9B.6 The Vertical City Weather Generator (VCWG 1.0)

Wednesday, 15 January 2020: 11:30 AM
104C (Boston Convention and Exhibition Center)
Mohsen Moradi, Univ. of Guelph, Guelph, ON, Canada; and B. Dyer, A. Nazem, M. K. Nambiar, M. R. Nahian, B. Bueno, C. Mackey, S. Vasanthakumar, N. Nazarian, E. S. Krayenhoff, L. K. Norford, and A. A. Aliabadi

The Vertical City Weather Generator (VCWG) is a computationally efficient urban microclimate model developed to extend the spatial dimension of the preexisting single-layer urban microclimate models to one-dimension in the vertical direction, while it also considers the relationship of the urban microclimate model to the rural meteorological and the building energy conditions. The model is designed to calculate vertical profiles of meteorological variables including potential temperature, wind speed, specific humidity, and turbulence kinetic energy in an urban area. The VCWG is composed of various sub models: a rural model, an urban microclimate model, and a building energy model. In a nearby rural site, a rural model is forced with weather data to solve a vertical diffusion equation to calculate vertical potential temperature profiles using a novel parameterization. The rural model also calculates a horizontal pressure gradient. The rural model outputs are then forced on a vertical diffusion urban microclimate model that solves vertical transport equations for momentum, temperature, and specific humidity. The urban microclimate model is also coupled to a building energy model using feedback interaction. The aerodynamic and thermal effects of urban elements and vegetation are considered in VCWG. To evaluate the VCWG model, a microclimate field campaign was held in Guelph, Canada, from 15 July 2018 to 5 September 2018. The meteorological measurements were carried out under a comprehensive set of wind directions, wind speeds, and thermal stability conditions in both the rural and the nearby urban areas. The results obtained from VCWG agreed reasonably well with the measurements and predicted a +1.0 K Urban Heat Island (UHI) with reasonable agreement to a measured value of +0.7 K. In comparison to measurements, the overall model biases for potential temperature, wind speed, and specific humidity were within 5%, 11%, and 7%, respectively. The performance of the model was further explored to investigate the effects of urban configurations such as plan and frontal area densities, varying levels of vegetation, seasonal variations, different climate zones (Buenos Aires, Tucson, Vancouver, Osaka, and Copenhagen), and time series analysis on the model predictions. The results obtained from the explorations were reasonably consistent with previous studies in the literature, justifying the reliability and computational efficiency of VCWG for operational urban development projects.
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