Abstract
We study entrainment in dry thermals in neutrally and unstably stratified ambients, and moist thermals in dry-neutrally stratified ambients using direct numerical simulations. We find, in agreement with results of Lecoanet and Jeevanjee [J. Atmos. Sci. 76, 3785 (2019)], that turbulence plays a minor role in entrainment in dry thermals in a neutral ambient for Reynolds numbers . We then show that the net entrainment rate increases when the buoyancy of the thermals increases, either by condensation heating or because of an unstably stratified ambient. This is in contrast with the findings of Morrison et al. [J. Atmos. Sci. 78, 797 (2021)]. We also show that the role of turbulence is greater in these cases than in dry thermals and, significantly, that the combined action of condensation heating and turbulence creates intense small-scale vorticity, destroying the coherent vortex ring that is seen in dry and moist laminar thermals. These findings suggest that fully resolved simulations at Reynolds numbers significantly larger than the mixing transition Reynolds number are necessary to understand the role of turbulence in the entrainment in growing cumulus clouds, which consist of a series of thermals rising and decaying in succession.
12 More- Received 2 August 2021
- Accepted 20 April 2022
DOI:https://doi.org/10.1103/PhysRevFluids.7.050501
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by Bibsam.
Published by the American Physical Society
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Cloud Physics Invited Papers
Physical Review Fluids publishes a collection of papers associated with invited talks presented at the mini-symposium on the Cloud Physics at the 73rd Annual Meeting of the APS Division of Fluid Dynamics.
synopsis
Fluid Dynamics of Clouds
Published 17 May 2022
In a series of invited papers, researchers discuss new tools for reducing uncertainties in climate models associated with cloud formation and transport.
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