Satellite-based Solar Resource for High Latitudes from the NSRDB

The National Renewable Energy Laboratory’s (NREL’s) National Solar Radiation Database (NSRDB), sponsored by the Department of Energy (DOE) Solar Energy Technologies Office (SETO), is one of the most well-known solar resource datasets covering the contiguous United States (CONUS) and a growing list of international locations. For continuous observation of solar radiation, the latest NSRDB utilizes high-resolution data from geostationary satellites, Geostationary Operational Environmental Satellite-16 (GOES-16) and GOES-17, which cover the Western Hemisphere from 60° North to 60° South latitude including the CONUS, South Canada, Central America, and South America. Due to the design of the GOES satellite constellations and the consequent spatial coverage, solar radiation data for the Arctic region are unavailable from the current NSRDB.

The Arctic region has significant solar resource and high electricity prices, making it a favorable area to develop PV projects. Although solar radiation is low in winter, sunlight during the summer months last for 18-24 hours a day. The snow reflection in spring and fall also helps increase solar energy production. Moreover, electricity prices in the Arctic region are typically much higher than the national average, which creates a great deal of interest in solar energy technologies. Therefore, it is crucial to extend the current NSRDB to provide high-resolution solar resource information for this region.

Based on the available polar-orbiting satellite data and NREL’s modeling capability, we have extended the NSRDB to provide high-resolution solar resource data for the Arctic region. The products of NASA’s multi-sensor Global Cloud and Radiance composites have been employed to provide the cloud properties for the region. Cloud properties are retrieved by using the CERES cloud retrieval algorithm. The NREL’s Physical Solar Model (PSM) has been applied to compute global horizontal irradiance (GHI) and direct normal irradiance (DNI) for the period from 2014 to 2024. Validation using surface observations indicates the mean bias error (MBE) for GHI and DNI is below 5% and 10%, respectively, under all sky conditions.