CAELUS: Classification of sky conditions from 1-min time series of global solar irradiance using variability indices and dynamic thresholds

Abstract

Precise sky classification as a function of cloudiness is desirable or necessary in a variety of applications. CAELUS, a novel classification algorithm that relies on various thresholds to separate all possible sky conditions into six classes, is presented here. It uses global horizontal irradiance (GHI) measurements at 1-min resolution, from which a set of four indices is derived to characterize the magnitude and temporal variability of GHI. The algorithm also requires precise estimates of 1-min GHI under hypothetical cloudless conditions, and the solar zenith angle (limited to a maximum of 85°). Using 1-min GHI measurements from 54 BSRN high-quality radiometric stations, which cover all five primary Köppen-Geiger climate classes, CAELUS is used here to classify their sky conditions. The classification results, including the distribution of sky classes and the transitions between consecutive sky classes, are found consistent with the known characteristics of each primary Köppen-Geiger climate. Moreover, in each climate class, the detection of 1-min cloudless situations is found comparable to that provided by two dedicated and state-of-the-art methods—Reno-Hansen and Bright-Sun.