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Evaluating Boundary Layer–Based Mass Flux Closures Using Cloud-Resolving Model Simulations of Deep Convection

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  • 1 University of Washington, Seattle, Washington
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Abstract

High-resolution three-dimensional cloud resolving model simulations of deep cumulus convection under a wide range of large-scale forcings are used to evaluate a mass flux closure based on boundary layer convective inhibition (CIN) that has previously been applied in parameterizations of shallow cumulus convection. With minor modifications, it is also found to perform well for deep oceanic and continental cumulus convection, and it matches simulated cloud-base mass flux much better than a closure based only on the boundary layer convective velocity scale. CIN closure maintains an important feedback among cumulus base mass flux, compensating subsidence, and CIN that keeps the boundary layer top close to cloud base. For deep convection, the proposed CIN closure requires prediction of a boundary layer mean turbulent kinetic energy (TKE) and a horizontal moisture variance, both of which are strongly correlated with precipitation. For our cases, CIN closure predicts cloud-base mass flux in deep convective environments as well as the best possible bulk entraining CAPE closure, but unlike the latter, CIN closure also works well for shallow cumulus convection without retuning of parameters.

Corresponding author address: Jennifer Fletcher, University of Washington, 408 ATG Bldg., Seattle, WA 98195–1640. Email: jkf@atmos.washington.edu

Abstract

High-resolution three-dimensional cloud resolving model simulations of deep cumulus convection under a wide range of large-scale forcings are used to evaluate a mass flux closure based on boundary layer convective inhibition (CIN) that has previously been applied in parameterizations of shallow cumulus convection. With minor modifications, it is also found to perform well for deep oceanic and continental cumulus convection, and it matches simulated cloud-base mass flux much better than a closure based only on the boundary layer convective velocity scale. CIN closure maintains an important feedback among cumulus base mass flux, compensating subsidence, and CIN that keeps the boundary layer top close to cloud base. For deep convection, the proposed CIN closure requires prediction of a boundary layer mean turbulent kinetic energy (TKE) and a horizontal moisture variance, both of which are strongly correlated with precipitation. For our cases, CIN closure predicts cloud-base mass flux in deep convective environments as well as the best possible bulk entraining CAPE closure, but unlike the latter, CIN closure also works well for shallow cumulus convection without retuning of parameters.

Corresponding author address: Jennifer Fletcher, University of Washington, 408 ATG Bldg., Seattle, WA 98195–1640. Email: jkf@atmos.washington.edu

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