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- W2172655276 abstract "Identification of clouds from satellite images is now a routine task. Observation of clouds from the ground, however, is still needed to acquire a complete description of cloud conditions. Among the standard meteorological variables, solar radiation is the most affected by cloud cover. In this note, a method for using global and diffuse solar radiation data to classify sky conditions into several classes is suggested. A classical maximum-likelihood method is applied for clustering data. The method is applied to a series of four years of solar radiation data and human cloud observations at a site in Catalonia, Spain. With these data, the accuracy of the solar radiation method as compared with human observations is 45% when nine classes of sky conditions are to be distinguished, and it grows significantly to almost 60% when samples are classified in only five different classes. Most errors are explained by limitations in the database; therefore, further work is under way with a more suitable database." @default.
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- W2172655276 date "2001-12-01" @default.
- W2172655276 modified "2023-10-01" @default.
- W2172655276 title "A Method for Sky-Condition Classification from Ground-Based Solar Radiation Measurements" @default.
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- W2172655276 doi "https://doi.org/10.1175/1520-0450(2001)040<2193:amfscc>2.0.co;2" @default.
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