The Vertical City Weather Generator (VCWG v1.3.2)
Name
gmd-14-961-2021.pdf
Description
Published version
Size
4.07 MB
Format
Adobe PDF
Checksum (MD5)
0a045f484ee3b5ac6bcd47a8519a65d6
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
2021
Journal
Geoscientific Model Development
Publisher
Copernicus GmbH
Version
Final published version
Abstract
© 2020 Georg Thieme Verlag. All rights reserved. The Vertical City Weather Generator (VCWG) is a computationally efficient urban microclimate model developed to predict temporal and vertical variation of potential temperature, wind speed, specific humidity, and turbulent kinetic energy. It is composed of various sub-models: A rural model, an urban vertical diffusion model, a radiation model, and a building energy model. Forced with weather data from a nearby rural site, the rural model is used to solve for the vertical profiles of potential temperature, specific humidity, and friction velocity at 10 m a.g.l. The rural model also calculates a horizontal pressure gradient. The rural model outputs are applied to a vertical diffusion urban microclimate model that solves vertical transport equations for potential temperature, momentum, specific humidity, and turbulent kinetic energy. The urban vertical diffusion model is also coupled to the radiation and building energy models using twoway interaction. The aerodynamic and thermal effects of urban elements, surface vegetation, and trees are considered. The predictions of the VCWG model are compared to observations of the Basel UrBan Boundary Layer Experiment (BUBBLE) microclimate field campaign for 8 months from December 2001 to July 2002. The model evaluation indicates that the VCWG predicts vertical profiles of meteorological variables in reasonable agreement with the field measurements. The average bias, root mean square error (RMSE), and R2for potential temperature are 0.25 K, 1.41 K, and 0.82, respectively. The average bias, RMSE, and R2for wind speed are 0.67 ms-1, 1.06 ms-1, and 0.41, respectively. The average bias, RMSE, and R2for specific humidity are 0.00057 kg -1, 0.0010 kg kg-1
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-14-961-2021
