Abstract

We present a new diagnostic mixing length for a turbulence scheme based on a prognostic equation for the turbulence kinetic energy. The formulation adds a local vertical wind shear term to the non-local buoyancy-based mixing length currently used in the research mesoscale model Meso-NH. The combined effects better represent local mixing for stably stratified flows where the wind shear plays a major role. The proposed formulation is directly evaluated in large-eddy simulations of stable, neutral, and unstable atmospheres. It is tested in single-column simulations with different length scale formulations and compared to large-eddy simulations. Idealized cases with varying surface cooling rates and different prescribed geostrophic winds are used to evaluate the impact of the new model on the stable boundary layer. The model reduces the over-diffusion typically occuring in modeling the stable boundary layer and shows better performance in terms of the turbulent mixing, the temperature inversion, and the boundary-layer and low-level jet heights compared to large-eddy simulations. A slight improvement of the turbulence intensity is shown for convective boundary layers.

Highlights

  • Stable boundary layer (SBL) modeling in numerical weather prediction (NWP) models plays a major role in terms of the predictability of the minimal temperature, surface frost, dew, fog, and low-level jet (LLJ)

  • Over the last decade, such model intercomparisons have been investigated at an international scale within the Global Energy and Water Exchanges (GEWEX) Atmospheric Boundary Layer Study (GABLS, Holtslag, 2006) for weakly stable boundary layer (WSBL) (Cuxart et al, 2006; Svensson et al, 2011; Bosveld et al, 2014)

  • The additional shear length scale allowed to reduce the over-mixing of a buoyancy-based formulation in the z-less regime of the very stable regime (VSBL) compared to an improved Prandtl model for a katabatic flow (Grisogono and Belušic, 2008; Grisogono, 2010)

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Summary

Introduction

Stable boundary layer (SBL) modeling in numerical weather prediction (NWP) models plays a major role in terms of the predictability of the minimal temperature, surface frost, dew, fog, and low-level jet (LLJ). The prediction of these features is required in sectors such as air quality (Weil, 2012), air and road traffic, agriculture, and wind farming (Hansen et al, 2012). In the very stable regime (VSBL), the turbulence is relatively weak and globally intermittent associated with weak winds This division is not completed and oversimplified (Mahrt, 1998), a unique classification is not yet formulated (e.g., Van de Wiel et al, 2003; Banta, 2008; Mahrt, 2014)

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