10.2 Simulation of Stratocumulus and Deep Convective Clouds with the Dynamic Reconstruction Turbulence Closure

Wednesday, 26 July 2017: 10:45 AM
Coral Reef Harbor (Crowne Plaza San Diego)
Xiaoming Shi, University of California, Berkeley, CA; and F. K. Chow, R. L. Street, and G. H. Bryan
Manuscript (2.6 MB)

Large-eddy simulation (LES) is an essential tool in reducing uncertainty in cloud processes needed by global climate models. Here the effects of sub-filter scale (SFS) turbulence closure schemes on LES of clouds are evaluated by comparing three different closures, including the traditional Smagorinsky model, Deardorff-type TKE models, and the dynamic reconstruction model (DRM).

Two cloud regimes are considered -- a stratocumulus-topped boundary layer under sharp inversion, and deep tropical convection. In the stratocumulus regime, DRM maintains significantly more cloud water than the traditional turbulence models, keeping the boundary layer well mixed and coupled in the vertical. These features of DRM persist even when the resolution of simulations fall into the so-called 'terra-incognita' of numerical simulations. In the tropical convection case, DRM produces more deep updraft cores and therefore more precipitation than other turbulence models. The strongest convective core in the simulation using DRM can penetrate the tropopause and reach a height of about 16km, while other turbulence models do not produce such intense convection.

Differing from traditional turbulence models, DRM partitions SFS turbulence into resolvable sub-filter scales and unresolved sub-grid scales. The former are reconstructed, and the latter modeled. The main difference between DRM and traditional models lies in DRM's reconstruction part that can represent backscatter of energy by producing counter-gradient fluxes/stresses, i.e. the transfer of energy from the small subfilter scales to the resolved scales, which are not included in traditional eddy viscosity models.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner