A new characterization and classification method for daily sky conditions based on ground-based solar irradiance measurement data

This paper proposes a new characterization and classification method for daily sky conditions by using the daily sky clearness index (KD) and the daily probability of persistence (POPD) that can be derived from ground-based irradiance measurement data. Quality of daily solar irradiance is characterized by a newly proposed parameter, POPD. This characterized daily quality is varying and uncertain at the middle level of the quantity, but high and more certain at very high and low quantity levels. In addition, the proposed characterization method shows interesting results for KD and POPD: a statistical consistency for multiple years and similarity for their seasonal trends. The classification results also indicate an existence of dominant classes, and transitions between the dominant classes are significant for all locations. This paper also generates annual synthetic sequences of KD and POPD using a Markov approach. The generated sequences show statistical similarities with observed sequences.