Campus Units

Civil, Construction and Environmental Engineering, Geological and Atmospheric Sciences, Mechanical Engineering

Document Type

Conference Proceeding

Publication Version

Published Version

Publication Date

2019

Journal or Book Title

ASHRAE Transactions

Volume

125

First Page

248

Last Page

256

Conference Title

2019 ASHRAE Annual Conference

Conference Date

June 22-26, 2019

City

Kansas City, MO

Abstract

Building energy consumption is highly influenced by weather conditions, thus having appropriate weather data is important for improving the accuracy of building energy models. Typically local weather station data from the nearest airport or military base is used for weather data input. However this is generally known to differ from the actual weather conditions experienced by an urban building, particularly considering most weather stations are located far from urban areas. The use of the Weather Research and Forecasting Model (WRF) coupled with an Urban Canopy Model (UCM) provides a means to be able to predict more localized variations in weather conditions. However, one of the main challenges associated with the assessment of the use of this model is the lack of availability of ground based weather station data with which to compare its results. This has generally limited the ability to assess the level of agreement between WRF-UCM weather predictions and measured weather data in urban locations. In this study, a network of 40 ground based weather stations located in Austin, TX are compared to WRF/UCM-predicted weather data, to assess similarities and differences between model-predicted results and actual data. Given that the WRF-UCM method also takes into account many input parameters and assumptions, including the urban fraction which can be measured at different scales, this work also considers the relative impact of the granularity of the urban fraction data on WRF-UCM predicted weather. As a case study, a building energy model of a typical residential building is then developed and used to assess the differences in predicted building energy use and demands between the WRF-UCM weather and measured weather conditions during an extreme heatwave event in Austin, TX.

Comments

This proceeding is published as Jahani, Elham, Soham Vanage, Kristen Cetin, David Jahn, and William Gallus. "City-Scale High-Resolution WRF-UCM Urban Weather Predictions Compared to a Dense Network of Ground-Based Weather Station Data for Assessment of Urban Building Energy Consumption." ASHRAE Transactions 125, part 2 (2019): 248-256. Posted with permission.

Copyright Owner

ASHRAE

Language

en

File Format

application/pdf

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