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 climate change scenarios. Sup3rCC is downscaled Global Climate Model (GCM) data. For example, the initial dataset "sup3rcc_conus_mriesm20_ssp585_r1i1p1f1" is downscaled from MRI ESM 2.0 for climate change scenario SSP5 8.5 and variant label r1i1p1f1. The downscaling process was performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy Resource Data (linked below as "Sup3r GitHub Repo"). The data includes both historical and future weather years, although the historical years represent the historical average climate, not the actual historical weather that we experienced. The Sup3rCC data is intended to help researchers study the impact of climate change on energy systems with high levels of wind and solar capacity. Please note that all climate change data is only a representation of the *possible* future climate and contains significant uncertainty. Analysis of multiple climate change scenarios and multiple climate models can help quantify this uncertainty.

(Link to Metadata) Wind speed predictions at 30m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account geophysical inputs such as elevation, land use, and vegetation. The information was produced by TrueWind Solutions using their Mesomap system. This work was commissioned by the Massachusetts Technology Collaborative, in conjunction with the Connecticut Clean Energy Fund and Northeast Utilities, and the results have been validated by NREL (National Renewable Energy Laboratory).

(Link to Metadata) Wind speed predictions at 70m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account geophysical inputs such as elevation, land use, and vegetation. The information was produced by TrueWind Solutions using their Mesomap system. This work was commissioned by the Massachusetts Technology Collaborative, in conjunction with the Connecticut Clean Energy Fund and Northeast Utilities, and the results have been validated by NREL (National Renewable Energy Laboratory).