turbulence; Turbulence intensity; Turbulent entrainment; Turbulent mixing; Vortices
• DOI: 10.1175/JAS-D-18-0078.1
• ISSN: 0022-4928

This paper discusses the effects of cloud turbulence, turbulent entrainment, and entrained cloud condensation nuclei (CCN) activation on the evolution of the cloud droplet size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events modeled as a random process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet activation and growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate, CCN concentration, and the mean fraction of environmental air entrained in an event are all specified as independent external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. These are either unactivated CCN or cloud droplets that grow from activated CCN. The model accounts for the addition of environmental CCN into the cloud by entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using the classical linear relaxation to the mean model. We show that turbulence plays an important role in aiding entrained CCN to activate, and thus broadening the droplet size distribution. These findings are consistent with previous large-eddy simulations (LESs) that consider the impact of variable droplet growth histories on the droplet size spectra in small cumuli. The scheme developed in this work is ready to be used as a stochastic subgrid-scale scheme in LESs of natural clouds.