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dc.contributor.authorMoradi, Mohsen
dc.contributor.authorDyer, Benjamin
dc.contributor.authorNazem, Amir
dc.contributor.authorNambiar, Manoj K
dc.contributor.authorNahian, M Rafsan
dc.contributor.authorBueno, Bruno
dc.contributor.authorMackey, Chris
dc.contributor.authorVasanthakumar, Saeran
dc.contributor.authorNazarian, Negin
dc.contributor.authorKrayenhoff, E Scott
dc.contributor.authorNorford, Leslie Keith
dc.contributor.authorAliabadi, Amir A
dc.date.accessioned2021-10-18T14:26:15Z
dc.date.available2021-10-18T14:26:15Z
dc.date.issued2019-08
dc.identifier.urihttps://hdl.handle.net/1721.1/133020
dc.description.abstract<jats:p>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. </jats:p>en_US
dc.language.isoen
dc.publisherCopernicus GmbHen_US
dc.relation.isversionof10.5194/GMD-2019-176en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceCopernicus Publicationsen_US
dc.titleThe Vertical City Weather Generator (VCWG v1.0.0)en_US
dc.typeArticleen_US
dc.identifier.citationMoradi, 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.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Architectureen_US
dc.relation.journalGeoscientific Model Development Discussionsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-05-10T18:15:41Z
dspace.orderedauthorsMoradi, M; Dyer, B; Nazem, A; Nambiar, MK; Nahian, MR; Bueno, B; Mackey, C; Vasanthakumar, S; Nazarian, N; Krayenhoff, ES; Norford, LK; Aliabadi, AAen_US
dspace.date.submission2021-05-10T18:15:46Z
mit.licensePUBLISHER_CC
mit.metadata.statusPublication Information Neededen_US


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