Model America – data and models of every U.S. building

New, Joshua; Adams, M. R.; Berres, Anne; Bass, Brett; Clinton, Nicholas

doi:10.13139/ornlnccs/1774134

Cited by 4 publications

(3 citation statements)

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“…Such work would build on previous efforts by, for example, Haman, et al 74 and Soleimanian, et al 75 . 2) coupled with information from urban digital twins 76 , it could contribute to improving our understanding of the natural ventilation potential of buildings in Houston. Such work would build on previous efforts by, for example, Tong, et al 77 and Davis and Lamer 78 .…”

Section: Usage Notesmentioning

confidence: 99%

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

Lamer,

Mages,

Treserras

et al. 2024

Sci Data

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In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston’s proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.

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Section: Usage Notesmentioning

confidence: 99%

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

Lamer,

Mages,

Treserras

et al. 2024

Sci Data

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“…On the other end of the spectrum, there is the approach to model every building within the stock-a "population" modeling approach. This is not common given the computational intensity and the difficulty obtaining data on every single building within a stock, but there are a few notable examples of this approach being used (New et al 2021). For this project, we propose an intermediate approach where we develop a large set of representative BEMs for each typology segment in the stock using NREL's ResStock and ComStock models.…”

Section: Background On Building Stock Segmentation Approachesmentioning

confidence: 99%

U.S. Building Stock Characterization Study: A National Typology for Decarbonizing U.S. Buildings

Reyna¹,

Wilson²,

Parker³

et al. 2022

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This report, originally published in December 2021, has been revised in July 2022 to expand the report scope to include commercial characterization in addition to the residential characterization in the original publication. The majority of these changes are in the new Section 3.2. Additionally, to support this scope expansion, we have included the additional section authors, added two appendences, modified the executive summary and conclusions, and updated text throughout to be inclusive of both the residential and commercial sectors. iv This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

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“…Theoretically, a "population" model (where every single building is simulated) could be ideal for identifying retrofit opportunities, but practically, on a national scale it would be extremely difficult to map building characteristics, and it would require high computational intensity. Despite this, there is one recent example of a project pursuing this approach (New et al 2021). For this project, we propose an intermediate approach where we develop a large set of representative BEMs for each typology segment in the stock using NREL's ResStock and ComStock models.…”

Section: Background On Building Stock Segmentation Approachesmentioning

confidence: 99%

U.S. Building Stock Characterization Study: A National Typology for Decarbonizing U.S. Buildings

Reyna¹,

Wilson²,

Satre-Meloy³

et al. 2021

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This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. Residential Climate Area 4: Hot-Dry/Mixed-DryThe Hot-Dry/Mixed-Dry climate region covers southern California, the California Central Valley, southern Nevada, southern Arizona, southern New Mexico, and west Texas. Homes in this area represent 12% of U.S. housing units and residential buildings, and 6% of the residential thermal end-use energy. Figure 14 shows the 33 segments in the Hot-Dry/Mixed-Dry region, with the number of buildings, average building size, average thermal end-use intensity, and annual thermal end-use energy used in each segment.

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Model America – data and models of every U.S. building

Cited by 4 publications

References 0 publications

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

U.S. Building Stock Characterization Study: A National Typology for Decarbonizing U.S. Buildings

U.S. Building Stock Characterization Study: A National Typology for Decarbonizing U.S. Buildings

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