Sup3rCC

Released to the public as part of the Department of Energy&#39;s Open Energy Data Initiative, these data represent a serially complete collection of hourly 4km wind, solar, temperature, humidity, and pressure fields for the Continental United States under climate change scenarios.Sup3rCC is downscaled Global Climate Model (GCM) data. For example, the initial file set tagged &quot;sup3rcc_conus_mriesm20_ssp585_r1i1p1f1&quot; is downscaled from MRI ESM 2.0 for climate change scenario SSP5 8.5 and variant label r1i1p1f1. The downscaling process is performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy Resource Data. The data includes both historical and future weather years, although the historical years represent the historical average climate, not true historical weather. The Sup3rCC data is intended to help researchers study the impact of climate change on energy systems with high levels of wind and solar power generation. Please note that all climate change data is only a representation of the <em>possible</em> future climate and contains significant uncertainty. Analysis of multiple climate change scenarios and multiple climate models can help quantify this uncertainty.

作为美国能源部开放能源数据计划的一部分公开发布，本数据集构成了一个序列完整的小时级4公里风速、太阳能、温度、湿度和气压场集合，该集合反映了在气候变化情景下的美国大陆。Sup3rCC是对全球气候模型（GCM）数据进行降尺度的产物。例如，标记为“sup3rcc_conus_mriesm20_ssp585_r1i1p1f1”的初始文件集，是从MRI ESM 2.0模型中针对气候变化情景SSP5-8.5及其变体标签r1i1p1f1进行降尺度处理得到的。降尺度过程采用了一种名为sup3r的生成式机器学习方法，即用于可再生能源资源数据超分辨率的sup3r方法。数据集包含历史和未来的气象年份，尽管历史年份代表的是历史平均气候，而非真实的历史天气。Sup3rCC数据旨在协助研究人员研究气候变化对高度依赖风能和太阳能发电的能源系统的影响。请注意，所有气候变化数据仅是对未来气候的潜在表征，并包含显著的不确定性。分析多个气候变化情景和多个气候模型有助于量化这种不确定性。