Estimating Solar Radiation under Cloudy Conditions for Implementation in NREL's National Solar Radiation Data Base (NSRDB)

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Monday, 5 January 2015
Yu Xie, National Renewable Energy Laboratory, Golden, CO; and M. Sengupta

Geostationary Operational Environmental Satellite (GOES) provides global and regional observations in visible and infrared channels which have been used to retrieve cloud and surface properties at a reasonably high resolution for long periods of time. This information can be used as an input to develop and update the widely used National Solar Radiation Data Base (NSRDB) distributed by the National Renewable Energy Lab (NREL). NREL recently teamed up with National Oceanic and Atmospheric Administration (NOAA) and University of Wisconsin to create an updated NSRDB using a 2-step physical approach. Step 1 identifies clear and cloudy scenes and estimates cloud properties using algorithms from the PATMOS-X heritage. Step 2 estimates solar radiation using the information from Step 1 and a radiative transfer model with other ancillary information. This study presents results of an effort to understand the uncertainties in the retrieved cloud products and their impact on the estimation of surface radiation. The Rapid Radiative Transfer Model (RRTM) is used to simulate global horizontal (GHI) and direct normal irradiance (DNI) at the surface with satellite retrieved cloud properties as inputs. The simulations are compared against surface measurements of solar radiation at the SURFRAD sites. We also explore the potential ways to improve the radiative transfer model for estimating solar resource at the surface.