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 Global Climate Model (GCM) data. 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 climate, not the actual historical weather that we experienced. You cannot use Sup3rCC data to study historical weather events, although other sup3r datasets may be intended for this.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.

《考虑气候变化影响的可再生能源资源超分辨率数据集》（Sup3rCC）系一套集合，包含连续美国地区的4公里分辨率每小时风速、太阳能、温度、湿度和气压场数据，数据覆盖了多种气候变化情景。Sup3rCC数据源自全球气候模型（GCM）的降尺度处理。降尺度过程采用了名为sup3r的生成式机器学习方法（Super-Resolution for Renewable Energy Resource Data，以下简称“Sup3r”），具体方法链接见下文“Sup3r GitHub Repo”。该数据集涵盖了历史与未来气象年数据，其中历史年数据代表历史气候而非实际经历的历史天气。请注意，Sup3rCC数据不适用于研究历史天气事件，尽管其他sup3r数据集可能旨在进行此类研究。Sup3rCC数据旨在协助研究人员研究气候变化对高风速和太阳能容量的能源系统的影响。需特别指出，所有气候变化数据仅对未来可能气候的表征，且含有显著的不确定性。分析多个气候变化情景及多个气候模型有助于量化这种不确定性。