Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes models trained to estimate UHI in Los Angeles and Seattle, along with open-source software and additional training data for the 50 most populous cities in the contiguous United States. The study demonstrates the application of these methods in evaluating climate change impacts and heat mitigation strategies within high-resolution urban microclimate modeling. The dataset aims to provide a computationally efficient and adaptable solution for urban planners to address various heat planning questions and prioritize heat mitigation strategies. The open-source models, software, and data will contribute to the development of more heat-resilient and sustainable urban environments in the face of climate change.
Citation Formats
TY - DATA
AB - Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes models trained to estimate UHI in Los Angeles and Seattle, along with open-source software and additional training data for the 50 most populous cities in the contiguous United States. The study demonstrates the application of these methods in evaluating climate change impacts and heat mitigation strategies within high-resolution urban microclimate modeling. The dataset aims to provide a computationally efficient and adaptable solution for urban planners to address various heat planning questions and prioritize heat mitigation strategies. The open-source models, software, and data will contribute to the development of more heat-resilient and sustainable urban environments in the face of climate change.
AU - Buster, Grant
A2 - Cox, Jordan
A3 - Benton, Brandon
A4 - King, Ryan
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Laboratory of the Rockies
DO -
KW - energy
KW - power
KW - urban heat island uhi
KW - climate change
KW - cmip6
KW - climate adaptation
KW - extreme heat
KW - albedo modification
KW - air temperature
KW - land surface temperature lst
KW - relative humidity
KW - sustainability
KW - machine learning
KW - weather
KW - climate
KW - remote sensing
KW - satellite data
KW - Sup3rUHI
KW - renewable resource
KW - ML
KW - UHI
KW - cities
KW - United States
KW - heat mitigation
KW - microclimate
KW - model
KW - data
LA - English
DA - 2024/10/16
PY - 2024
PB - National Renewable Energy Lab (NREL)
T1 - Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)
UR - https://data.openei.org/submissions/6220
ER -
Buster, Grant, et al. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). National Renewable Energy Lab (NREL), 16 October, 2024, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/6220.
Buster, G., Cox, J., Benton, B., & King, R. (2024). Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). [Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Lab (NREL). https://data.openei.org/submissions/6220
Buster, Grant, Jordan Cox, Brandon Benton, and Ryan King. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). National Renewable Energy Lab (NREL), October, 16, 2024. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/6220
@misc{OEDI_Dataset_6220,
title = {Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)},
author = {Buster, Grant and Cox, Jordan and Benton, Brandon and King, Ryan},
abstractNote = {Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes models trained to estimate UHI in Los Angeles and Seattle, along with open-source software and additional training data for the 50 most populous cities in the contiguous United States. The study demonstrates the application of these methods in evaluating climate change impacts and heat mitigation strategies within high-resolution urban microclimate modeling. The dataset aims to provide a computationally efficient and adaptable solution for urban planners to address various heat planning questions and prioritize heat mitigation strategies. The open-source models, software, and data will contribute to the development of more heat-resilient and sustainable urban environments in the face of climate change.},
url = {https://data.openei.org/submissions/6220},
year = {2024},
howpublished = {Open Energy Data Initiative (OEDI), National Renewable Energy Lab (NREL), https://data.openei.org/submissions/6220},
note = {Accessed: 2026-08-18}
}
Details
Data from Oct 16, 2024
Last updated Sep 16, 2025
Submitted Oct 23, 2024
Organization
National Renewable Energy Lab (NREL)
Contact
Grant Buster
720.495.6245
