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• W2022752359 abstract "Abstract Solar radiation derived from geostationary satellite images has become an advantageous technique for solar resource characterisation over large areas. The simplest methods for estimate solar radiation from the satellite information rely on straight forward relationships between a normalised parameter of the solar irradiance (such as clearness or clear sky index) and the cloud index. This paper presents a statistical fit of this relationship (fitted and tested using data from 28 Spanish radiometric station) different from the approach used by Heliosat-2 method (Rigollier, C., Lefevre, M., Wald, L., 2004. The method Heliosat-2 for deriving shortwave solar radiation from satellite images. Solar Energy 77, 159–169), that includes local statistical measures of the cloud index distribution and the air mass. In particular, the inclusion of the local cloud index percentiles (median, first and third quartile) estimated from the whole series on each pixel improves clearly the model response, and is a way to account for the local climatological aspects of any location. The inclusion of the new explicative variables yield to practically unbiased results and the relative RMSE decrease to about 17% from the 21% result of the expression applied in the Heliosat-2 model." @default.
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• W2022752359 date "2009-04-01" @default.
• W2022752359 modified "2023-10-16" @default.
• W2022752359 title "A new statistical approach for deriving global solar radiation from satellite images" @default.
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• W2022752359 doi "https://doi.org/10.1016/j.solener.2008.09.006" @default.
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