Abstract
Computational fluid dynamics (CFD) is an effective technique for investigating atmospheric processes at a local scale. For example, in near-source atmospheric dispersion applications, the effects of meteorology, air-pollutant sources, and buildings can be included. A prerequisite is to establish realistic atmospheric conditions throughout the computational domain. This work investigates the modeling of the atmospheric surface layer under neutral and stable boundary-layer conditions, respectively. Steady-state numerical solutions of the Reynolds averaged Navier–Stokes equations were used, including the k-ε turbulence model. Atmospheric profiles derived from the Cooperative Atmosphere–Surface Exchange Study-99 (Kansas, USA) were used as reference data. The results indicate that the observed profiles of velocity and potential temperature can be reproduced with CFD, while turbulent kinetic energy showed less agreement with the observations. For the stable boundary layer, reasonable agreement of the numerical results with the observations was also obtained for surface layer depth, shear stress, and heat-flux profiles, respectively. The results are discussed in relation to the boundary conditions and sources, and the observation data.
Highlights
Computational fluid dynamics (CFD) is an effective technique for investigating atmospheric processes at a local scale
This work investigated the modeling of the atmospheric surface layer (ASL) under neutral and stable boundary layer conditions, respectively
The ASL is the turbulent layer most affected by the surface, and fluxes of heat and momentum may be assumed to be almost constant in the ASL
Summary
Computational fluid dynamics (CFD) is an effective technique for investigating atmospheric processes at a local scale. In near-source atmospheric dispersion applications, the effects of meteorology, air-pollutant sources, and buildings can be included. A prerequisite is to establish realistic atmospheric conditions throughout the computational domain. This work investigated the modeling of the atmospheric surface layer (ASL) under neutral and stable boundary layer conditions, respectively. The ASL can be simplistically defined as the bottom 10% of the atmospheric boundary layer [1]. The ASL is the turbulent layer most affected by the surface, and fluxes of heat and momentum may be assumed to be almost constant in the ASL
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