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  Cloud detection and classification based on MAX-DOAS observations

Wagner, T., Apituley, A., Beirle, S., Dörner, S., Friess, U., Remmers, J., et al. (2014). Cloud detection and classification based on MAX-DOAS observations. Atmospheric Measurement Techniques, 7(5), 1289-1320. doi:10.5194/amt-7-1289-2014.

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 Creators:
Wagner, T.1, Author           
Apituley, A.2, Author
Beirle, S.1, Author           
Dörner, S.1, Author           
Friess, U.2, Author
Remmers, J.1, Author           
Shaiganfar, R.1, Author           
Affiliations:
1Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society, ou_1826293              
2external, ou_persistent22              

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 Abstract: Multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations of aerosols and trace gases can be strongly influenced by clouds. Thus, it is important to identify clouds and characterise their properties. In this study we investigate the effects of clouds on several quantities which can be derived from MAX-DOAS observations, like radiance, the colour index (radiance ratio at two selected wavelengths), the absorption of the oxygen dimer O-4 and the fraction of inelastically scattered light (Ring effect). To identify clouds, these quantities can be either compared to their corresponding clear-sky reference values, or their dependencies on time or viewing direction can be analysed. From the investigation of the temporal variability the influence of clouds can be identified even for individual measurements. Based on our investigations we developed a cloud classification scheme, which can be applied in a flexible way to MAX-DOAS or zenith DOAS observations: in its simplest version, zenith observations of the colour index are used to identify the presence of clouds (or high aerosol load). In more sophisticated versions, other quantities and viewing directions are also considered, which allows subclassifications like, e.g., thin or thick clouds, or fog. We applied our cloud classification scheme to MAX-DOAS observations during the Cabauw intercomparison campaign of Nitrogen Dioxide measuring instruments (CINDI) campaign in the Netherlands in summer 2009 and found very good agreement with sky images taken from the ground and backscatter profiles from a lidar.

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 Dates: 2014
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: ISI: 000336740700010
DOI: 10.5194/amt-7-1289-2014
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Title: Atmospheric Measurement Techniques
  Abbreviation : AMT
Source Genre: Journal
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Publ. Info: Göttingen : European Geosciences Union, Copernicus
Pages: - Volume / Issue: 7 (5) Sequence Number: - Start / End Page: 1289 - 1320 Identifier: Other: 1867-1381
CoNE: https://pure.mpg.de/cone/journals/resource/1867-1381