A skewed homogeneous lagrangian particle model for convective conditions

Abstract Numerical solution of the Langevin equation for convective conditions usually requires quite small time steps in order to resolve properly the smaller-scale turbulence near the boundaries. This time step restriction can be eased significantly if it is assumed that the turbulence is uniform over the whole depth of the mixed layer. In this paper, we investigate the effect of this homogeneous turbulence assumption on ground-level concentration (glc) by comparing results with (a) the Willis and Deardorff laboratory experiments on dispersion in fully convective conditions and (b) the predictions of a model employing a more realistic inhomogeneous parameterization for the turbulence. As far as the ability to predict the magnitude and location of the near-source maximum glc, and the ability to maintain a well-mixed profile further downwind are concerned, we conclude that the assumption of homogeneous turbulence is quite adequate. We also compare Gaussian and skewed distributions for homogeneous turbulence and show that realistic results in convective conditions can only be obtained with the skewed distribution.

[1]  Y. Zhuang,et al.  Restriction on the timestep to be used in stochastic Lagrangian models of turbulent dispersion , 1989 .

[2]  Peter J. Hurley,et al.  A Lagrangian particle model of fumigation by breakdown of the nocturnal inversion , 1991 .

[3]  S. Bunker,et al.  Development of a Nested Grid, Second Moment Turbulence Closure Model and Application to the 1982 ASCOT Brush Creek Data Simulation , 1988 .

[4]  J. Deardorff,et al.  A laboratory study of dispersion from a source in the middle of the convectively mixed layer , 1981 .

[5]  J. Deardorff,et al.  A laboratory model of diffusion into the convective planetary boundary layer , 1976 .

[6]  D. Thomson Criteria for the selection of stochastic models of particle trajectories in turbulent flows , 1987, Journal of Fluid Mechanics.

[7]  J. Deardorff,et al.  Three-dimensional numerical study of turbulence in an entraining mixed layer , 1974 .

[8]  Rex Britter,et al.  A random walk model for dispersion in inhomogeneous turbulence in a convective boundary layer , 1989 .

[9]  Frans T. M. Nieuwstadt,et al.  An application of the Langevin equation for inhomogeneous conditions to dispersion in a convective boundary layer , 1986 .

[10]  Chih-Yue Jim Kao,et al.  Use of the CAPTEX Data for Evaluations of a Long-Range Transport Numerical Model with a Four-Dimensional Data Assimilation Technique , 1988 .

[11]  Roger A. Pielke,et al.  Influence of diurnal and inertial boundary-layer oscillations on long-range dispersion , 1988 .

[12]  D. Etling,et al.  Application of a random walk model to turbulent diffusion in complex terrain , 1986 .

[13]  Ground-level concentrations due to fumigation into an entraining mixed layer , 1982 .

[14]  J. Deardorff,et al.  A laboratory study of dispersion from an elevated source within a modeled convective planetary boundary layer , 1978 .

[15]  Donald H. Lenschow,et al.  Mean-Field and Second-Moment Budgets in a Baroclinic, Convective Boundary Layer , 1980 .

[16]  J. Deardorff,et al.  A Laboratory Model of the Unstable Planetary Boundary Layer , 1974 .

[17]  Robert G. Lamb,et al.  A numerical simulation of dispersion from an elevated point source in the convective planetary boundary layer , 1978 .

[18]  Ruwim Berkowicz,et al.  Monte Carlo simulation of plume dispersion in the convective boundary layer , 1984 .

[19]  B. Sawford,et al.  Lagrangian Stochastic Analysis of Flux-Gradient Relationships in the Convective Boundary Layer , 1987 .

[20]  R. Pielke,et al.  Application of a mesoscale atmospheric dispersion modeling system to the estimation of SO2 concentrations from major elevated sources in Southern Florida , 1988 .