Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America

Zeng, Zhaoyun; Kim, Ji-Hyun; Wang, Jiali; Muehleisen, Ralph

doi:10.25984/2202668

Title: Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America

Dataset
Other Related Research

Abstract

This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4). This dataset is in the EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). It contains 13 weather variables, which are the Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth. The weather data is created for two emissions scenarios: RCP4.5 and RCP8.5 and spans two 10-year time slices in the future: 2045 - 2054 and 2085 - 2094. It offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormousmore »« less

Authors:

; Kim, Ji-Hyun; Wang, Jiali; Muehleisen, Ralph

Publication Date:: Tue Oct 03 00:00:00 EDT 2023

Other Number(s):: 5974

DOE Contract Number:: FY22 AOP 3.5.5.63

Research Org.:: DOE Open Energy Data Initiative (OEDI); Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)

Collaborations:: Argonne National Laboratory

Subject:: Array

Keywords:: energy; future weather; climate change; North America; building energy modeling; dynamical downscaling; WRF; model; modeling; data; processed data; weather; RCP8.5; RCP4.5; PUMA; hourly

Geolocation:: 78.2,-58.5|23.8,-58.5|23.8,-158.4|78.2,-158.4|78.2,-58.5

OSTI Identifier:: 2202668

DOI:: https://doi.org/10.25984/2202668

Project Location:

Citation Formats


                    Zeng, Zhaoyun, Kim, Ji-Hyun, Wang, Jiali, and Muehleisen, Ralph. Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America.  United States: N. p., 2023. 
        Web.  doi:10.25984/2202668.

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                    Zeng, Zhaoyun, Kim, Ji-Hyun, Wang, Jiali, & Muehleisen, Ralph. Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America.  United States.  doi:https://doi.org/10.25984/2202668

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                    Zeng, Zhaoyun, Kim, Ji-Hyun, Wang, Jiali, and Muehleisen, Ralph. 2023.  
"Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America".  United States.  doi:https://doi.org/10.25984/2202668.  https://www.osti.gov/servlets/purl/2202668. Pub date:Tue Oct 03 00:00:00 EDT 2023

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@article{osti_2202668,

  title        = {Dynamically Downscaled Hourly Future Weather Data with 12-km Resolution Covering Most of North America},

  author       = {Zeng, Zhaoyun and Kim, Ji-Hyun and Wang, Jiali and Muehleisen, Ralph},

  abstractNote = {This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4). This dataset is in the EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). It contains 13 weather variables, which are the Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth. The weather data is created for two emissions scenarios: RCP4.5 and RCP8.5 and spans two 10-year time slices in the future: 2045 - 2054 and 2085 - 2094. It offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormous size of the entire dataset, in the first stage of its distribution, we provide 20 years of future weather data for the centroid of each Public Use Microdata Area (PUMA), excluding Hawaii. PUMAs are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. The 2,378 PUMAs as a whole cover the entirety of the U.S. The weather data can be utilized alongside the large-scale energy analysis tools, ResStock and ComStock, developed by National Renewable Energy Laboratory, whose smallest resolution is at the PUMA scale. The data for RCP4.5 is still being processed and will be published soon.},

  doi          = {10.25984/2202668},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Oct 03 00:00:00 EDT 2023},

  month        = {Tue Oct 03 00:00:00 EDT 2023}

}

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DOI: https://doi.org/10.25984/2202668

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