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Title: Representation and evolution of urban weather boundary conditions in downtown Chicago

Abstract

Our study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the operational High-Resolution Rapid Refresh (HRRR) dataset to provide hourly weather conditions over the Chicago region. We utilize the building footprint, land use, and building stock datasets to generate building energy models using EnergyPlus. We mapped the building exterior surfaces to local air nodes to import simulated microclimate data and to export buildings' heat emissions to their local environment. Preliminary experiments for a test area in Chicago show that predicted building cooling energy use differs by about 4.7% for the selected date when compared with simulations using TMY weather data and without considering the urban microclimate boundary conditions.

Authors:
 [1];  [2];  [1];  [2];  [1]
+ Show Author Affiliations
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Building Technology and Urban Systems Div.
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Argonne National Laboratory (ANL), Argonne, IL (United States). Laboratory Computing Resource Center (LCRC)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
OSTI Identifier:
1484209
Alternate Identifier(s):
OSTI ID: 1638353
Grant/Contract Number:  
AC02-05CH11231; 17-SC-20-SC; AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Building Performance Simulation
Additional Journal Information:
Journal Volume: 13; Journal Issue: 2; Journal ID: ISSN 1940-1493
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; EnergyPlus; WRF; coupling; energy modelling; urban climate modelling

Citation Formats

Jain, Rajeev, Luo, Xuan, Sever, Gökhan, Hong, Tianzhen, and Catlett, Charlie. Representation and evolution of urban weather boundary conditions in downtown Chicago. United States: N. p., 2018. Web. doi:10.1080/19401493.2018.1534275.
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Jain, Rajeev, Luo, Xuan, Sever, Gökhan, Hong, Tianzhen, & Catlett, Charlie. Representation and evolution of urban weather boundary conditions in downtown Chicago. United States. https://doi.org/10.1080/19401493.2018.1534275
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Jain, Rajeev, Luo, Xuan, Sever, Gökhan, Hong, Tianzhen, and Catlett, Charlie. Wed . "Representation and evolution of urban weather boundary conditions in downtown Chicago". United States. https://doi.org/10.1080/19401493.2018.1534275. https://www.osti.gov/servlets/purl/1484209.
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@article{osti_1484209,
title = {Representation and evolution of urban weather boundary conditions in downtown Chicago},
author = {Jain, Rajeev and Luo, Xuan and Sever, Gökhan and Hong, Tianzhen and Catlett, Charlie},
abstractNote = {Our study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the operational High-Resolution Rapid Refresh (HRRR) dataset to provide hourly weather conditions over the Chicago region. We utilize the building footprint, land use, and building stock datasets to generate building energy models using EnergyPlus. We mapped the building exterior surfaces to local air nodes to import simulated microclimate data and to export buildings' heat emissions to their local environment. Preliminary experiments for a test area in Chicago show that predicted building cooling energy use differs by about 4.7% for the selected date when compared with simulations using TMY weather data and without considering the urban microclimate boundary conditions.},
doi = {10.1080/19401493.2018.1534275},
journal = {Journal of Building Performance Simulation},
number = 2,
volume = 13,
place = {United States},
year = {Wed Nov 07 00:00:00 EST 2018},
month = {Wed Nov 07 00:00:00 EST 2018}
}
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Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1080/19401493.2018.1534275
Copyright Statement
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Citation Metrics:
Cited by: 6 works
Citation information provided by
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Figures / Tables:

Figure 1 Figure 1: Left: footprint (city of Chicago). Centre: Goose Island Region with ∼ 20,000 buildings. Right: a small subset of Goose Island with 20 buildings (target area).
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Works referenced in this record:

Global scenarios of urban density and its impacts on building energy use through 2050
journal, January 2017

  • Güneralp, Burak; Zhou, Yuyu; Ürge-Vorsatz, Diana
  • Proceedings of the National Academy of Sciences, Vol. 114, Issue 34
  • DOI: 10.1073/pnas.1606035114

The Impact of Local Microclimate Boundary Conditions on Building Energy Performance
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  • Sustainability, Vol. 7, Issue 7
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Cloud archiving and data mining of High-Resolution Rapid Refresh forecast model output
journal, December 2017

Transforming typical hourly simulation weather data files to represent urban locations by using a 3D urban unit representation with micro-climate simulations
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An Ice-Water Saturation Adjustment
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Chicago’s Heat Island and Climate Change: Bridging the Scales via Dynamical Downscaling
journal, July 2015

  • Conry, Patrick; Sharma, Ashish; Potosnak, Mark J.
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The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems
journal, January 2011

  • Chen, Fei; Kusaka, Hiroyuki; Bornstein, Robert
  • International Journal of Climatology, Vol. 31, Issue 2
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Urban meteorological modeling using WRF: a sensitivity study: SENSITIVITY STUDY ON URBAN METEOROLOGY MODELING
journal, July 2016

  • Sharma, Ashish; Fernando, Harindra J. S.; Hamlet, Alan F.
  • International Journal of Climatology, Vol. 37, Issue 4
  • DOI: 10.1002/joc.4819
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    Figures / Tables found in this record:

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    Figure 16 (p. 12)figure
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