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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 4, issue 2
Atmos. Meas. Tech., 4, 319–337, 2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 4, 319–337, 2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 Feb 2011

Research article | 22 Feb 2011

Synergetic cloud fraction determination for SCIAMACHY using MERIS

C. Schlundt, A. A. Kokhanovsky, W. von Hoyningen-Huene, T. Dinter, L. Istomina, and J. P. Burrows C. Schlundt et al.
  • Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany

Abstract. Since clouds play an essential role in the Earth's climate system, it is important to understand the cloud characteristics as well as their distribution on a global scale using satellite observations. The main scientific objective of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) onboard the ENVISAT satellite is the retrieval of vertical columns of trace gases.

On the one hand, SCIAMACHY has to be sensitive to low variations in trace gas concentrations which means the ground pixel size has to be large enough. On the other hand, such a large pixel size leads to the problem that SCIAMACHY spectra are often contaminated by clouds. SCIAMACHY spectral measurements are not well suitable to derive a reliable sub-pixel cloud fraction that can be used as input parameter for subsequent retrievals of cloud properties or vertical trace gas columns. Therefore, we use MERIS/ENVISAT spectral measurements with its high spatial resolution as sub-pixel information for the determination of MerIs Cloud fRation fOr Sciamachy (MICROS). Since MERIS covers an even broader swath width than SCIAMACHY, no problems in spatial and temporal collocation of measurements occur. This enables the derivation of a SCIAMACHY cloud fraction with an accuracy much higher as compared with other current cloud fractions that are based on SCIAMACHY's PMD (Polarization Measurement Device) data.

We present our new developed MICROS algorithm, based on the threshold approach, as well as a qualitative validation of our results with MERIS satellite images for different locations, especially with respect to bright surfaces such as snow/ice and sands. In addition, the SCIAMACHY cloud fractions derived from MICROS are intercompared with other current SCIAMACHY cloud fractions based on different approaches demonstrating a considerable improvement regarding geometric cloud fraction determination using the MICROS algorithm.

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