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CLAAS-2: CM SAF CLoud property dAtAset using SEVIRI - Edition 2

This paper is available in a repository.
This paper is available in a repository.

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Abstract

The CLAAS-2 record provides cloud properties derived from the SEVIRI sensor onboard METEOSAT second generation (MSG) satellites. This second edition is the improved and extended follow-up of the first version of the record (Stengel et al., 2014; CLAAS-1 DOI:10.5676/EUM_SAF_CM/CLAAS/V001). In order to ensure a homogeneous data basis, the solar SEVIRI channels of MSG-1, MSG-2 and MSG-3 were intercalibrated (Meirink et al, 2013) with MODIS Aqua before applying the cloud retrievals. CLAAS-2 features 12 years (2004-2015) of cloud mask/type, cloud top temperature/pressure/height, cloud phase as well as cloud microphysical properties such as optical thickness, effective droplet radius and cloud water path. The data are available on native SEVIRI resolution, i.e. 15 minutes repeat cycle and 3km (nadir) to 11km (edge of the field of view) spatial resolution. In addition, spatio-temporal averages of the above mentioned cloud properties are included: Daily and monthly averages and monthly histograms on a 0.05° x 0.05° grid as well as monthly mean diurnal cycles on a 0.25° x 0.25° grid. The advancements compared to CLAAS-1 (DOI:10.5676/EUM_SAF_CM/CLAAS/V001) are for example: (1) extended MSG measurement record used with better calibration, (2) improvements made to the retrieval algorithm leading to products with higher quality and (3) increased temporal resolution (15 Minutes). A summary on the CLAAS-2 characteristics and a comprehensive evaluation of the results are currently documented in Benas et al. (2016). Along with the data, a comprehensive documentation including user guide, algorithm descriptions, reprocessing layout and extensive validation studies, is provided. With CLAAS-2, regional and large scale cloud processes at temporal scales of minutes to years can be studied. SEVIRI-based surface radiation products, which were part of CLAAS-1, are now released in a separate dataset (SARAH-2).