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P. Ramamurthy, E. R. Pardyjak, and J. C. Klewicki

data were broken up into three datasets representing the three stability regimes considered as follows: 20 h, stable; 16 h, unstable; and 12 h, neutral. The fluctuating components of velocity and temperature were calculated by first linearly detrending the raw dataset using 5-min windows. The detrended data were then used to calculate 15-min averages of various turbulence statistics (i.e., momentum fluxes, heat fluxes, turbulent kinetic energy, and variances). Fifteen-minute averaging periods were

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Yansen Wang, Cheryl L. Klipp, Dennis M. Garvey, David A. Ligon, Chatt C. Williamson, Sam S. Chang, Rob K. Newsom, and Ronald Calhoun

a topic of research. Due to the interaction of high roughness and thermally generated turbulence, the urban atmospheric boundary layer is complex and difficult to study. Many observational studies have focused on intraurban surface fluxes using standard micrometeorological towers. Very few observations have been made above the building height. Most published urban boundary layer (UBL) field studies have concentrated on convective conditions ( Jackson 1978 ; Ching 1985 ; Godowitch 1986

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Cheryl Klipp

constant flux layer as assumed by surface-layer scaling relationships ( Rotach 1993 ). However, it is these surface-layer relationships, derived over flat homogeneous terrain, that are the basis of boundary layer models. It is assumed that the higher the observation is above the obstructions, the more the effects of individual surface elements are blended into a uniform representation of the entire urban area. Most experiments attempt to place instrumentation above the effects of local influences so as

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Steve R. Diehl, Donald A. Burrows, Eric A. Hendricks, and Robert Keith

the size of the smallest building of interest. To initialize the grid and to supply the wind profile and turbulence energy and dissipation at the inflow boundary, a 1D numerical algorithm that contains the k – ω turbulence equations is included. The algorithm computes the flow as a function of altitude over a rough surface based on the sensible heat flux and surface roughness. RUSTIC can be run with an upwind heat flux that differs from the heat flux value around the larger buildings. 3. MESO

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Eric A. Hendricks, Steve R. Diehl, Donald A. Burrows, and Robert Keith

equation, the speed of sound is reduced to the maximum velocity in the model in order to accelerate the computation (this can be done because acoustic waves do not contribute to the solution). The turbulent fluxes from the RANS equations are parameterized by a gradient transfer process, and a k–ω turbulence model ( Wilcox 1998 ) is used to predict the eddy viscosity coefficient. This turbulence model was chosen because it has been demonstrated to perform better in transitional flows, flows with

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Donald A. Burrows, Eric A. Hendricks, Steve R. Diehl, and Robert Keith

sources are modeled explicitly but require information on the atmospheric conditions, especially turbulence due to mesoscale circulations and boundary layer processes. For mesoscale models, estimates of the heat and momentum fluxes due to urban effects are needed, as is a characterization of the city in terms of surface roughness or drag coefficient. Urban-scale models could be used to provide better information to mesoscale models regarding the local influence of large building areas of a city. Of

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M. A. Nelson, E. R. Pardyjak, M. J. Brown, and J. C. Klewicki

and Oke 2002 ). High above the urban roughness in the inertial sublayer (ISL), where the turbulent fluxes are relatively constant, the flow mechanics are relatively straightforward and standard similarity theories generally apply; Roth (2000) provides a good review of several urban field studies that illustrate this. The complexity of the flow mechanics often increases in the canopy. Because the high three-dimensionality and spatial variability of the mean flow near urban surfaces, the study of

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M. A. Nelson, E. R. Pardyjak, J. C. Klewicki, S. U. Pol, and M. J. Brown

ASL may still apply. [ Roth (2000) provides a good review of several studies that demonstrate this.] This is because the underlying assumptions used to produce such relations (statistical stationarity, horizontal homogeneity, constant fluxes, zero-mean vertical and cross-wind components, etc.) may be approximately valid. For smaller scales of motion below a few average building heights, however [i.e., within the urban roughness sublayer (URSL) and urban canopy layer (UCL)], the buildings’ effects

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Julia E. Flaherty, Brian Lamb, K. Jerry Allwine, and Eugene Allwine

within 20% (lower) of those values listed in Table 1 determined from sonic measurements of momentum fluxes. The average surface roughness value (∼2 m) resulting from the fit to the logarithmic wind profile was commensurate with accepted values for urban areas ( Stull 1988 ). It is not clear why the wind speeds at the lowest two measurement heights (7.8 and 14.6 m) were considerably higher than expected from the logarithmic profile (approximately 2.7 m s −1 measured versus 1.8 m s −1 expected at

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Stevens T. Chan and Martin J. Leach

Releases—Implications for Homeland Security . National Research Council, 93 pp . Dyer , A. J. , 1974 : A review of flux-profile relationships. Bound.-Layer Meteor. , 7 , 363 – 372 . Gresho , P. , and S. Chan , 1998 : Projection 2 goes turbulent—and fully implicit. J. Comput. Fluid Dyn. , 9 , 249 – 272 . Hanna , S. , O. Hansen , and S. Dharmavaram , 2004 : FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations. Atmos

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