Preprints
https://doi.org/10.5194/egusphere-2022-1142
https://doi.org/10.5194/egusphere-2022-1142
 
01 Nov 2022
01 Nov 2022
Status: this preprint is open for discussion.

Mixed-phase Direct Numerical Simulation: Ice Growth in Cloud-Top Generating Cells

Sisi Chen1, Lulin Xue1, Sarah Tessendorf1, Kyoko Ikeda1, Courtney Weeks1, Roy Rasmussen1, Melvin Kunkel2, Derek Blestrud2, Shaun Parkinson2, Melinda Meadows2, and Nick Dawson2 Sisi Chen et al.
  • 1National Center for Atmospheric Research (NCAR), Boulder, CO
  • 2Idaho Power Company, Boise, ID

Abstract. A detailed microphysical model is developed using a Lagrangian-particle-based direct numerical simulation framework to simulate ice growth in a turbulent mixed-phase environment. The Lagrangian particle method is employed to track the interactions between ice, droplets, and turbulence at the native scales. The investigation reveals for the first time the mixed-phase processes at the sub-meter length scales using direct numerical simulation.

This paper examines the conditions that favor effective ice growth in the cloud top generating cells. Investigations over a range of environmental (macrophysical and turbulent) and microphysical conditions (ice number concentrations) that distinguish generating cells from their surrounding cloudy air were conducted. Results show that high liquid water content (LWC) or high relative humidity (RH) is critical to maintaining effective ice growth and mixed-phase. As a result, generating cells with high LWC and high RH provide favorable conditions for rapid ice growth. Sensitivity studies on ice number concentrations show that when the ice number concentration is below 1 cm-3, a typical range in the mixed-phase clouds, a high LWC is needed for efficient formation of big ice particles. The study also found that supersaturation fluctuations due to small-scale turbulent mixing have a negligible effect on the particle mean radius but substantially broaden the size spectra which can affect the subsequent collection process.

Sisi Chen et al.

Status: open (until 24 Dec 2022)

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  • RC1: 'Comment on egusphere-2022-1142', Anonymous Referee #1, 25 Nov 2022 reply

Sisi Chen et al.

Data sets

Replication Data for "Mixed-phase Direct Numerical Simulation: Ice Growth in Cloud-Top Generating Cells" Sisi Chen https://doi.org/10.7910/DVN/BKYGWW

Sisi Chen et al.

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Short summary
The possible mechanism of effective ice growth in the cloud-top generating cells in winter orographic clouds is explored using a newly developed ultra-high-resolution cloud microphysics model. Simulations demonstrate that a high availability of moisture and liquid water are critical to producing large ice particles. Fluctuations in temperature and moisture down to millimeter scales due to cloud turbulence can substantially affect the growth history of the individual cloud particles.