The Vertical City Weather Generator (VCWG v1.0.0)
Name
gmd-2019-176.pdf
Description
Published version
Size
12.05 MB
Format
Adobe PDF
Checksum (MD5)
dd5a65a64a2f595d44b4b970b46cc608
Author(s)
Moradi, Mohsen
Dyer, Benjamin
Nazem, Amir
Nambiar, Manoj K
Nahian, M Rafsan
Bueno, Bruno
Mackey, Chris
Vasanthakumar, Saeran
Nazarian, Negin
Krayenhoff, E Scott
Date Issued
August 2019
Journal
Geoscientific Model Development Discussions
Publisher
Copernicus GmbH
Citation
Moradi, Mohsen, Dyer, Benjamin, Nazem, Amir, Nambiar, Manoj K, Nahian, M Rafsan et al. 2019. "The Vertical City Weather Generator (VCWG v1.0.0)." Geoscientific Model Development Discussions.
Version
Final published version
Abstract
Abstract. The Vertical City Weather Generator (VCWG) is a computationally efficient urban microclimate model developed to predict temporal and vertical variation of temperature, wind speed, and specific humidity. It 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 model evaluation indicated that the VCWG predicted vertical profiles of meteorological variables in reasonable agreement with field measurements for selected days. 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, 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.
MIT Department
Massachusetts Institute of Technology. Department of Architecture
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.5194/GMD-2019-176
