skip to main content


Title: A unified high-resolution wind and solar dataset from a rapidly updating numerical weather prediction model

A new gridded dataset for wind and solar resource estimation over the contiguous United States has been derived from hourly updated 1-h forecasts from the National Oceanic and Atmospheric Administration High-Resolution Rapid Refresh (HRRR) 3-km model composited over a three-year period (approximately 22 000 forecast model runs). The unique dataset features hourly data assimilation, and provides physically consistent wind and solar estimates for the renewable energy industry. The wind resource dataset shows strong similarity to that previously provided by a Department of Energy-funded study, and it includes estimates in southern Canada and northern Mexico. The solar resource dataset represents an initial step towards application-specific fields such as global horizontal and direct normal irradiance. This combined dataset will continue to be augmented with new forecast data from the advanced HRRR atmospheric/land-surface model.
ORCiD logo [1] ;  [2] ;  [2]
  1. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.; Univ. of Colorado, Boulder, CO (United States). Cooperative Institute for Research in Environmental Sciences
  2. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.
Publication Date:
Grant/Contract Number:
Published Article
Journal Name:
Renewable Energy
Additional Journal Information:
Journal Volume: 102; Journal Issue: Part B; Journal ID: ISSN 0960-1481
Research Org:
Office of Oceanic and Atmospheric Research, Silver Spring, MD (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 14 SOLAR ENERGY; 17 WIND ENERGY; Wind resource; Solar resource; NWP forecast; Unified wind/solar
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1424933