EGU23-8101, updated on 03 Jan 2024
https://doi.org/10.5194/egusphere-egu23-8101
EGU General Assembly 2023
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Validation of a MAX-DOAS instrument-based cloud classification algorithm

Lucas Reischmann, Steffen Ziegler, Steffen Beirle, Vinod Kumar, Sebastian Donner, and Thomas Wagner
Lucas Reischmann et al.
  • Max Planck Institute for Chemistry , Satellite Remote Sensing, Germany (l.reischmann@mpic.de)

A major challenge in Differential Optical Absorption Spectroscopy (DOAS) is the characterization of the light path. For the determination of the light path length, cloud conditions are essential. While instruments like a LIDAR/ceilometer provide information on cloud base height in zenith direction, it is often quite challenging to obtain information on cloud coverage in the line of sight of a Multi-Axes-DOAS (MAX-DOAS) instrument.

In this study, we apply an existing cloud classification algorithm using combined information from the colour index and the O4 slant column density (Wagner et al., 2013) on spectra recorded by a MAX-DOAS instrument. In order to validate the algorithm, a MAX-DOAS with camera measurements of the sky conditions carried out at the Max Planck Institute for Chemistry in Mainz for several months. The results of the cloud classification algorithm are compared to the recordings of the cameras in order to analyse the performance of the algorithm.

How to cite: Reischmann, L., Ziegler, S., Beirle, S., Kumar, V., Donner, S., and Wagner, T.: Validation of a MAX-DOAS instrument-based cloud classification algorithm, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8101, https://doi.org/10.5194/egusphere-egu23-8101, 2023.