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| Titel |
Cloud detection and classification based on MAX-DOAS observations |
| VerfasserIn |
T. Wagner, A. Apituley, S. Beirle, S. Dörner, U. Frieß, J. Remmers, R. Shaiganfar |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 7, no. 5 ; Nr. 7, no. 5 (2014-05-19), S.1289-1320 |
| Datensatznummer |
250115758
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| Publikation (Nr.) |
 copernicus.org/amt-7-1289-2014.pdf |
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| Zusammenfassung |
| 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 O4 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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