Reducing cloud contamination in aerosol optical depth (AOD) measurements

Abstract

We propose a new cloud screening method for sun photometry that is designed to effectively filter thin clouds. Our method is based on a k-nearest-neighbour algorithm instead of scanning time series of aerosol optical depth. Using 10 years of data from a precision filter radiometer in Innsbruck, we compare our new method and the currently employed screening technique. We exemplify the performance of the two routines in different cloud conditions. While both algorithms agree on the classification of a data point as clear or cloudy in a majority of the cases, the new routine is found to be more effective in flagging thin clouds. We conclude that this simple method can serve as a valid alternative for cloud detection, and we discuss the generalizability to other observation sites.