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 only 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°). CAELUS was used to classify the sky conditions at 54 BSRN high-quality radiometric stations, which cover all five Köppen-Geiger primary climate classes, from their 1-min GHI measurements. 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 Köppen-Geiger major 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.