2026-04-17T02:41:57Zhttps://recercat.cat/oai/request

oai:recercat.cat:10256/76932024-06-14T09:36:29Zcom_2072_452955com_2072_2054col_2072_453063

00925njm 22002777a 4500 dc Calbó Angrill, Josep author González Gutiérrez, Josep Abel author Pagès, David author 2001 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 meteorologicalvariables, 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 http://hdl.handle.net/10256/7693 Radiació solar Núvols Clouds Meteorologia -- Observacions Meteorology -- Observations Sun -- Radiation A Method for Sky-Condition Classification from Ground-Based Solar Radiation Measurements