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A new algorithm to estimate sky condition based on 5 minutes-averaged values of clearness index and relative optical air mass |
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| Authors: | H F Assunção J F Escobedo A P Oliveira |
| Institution: | Department of Geography, Federal University of Goiás, Campus of Jataí, Jataí, Goiás, Brazil Department of Natural Resources, School of Agronomic Science, University of State of S?o Paulo, Botucatu, S?o Paulo, Brazil Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences, University of S?o Paulo, S?o Paulo, Brazil |
| Abstract: | Summary This work describes a new algorithm to characterize sky condition in intervals of 5 min using four categories of sun exposition: apparent sun with cloud reflection effects; apparent sun without cloud effects; sun partially concealed by clouds; and sun totally concealed by clouds. The algorithm can also be applied to estimate hourly and daily sky condition in terms of the traditional three categories: clear, partially cloudy and cloudy day. It identifies sky conditions within a confidence interval of 95% by minimizing local climate and measurement effects. This is accomplished by using a logistic cumulative probability function to characterize clear sky and Weibull cumulative probability function to represent cloudy sky. Both probability functions are derived from frequency distributions of clearness index, based on 5 minutes-averaged values of global solar irradiance observed at the surface during a period of 6 years in Botucatu, Southeastern of Brazil. The relative sunshine estimated from the new algorithm is statistically comparable to the one derived from Campbell-Stocks sunshine recorder for both daily and monthly values. The new method indicates that the highest frequency of clear sky days occurs in Botucatu during winter (66%) and the lowest during the summer (38%). Partially cloudy condition is the dominant feature during all months of the year. |
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