@misc{6509d6e6aa6e4d67bed86d07b3d4b298,
title = "Development of A High-Resolution Dataset for Solar Resource Adequacy Studies",
abstract = "High-resolution, long-term solar dataset is essential for characterizing the variability of solar energy resources and for informing strategies that ensure grid reliability and resilience in grid systems with high levels of solar energy integration. We present the development of a new 4-km, hourly Earth system dataset for the contiguous United States (CONUS), using a statistical downscaling approach that integrates the National Solar Radiation Database (NSRDB) with regional Earth system model projections. The new high-resolution Earth system dataset includes key variables - GHI, DNI, DHI, surface air temperature, and wind speed - under two future scenarios. Preliminary results show a reasonable agreement with NSRDB observations, with nBias less than 1\% for GHI across CONUS. The dataset is expected to support in-depth analyses of extreme weather impacts and provide input to resource adequacy for future energy systems with diverse generation sources.",
keywords = "downscaling, ESM, high-resolution resource data, resource adequacy, solar",
author = "Manajit Sengupta and Jaemo Yang and Aron Habte and Yu Xie and Maggie Bailey and Douglas Nychka and Soutir Bandyopadhyay",
year = "2025",
doi = "10.2172/3023371",
language = "American English",
series = "Presented at the 53rd IEEE Photovoltaic Specialists Conference (PVSC 53), 8-13 June 2025, Montreal, Canada",
type = "Other",
}