Automated cloud screening algorithm for MFRSR data

A new automated cloud screening algorithm for ground-based sun-photometric measurements is described and illustrated on examples of real (MFRSR) and simulated data. The algorithm uses single channel direct beam measurements and is based on variability analysis of retrieved optical thickness. To quantify this variability the inhomogeneity parameter e is used. This parameter is commonly used for cloud remote sensing and modeling, but not for cloud screening. In addition to this an adjustable enveloping technique is applied to control strictness of the selection method. The key advantages of this technique are its objectivity, computational efficiency and the ability to detect short clear-sky intervals under broken cloud cover conditions. Moreover, it does not require any knowledge of the instrument calibration. The performance of the method has been compared with that of AERONET cloud screening algorithm.