Return to search results
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.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"019:20"
]
|
| contactPoint |
{
"fn": "Grant Buster",
"@type": "vcard:Contact",
"hasEmail": "mailto:grant.buster@nrel.gov"
}
|
| dataQuality |
true
|
| description | 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. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Sup3rUHI on AWS",
"format": "HTML",
"accessURL": "https://data.openei.org/s3_viewer?bucket=oedi-data-lake&prefix=sup3ruhi%2F",
"mediaType": "text/html",
"description": "Sup3rUHI dataset in AWS S3. "
},
{
"@type": "dcat:Distribution",
"title": "Sup3rUHI Github Repository",
"format": "HTML",
"accessURL": "https://github.com/nrel/sup3ruhi",
"mediaType": "text/html",
"description": "Sup3rUHI software code repository."
},
{
"@type": "dcat:Distribution",
"title": "OEDI Data Registry on AWS",
"format": "HTML",
"accessURL": "https://registry.opendata.aws/oedi-data-lake/",
"mediaType": "text/html",
"description": "AWS public dataset program registry page for data released under the Department of Energy's (DOE) Open Energy Data Initiative (OEDI). The registry page contains information about dataset documentation, access, and contact, for each of the OEDI Data Lake datasets."
},
{
"@type": "dcat:Distribution",
"title": "Publication",
"format": "HTML",
"accessURL": "https://www.sciencedirect.com/science/article/pii/S2212095525003190",
"mediaType": "text/html",
"description": ""Estimating the impacts of increasing temperatures and the efficacy of climate adaptation strategies in urban microclimates with deep learning" publication detailing the Sup3rUHI project purpose, methods, and conclusions. "
}
]
|
| identifier | https://data.openei.org/submissions/6220 |
| issued | 2024-10-16T06:00:00Z |
| keyword |
[
"ML",
"Sup3rUHI",
"UHI",
"United States",
"air temperature",
"albedo modification",
"cities",
"climate",
"climate adaptation",
"climate change",
"cmip6",
"data",
"energy",
"extreme heat",
"heat mitigation",
"land surface temperature lst",
"machine learning",
"microclimate",
"model",
"power",
"relative humidity",
"remote sensing",
"renewable resource",
"satellite data",
"sustainability",
"urban heat island uhi",
"weather"
]
|
| landingPage | https://data.openei.org/submissions/6220 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2025-09-16T21:16:25Z |
| programCode |
[
"019:000",
"019:002",
"019:023"
]
|
| publisher |
{
"name": "National Renewable Energy Lab (NREL)",
"@type": "org:Organization"
}
|
| spatial |
"{"type":"Polygon","coordinates":[[[-180,-83],[180,-83],[180,83],[-180,83],[-180,-83]]]}"
|
| title | Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) |
