A Generalized Mixing Length Closure for Eddy-Diffusivity Mass-Flux Schemes of Turbulence and Convection
Abstract
Because of their limited spatial resolution, numerical weather prediction and climate models have to rely on parameterizations to represent atmospheric turbulence and convection. Historically, largely independent approaches have been used to represent boundary layer turbulence and convection, neglecting important interactions at the subgrid scale. Here we build on an eddy‐diffusivity mass‐flux (EDMF) scheme that represents all subgrid‐scale mixing in a unified manner, partitioning subgrid‐scale fluctuations into contributions from local diffusive mixing and coherent advective structures and allowing them to interact within a single framework. The EDMF scheme requires closures for the interaction between the turbulent environment and the plumes and for local mixing. A second‐order equation for turbulence kinetic energy (TKE) provides one ingredient for the diffusive local mixing closure, leaving a mixing length to be parameterized. Here, we propose a new mixing length formulation, based on constraints derived from the TKE balance. It expresses local mixing in terms of the same physical processes in all regimes of boundary layer flow. The formulation is tested at a range of resolutions and across a wide range of boundary layer regimes, including a stably stratified boundary layer, a stratocumulus‐topped marine boundary layer, and dry convection. Comparison with large eddy simulations (LES) shows that the EDMF scheme with this diffusive mixing parameterization accurately captures the structure of the boundary layer and clouds in all cases considered.
Additional Information
© 2020 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Issue Online: 29 October 2020; Version of Record online: 29 October 2020; Accepted manuscript online: 14 October 2020; Manuscript accepted: 07 October 2020; Manuscript revised: 02 September 2020; Manuscript received: 01 May 2020. This research was made possible by the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program, by Earthrise Alliance, Mountain Philanthropies, the Paul G. Allen Family Foundation, and the National Science Foundation (NSF, Award AGS1835860)). I. L. would like to thank the Resnick Sustainability Institute at Caltech for fellowship support. Parts of the research were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration and funded through the Internal Research and Technology Development Program. We thank Gregory L. Wagner and two anonymous reviewers for helpful comments on an earlier version of this paper. © 2020. California Institute of Technology. Government sponsorship acknowledged. Data Availability Statement: The PyCLES code used to generate LES results is available online (climate‐dynamics.org/software/#pycles). The SCM code is available at https://doi.org/10.5281/zenodo.3789011 website. All LES and SCM data are publicly available online (https://doi.org/10.5281/zenodo.3996252).Attached Files
Published - 2020MS002161.pdf
Submitted - essoar.10502906.1.pdf
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Additional details
- Eprint ID
- 106101
- Resolver ID
- CaltechAUTHORS:20201015-152734310
- Schmidt Futures Program
- Earthrise Alliance
- Mountain Philanthropies
- Paul G. Allen Family Foundation
- NSF
- AGS-1835860
- Resnick Sustainability Institute
- NASA/JPL/Caltech
- Created
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2020-10-16Created from EPrint's datestamp field
- Updated
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2023-06-01Created from EPrint's last_modified field
- Caltech groups
- Resnick Sustainability Institute, Division of Geological and Planetary Sciences