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Roebeling et al. 2006
Roebeling, R.A., Feijt, A.J. and Stammes, P. (2006). Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17. Journal of Geophysical Research 111: doi: 10.1029/2005JD006990. issn: 0148-0227.

In the framework of the Satellite Application Facility on Climate Monitoring (CM-SAF) an algorithm was developed to retrieve Cloud Physical Properties (CPP) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (METEOSAT-8) and the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellites. This paper presents the CPP algorithm and determines if SEVIRI can be used together with AVHRR to build a consistent and accurate data set of cloud optical thickness (COT) and cloud liquid water path (CLWP) over Europe for climate research purposes. After quantifying the differences in 0.6 and 1.6 ¿m operational calibrated reflectances of SEVIRI and AVHRR, a recalibration procedure is proposed to normalize and absolutely calibrate these reflectances. The effects of recalibration, spatial resolution, and viewing geometry differences on the SEVIRI and AVHRR cloud property retrievals are evaluated. The intercomparison of 0.6 and 1.6 ¿m operationally calibrated reflectances indicates ~6 and ~26% higher reflectances for SEVIRI than for AVHRR. These discrepancies result in retrieval differences between AVHRR and SEVIRI of ~8% for COT and ~60% for CLWP. Owing to recalibration these differences reduce to ~5%, while the magnitude of the median COT and CLWP values of AVHRR decrease ~2 and ~60% and the SEVIRI values increase ~10 and ~55%, respectively. The differences in spatial resolution and viewing geometry slightly influence the retrieval precision. Thus the CPP algorithm can be used to build a consistent and high-quality data set of SEVIRI and AVHRR retrieved cloud properties for climate research purposes, provided the instrument reflectances are recalibrated, preferably guided by the satellite operators.

BACKGROUND DATA FILES

Abstract

Keywords
Global Change, Remote sensing, Atmospheric Composition and Structure, Cloud physics and chemistry, Global Change, Climate variability (1635, 3305, 3309, 4215, 4513), Atmospheric Composition and Structure, Instruments and techniques
Journal
Journal of Geophysical Research
http://www.agu.org/journals/jb/
Publisher
American Geophysical Union
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