Dispersion of a Passive Tracer in Buoyancy- and Shear-Driven Boundary Layers

Abstract

By means of finescale modeling [large-eddy simulation (LES)], the combined effect of thermal and mechanical forcing on the dispersion of a plume in a convective boundary layer is investigated. Dispersion of a passive tracer is studied in various atmospheric turbulent flows, from pure convective to almost neutral, classified according to the scaling parameters u?/w? and ?zi/L. The LES results for the flow statistics and dispersion characteristics are first validated for pure convective cases against the available results from laboratory and field experiments. Currently used parameterizations are evaluated with the model results. The effect of wind shear is studied by analyzing the dynamic variables, in particular the velocity variances, and their relation with the dispersion characteristics, specifically plume mean height, dispersion parameters, ground concentrations, and concentration fluctuations. The main effect of the wind shear results in a reduction of the vertical spread and an enhancement of the horizontal dispersion. This effect greatly influences the behavior of the ground concentrations because the tracer is transported by the wind for a longer time before reaching the ground. The vertical dispersion parameter is studied by discussing the two main components: meandering and relative diffusion. Results show that the increasing wind reduces the plume vertical motion. The influence of increasing wind shear on the concentration fluctuation intensity is also analyzed. The limited plume vertical looping in conditions of weak convection results in reduction of the concentration fluctuation intensity. Parameterizations for the dispersion parameters are derived as a function of the flow characteristics, namely, the shear?buoyancy ratio, velocity variances, and wind shear. The parameterizations are partially based on previous studies and are verified for the different buoyancy- and shear-driven flows, showing satisfactory agreement with the model results.