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- Author or Editor: Richard A. Brost x
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Abstract
The vertical diffusion of a passive conservative scalar through the convective PBL is actually the superposition of what we call “top-down” and “bottom up” processes. These component processes are driven by scalar fluxes at the mixed-layer top and bottom. We argue that the vertical asymmetry in the buyoant production of the turbulent kinetic energy should cause the top-down and bottom-up diffusivities to differ. If so, we show that the diffusivity for the total process is poorly behaved; it depends on the scalar flux profile and can have singularities.
We present results from large-eddy simulations which confirm that the top-down and bottom-up diffusivities are different, the latter being substantially larger. We present simple parameterizations for these diffusivities and the corresponding mean gradients. The results are useful in “unmixed layer” models and in Fielder' integral closure for scalar flux.
Abstract
The vertical diffusion of a passive conservative scalar through the convective PBL is actually the superposition of what we call “top-down” and “bottom up” processes. These component processes are driven by scalar fluxes at the mixed-layer top and bottom. We argue that the vertical asymmetry in the buyoant production of the turbulent kinetic energy should cause the top-down and bottom-up diffusivities to differ. If so, we show that the diffusivity for the total process is poorly behaved; it depends on the scalar flux profile and can have singularities.
We present results from large-eddy simulations which confirm that the top-down and bottom-up diffusivities are different, the latter being substantially larger. We present simple parameterizations for these diffusivities and the corresponding mean gradients. The results are useful in “unmixed layer” models and in Fielder' integral closure for scalar flux.
Abstract
We compared observed and model-simulated surface concentration on a spatial wale of 1100 km and a temporal scale of 36 h. The Eulerian tracer model calculated advection by the mean winds and gradient transport for subgrid-scale turbulent transfer. The simulations were evaluated by the maximum concentrations, spatial correlations between concentrations, plume sizes, and trajectory errors. We examined the following inputs and model parameters: 1) different meteorologies, including simulated, observed, and combinations of the two; 2) the spatial and temporal resolution of the observations; 3) the spatial resolution of the meteorological model; and 4) the spatial resolution of the tracer model. The best meteorology was observed horizontal winds, enhanced with additional, nonstandard rawinsondes and model-simulated eddy diffusivities. The spatial resolution of the tracer model was more important than that of the meteorological model. Meteorology from a mesoscale model could be competitive with that from standard observations. We found consistency between different measures of tracer simulation quality.
Abstract
We compared observed and model-simulated surface concentration on a spatial wale of 1100 km and a temporal scale of 36 h. The Eulerian tracer model calculated advection by the mean winds and gradient transport for subgrid-scale turbulent transfer. The simulations were evaluated by the maximum concentrations, spatial correlations between concentrations, plume sizes, and trajectory errors. We examined the following inputs and model parameters: 1) different meteorologies, including simulated, observed, and combinations of the two; 2) the spatial and temporal resolution of the observations; 3) the spatial resolution of the meteorological model; and 4) the spatial resolution of the tracer model. The best meteorology was observed horizontal winds, enhanced with additional, nonstandard rawinsondes and model-simulated eddy diffusivities. The spatial resolution of the tracer model was more important than that of the meteorological model. Meteorology from a mesoscale model could be competitive with that from standard observations. We found consistency between different measures of tracer simulation quality.
