3.1 Use of turbulence measurements in dispersion modeling: past, present, and future (2010

3.1

Use of turbulence measurements in dispersion modeling: past, present, and future

Jeffrey C. Weil, CIRES/Univ. of Colorado, Boulder, CO

This paper reviews the use of turbulence measurements in dispersion

modeling for air quality and national security issues and considers its

future prospects. Historically, one of the prime types of turbulence

data used in these applications were the root-mean-square wind fluctuations

or velocity variances for estimating dispersion (plume spread) directly

by an application of Taylor's (1921) statistical theory; this has been applied

mostly for short-range dispersion---distances of 20 km or less.

Turbulence measurements of this type have been adopted in 1) simple

analytical/statistical models (e.g., Gaussian plume), 2) Lagrangian

particle models, 3) closure-based models, and 4) other numerical

models (e.g., large-eddy simulations (LESs)). Another key use of

turbulence information has been in building turbulence profile

parameterizations of planetary boundary layer (PBL) variables (e.g.,

velocity variances, skewness, time scales, etc.) for driving dispersion

models. This has been done in conjunction with PBL models, LES results,

and laboratory data, and such parameterizations have been adopted in

a number of state-of-the-art air pollution models (e.g., AERMOD,

OML, HPDM, etc.). One of the key quesitons is: Are model predicitons

improved and if so, by how much?

Along the same lines, we consider the use of high frequency wind and

temperature data to drive dispersion models---principally numerical

models that can accept such information. For example, we show results

from an LES application in Salt Lake City and also from a recent field

campaign at the Dugway Proving Ground. These and other uses of high

frequency data (e.g., data assimilation) are considered in the context

of future model applications.