The Next-Generation Satellite Product for NREL's National Solar Radiation Data Base (NSRDB)

Providing publicly accessible high-quality and long-term satellite based solar resource datasets for the US reduces barriers to solar grid penetration. There are two widely used approaches to derive solar resource from satellites (a) an empirical approach that relates ground based observations with satellite measurements and (b) a physics based approach that considers the radiation received at the satellite and create retrievals to estimate clouds and surface radiation. While empirical methods have been traditionally used for computing surface radiation the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is an operational physical model from NOAA that computes GHI using the visible and infrared channel measurements from the GOES satellites. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. NREL, University of Wisconsin and NOAA have recently collaborated to adapt GSIP to create a high temporal and spatial resolution dataset. The product initially generates the cloud properties using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms while the global horizontal radiation (GHI) and diffuse horizontal radiation (DHI) are calculated using SASRAB. Comparison with ground sites resulted in the finding that the satellite based surface radiation suffered from a significant low-bias. To remove this bias we tested three new radiative transfer algorithms that required aerosol optical depth and precipitable water vapor as inputs. These experiments showed significant improvement in the clear sky radiation (Figure 1). We will present an outline of the development of this new version of the NSRDB, a validation of the product and future plans for enhancement and improvement.