Updated version of the MAX-DOAS cloud classification algorithm and its validation

Characterizing the light path through the atmosphere is a fundamental challenge in Differential Optical Absorption Spectroscopy (DOAS). Clouds strongly influence the light paths and thus the interpretation and further use of the measurements. In this context, it is important to receive information about the cloud cover in the field of view of the Multi-AXis-DOAS (MAX-DOAS) instrument. A method for extracting this information from the measured spectra themselves was introduced by Wagner et al. (2014, 2016). They developed an algorithm to determine and classify sky conditions based on the combination of CI (Colour Index) and O4 absorption obtained from MAX-DOAS spectra. In this study, the improvements of an updated version of this algorithm are presented and validated by comparison with a series of observations with camera measurements of sky conditions at several stations. In order to process the large number of observations, a tool was implemented to enable rapid categorization of the camera images.