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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 model...
Buster, G. et al The National Renewable Energy Lab (NREL)
Oct 16, 2024
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
University of Miami Coupled Model (UMCM) for Hurricanes Ike and Sandy
The University of Miami Coupled Model (UMCM) is a coupled model that integrates atmospheric, wave, and ocean components to produce wind, wave, and current data. Atmospheric data is produced using the [Weather Research and Forecasting model](https://www.mmm.ucar.edu/weather-researc...
Phillipes, C. et al National Renewable Energy Laboratory
Sep 30, 2015
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)
The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios.
Sup3rCC is downscaled ...
Buster, G. et al The National Renewable Energy Lab (NREL)
Apr 19, 2023
7 Resources
1 Stars
Curated
7 Resources
1 Stars
Curated
High Resolution Ocean Surface Wave Hindcast (US Wave) Data
The development of this dataset was funded by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, Water Power Technologies Office to improve our understanding of the U.S. wave energy resource and to provide critical information for wave energy project de...
Yang, Z. et al National Renewable Energy Laboratory
Jul 01, 2020
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Seismic Survey 2016 Data at San Emidio Nevada
Included here are seismic data recorded at the San Emidio Geothermal field in Nevada. This passive seismic data were collected as part of the DOE-funded Subsurface Technology and Engineering R&D (SubTER) project to advance imaging and characterization of geothermal permeability. ...
Lord, N. et al University of Wisconsin-Madison
Jan 05, 2016
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
BUTTER Empirical Deep Learning Dataset
The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...
Tripp, C. et al National Renewable Energy Laboratory
May 20, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible