Paper
19 August 2010 Validating an operational physical method to compute surface radiation from geostationary satellites
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Abstract
Models to compute global horizontal irradiance (GHI) and direct normal irradiance (DNI) have been in development over the last three decades. These models can be classified as empirical or physical based on the approach. Empirical models relate ground-based observations with satellite measurements and use these relations to compute surface radiation. Physical models consider the physics behind the radiation received at the satellite and create retrievals to estimate surface radiation. While empirical methods have been traditionally used for computing surface radiation for the solar energy industry, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is a physical model that computes DNI and GHI using the visible and infrared channel measurements from a weather satellite. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in a radiative transfer model to calculate GHI and DNI. Developed for polar orbiting satellites, GSIP has been adapted to NOAA's Geostationary Operation Environmental Satellite series and can run operationally at high spatial resolutions. This method holds the possibility of creating high quality datasets of GHI and DNI for use by the solar energy industry. We present an outline of the methodology and results from running the model as well as a validation study using ground-based instruments.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manajit Sengupta, Andrew Heidinger, and Steven Miller "Validating an operational physical method to compute surface radiation from geostationary satellites", Proc. SPIE 7773, Reliability of Photovoltaic Cells, Modules, Components, and Systems III, 77730T (19 August 2010); https://doi.org/10.1117/12.861766
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Cited by 10 scholarly publications.
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KEYWORDS
Satellites

Clouds

Solar radiation models

Solar energy

Solar radiation

Brain-machine interfaces

Spatial resolution

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