Citation:

Pirhalla, M., D. Heist, S. Perry, S. Hanna, T. Mazzola, S. Arya, AND V. Aneja. Urban Wind Field Analysis from the Jack Rabbit II Special Sonic Anemometer Study. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 243:117871, (2020). https://doi.org/10.1016/j.atmosenv.2020.117871

Impact/Purpose:

The Jack Rabbit II Special Sonic Anemometer Study (JRII-S), a field project designed to examine the flow and turbulence within a systematically arranged mock-urban environment constructed from CONEX shipping containers, is described in detail in this manuscript. The study involved the deployment of 35 sonic anemometers at multiple heights and locations, including a tall, unobstructed tower located outside the building array to document the approach wind flow characteristics. This manuscript is the first in-depth description of the JRII-S field study. The purpose of this work was to analyze the sonic data and report observed wind flow patterns within the urban canopy in comparison to the approaching boundary layer flow. We show that the flow within the building array follows a tendency towards one of three generalized flow regimes displaying channeling over a wide range of wind speeds, directions, and atmospheric stabilities. Two or more sensors positioned only about 2-5 meters apart can have vastly different flow patterns that are dictated by the building structures. Within the building array, turbulence values represented by normalized vertical velocity variance, a method of describing fine-scale changes in upward or downward wind flow, are at least two to three times greater than that in the approach flow and show little variation with height. There is also little evidence that the vertical variance measured at various heights or locations within the array is a strong function of stability type in contrast to the approach flow. The results reinforce how urban areas create complicated wind patterns, channeling effects, and localized turbulence that can impact the dispersion of an effluent release. These findings can be used to inform development of improved wind flow algorithms to better characterize pollutant dispersion in fast-response models. The manuscript may be of interest to emergency planners, stakeholders, and micro-meteorologists examining complex wind flow within urban areas. The implication is that any neutrally buoyant release would be carried within the wind's streamline flow and affect locations downwind.

Description:

The Jack Rabbit II Special Sonic Anemometer Study (JRII-S), a field project designed to examine the flow and turbulence within a systematically arranged mock-urban environment constructed from CONEX shipping containers, is described in detail. The study involved the deployment of 35 sonic anemometers at multiple heights and locations, including a 32 m tall, unobstructed tower located about 115 m outside the building array to document the approach wind flow characteristics. Along with a description of the study, the purpose of this work was to analyze the sonic data and report observed wind flow patterns within the urban canopy in comparison to the approaching boundary layer flow. We show that the flow within the building array follows a tendency towards one of three generalized flow regimes displaying channeling over a wide range of wind speeds, directions, and stabilities. Two or more sonics positioned only a few meters apart can have vastly different flow patterns that are dictated by the building structures. Within the building array, turbulence values represented by normalized vertical velocity variance are at least two to three times greater than that in the approach flow and show little variation with height. There is also little evidence that the vertical variance measured at various heights or locations within the array is a strong function of stability type in contrast to the approach flow. The results reinforce how urban areas create complicated wind patterns, channeling effects, and localized turbulence that can impact the dispersion of an effluent release. These findings can be used to inform development of improved wind flow algorithms to better characterize pollutant dispersion in fast-response models.

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