Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

Summary

The U.S. Department of Energy's PACES project aims to help the energy sector plan for climate change by addressing uncertainties in power planning. The approach involves selecting and downscaling global climate model data using generative machine learning (Sup3rCC) to reflect climate change impacts on power systems. This report details the selection of five specific climate models and one emissions scenario from the CMIP6 archive for use in this ongoing project.

Key Facts

Source Document

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