329 CM SAF's cloud dataset CLAAS derived from SEVIRI on geostationary Meteosat Second Generation satellites

Wednesday, 9 July 2014
Anke Kniffka, Deutscher Wetterdienst, Offenbach, Germany; and M. Stengel, J. F. Meirink, and R. Hollmann

EUMETSAT's Satellite Application Facility on Climate Monitoring (CM SAF) uses space-based observations to provide satellite-derived geophysical parameter data sets suitable for research on smaller time-scales as well as climate monitoring. From the geostationary Meteosat Second Generation (MSG) satellites a complete series of datasets was derived consisting of top of atmosphere parameters, radiation fluxes and cloud parameters as well as surface albedo.

One of the latest releases is CLAAS (CLoud property dAtAset using SEVIRI, doi: 10.5676/EUM\_SAF\_CM/CLAAS/V001), which comprises micro and macrophysical cloud properties from geostationary MSG1 and MSG2 satellites, covering the time span 01/2004 - 12/2011. Along with this, a surface albedo and a radiation dataset have also been composed based on the same measurements as well as a top of atmosphere dataset using also GERB data.

CLAAS was derived from measurements of SEVIRI (Spinning Enhanced Visible and Infrared Imager), where SEVIRI radiances were calibrated against MODIS in channels 0.6, 0.8 and 1.6 µm.

CLAAS was produced with the following features: The data is available as daily and monthly means, as well as monthly mean diurnal cycles and monthly histograms. They possess a high spatial and temporal resolution; 0.05° • 0.05° for the daily and monthly averages from hourly data, the latter are available on SEVIRI's 3 • 3 km² grid. The quality of the derived cloud parameters is assessed in a validation framework including satellite-based reference observations (e.g. CALIOP, MODIS, AMSR-E) and ground-based data (e.g. LIDAR and spectroradiometer measurements as well as synoptic data).

With CM SAF's MSG-based datasets numerous applications on various temporal and spatial scales are possible. i.e. related to cloud radiation interactions, climate monitoring at weather services, over model evaluation as well as analysis of the diurnal evolution of atmospheric parameters can be accomplished. Additionally a climate dataset of the cloud mask derived from SEVIRI measurements was processed in full temporal and spatial resolution. The resulting cloud mask time-series will serve as input for further reprocessing of land surface and ocean analysis from MSG data where highest temporal resolution is needed, but will be available also directly from CM SAF for climate studies.

This presentation introduces the SEVIRI datasets and presents an overview about their features and applicabilities.

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