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Bruce B. Hicks, William R. Pendergrass III, Christoph A. Vogel, and Richard S. Artz

Abstract

Data from a network of micrometeorological instruments, mostly mounted 10 m above the roofs of 12 buildings in Washington, D.C., are used to derive average values and spatial differences of the normalized local friction velocity u */u ≡ ()1/2/u (with u being the wind speed reported at the same height as the covariance is measured, w being the vertical wind component, primes indicating deviations, and the overbar indicating averaging). The analysis is extended through consideration of two additional sites in New York City, New York. The ratio u */u is found to depend on wind direction for all locations. Averaged values of u */u appear to be best associated with the standard deviation of local building heights, with little evidence of a dependence on any other of the modern building-morphology indices. Temperature covariance data show a large effect of nearby activities, with the consequences of air-conditioning systems being obvious (especially at night) in some situations. The Washington data show that older buildings, built largely of native limestone, show the greatest effects of air-conditioning systems. The assumption that the nighttime surface boundary layer is stable is likely to be most often incorrect for both Washington and New York City—the sensible heat flux resulting from heating and cooling of building work spaces most often appears to dominate.

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Bruce B. Hicks, William J. Callahan, William R. Pendergrass III, Ronald J. Dobosy, and Elena Novakovskaia

Abstract

The utility of aggregating data from near-surface meteorological networks for initiating dispersion models is examined by using data from the “WeatherBug” network that is operated by Earth Networks, Inc. WeatherBug instruments are typically mounted 2–3 m above the eaves of buildings and thus are more representative of the immediate surroundings than of conditions over the broader area. This study focuses on subnetworks of WeatherBug sites that are within circles of varying radius about selected stations of the DCNet program. DCNet is a Washington, D.C., research program of the NOAA Air Resources Laboratory. The aggregation of data within varying-sized circles of 3–10-km radius yields average velocities and velocity-component standard deviations that are largely independent of the number of stations reporting—provided that number exceeds about 10. Given this finding, variances of wind components are aggregated from arrays of WeatherBug stations within a 5-km radius of selected central DCNet locations, with on average 11 WeatherBug stations per array. The total variance of wind components from the surface (WeatherBug) subnetworks is taken to be the sum of two parts: the temporal variance is the average of the conventional wind-component variances at each site and the spatial variance is based on the velocity-component averages of the individual sites. These two variances (and the standard deviations derived from them) are found to be similar. Moreover, the total wind-component variance is comparable to that observed at the DCNet reference stations. The near-surface rooftop wind velocities are about 35% of the magnitudes of the DCNet measurements. Limited additional data indicate that these results can be extended to New York City.

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Bruce B. Hicks, Elena Novakovskaia, Ronald J. Dobosy, William R. Pendergrass III, and William J. Callahan

Abstract

Data from six urban areas in a nationwide network of sites within the surface roughness layer are examined. It is found that the average velocity variances in time, derived by averaging the conventional variances from a network of n stations, are nearly equal to the velocity variances in space, derived as the variances among the n average velocities. This similarity is modified during sunlit hours, when convection appears to elevate the former. The data show little dependence of the ratio of these two variances on wind speed. It is concluded that the average state of the surface roughness layer in urban and suburban areas like those considered here tends toward an approximate equality of these two measures of variance, much as has been observed elsewhere for the case of forests.

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