Record Display for the EPA National Library Catalog

RECORD NUMBER: 25 OF 42

OLS Field Name OLS Field Data
Main Title Indirect Estimation of Convective Boundary Layer Structure for Use in Routine Dispersion Models.
Author Wilczak, J. M. ; Phillips, M. S. ;
CORP Author National Oceanic and Atmospheric Administration, Boulder, CO. Wave Propagation Lab.;Environmental Sciences Research Lab., Research Triangle Park, NC.
Year Published 1984
Report Number EPA/600/3-84/091;
Stock Number PB84-238260
Additional Subjects Atmospheric circulation ; Boundary layer flow ; Mathematical models ; Atmospheric diffusion ; Air pollution ; Meteorology ; Wind velocity ; Surfaces ; Atmospheric dispersion
Holdings
Library Call Number Additional Info Location Last
Modified
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Status
NTIS  PB84-238260 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 06/23/1988
Collation 89p
Abstract
Dispersion models of the convectively driven atmospheric boundary layer (ABL) often require as input meteorological parameters that are not routinely measured. These parameters usually include (but are not limited to) the surface heat and momentum fluxes, the height of the capping inversion Z(i), the mean windspeed, wind direction and temperature profiles up to Z(i), and the profiles of the turbulent wind components. Through use of a simple inversion rise model, surface layer flux-profile relationships, and similarity scaling laws for the convective ABL, we demonstrate how the required meteorological parameters can be deduced using much simpler and more readily available measurements. These measurements consist of an early morning temperature profile obtained from a radiosonde ascent; single level surface layer values of U, AZ, sigma sub u and sigma sub v; two levels of mean temperature near the surface; and an estimate of the local surface roughness. Predicted values of each of the required parameters are compared to directly measured values of 26 days of data. Except for wind direction, each of these parameters can be estimated with an average error of 10-30%. For light windspeeds the mean wind direction profile is strongly affected by slight terrain inhomogenieties, and simple wind direction parameterizations fail. Finally, the role of averaging time in estimating the error of an individual realization is discussed.