Cloud type separation using local correlation between visible and infrared satellite images

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Abstract
Radiance fields provided by geostationnary satellites are fundamental for the knowledge of the spatial heterogeneity and life cycle of clouds and cloud systems. However, detection and analysis of the cloud cover properties from VIS and/or JR radiance field is not obvious 1,2 and numerous methods, giving sometimes quite different results, have been proposed 3. In the present paper, we introduce a new parameter in the classification scheme we developed before 45 : the slope of the regression line between visible and infrared radiances. Moreover, studying the time evolution of cloud classes requires to ensure the classification consistency from one hour to the other. A new way of initializing the classification process is proposed and tested on a time series of Meteosat radiance fields taken over North Atlantic and West Europe during the 1989 ICE experiment. The 10 day cloud classification built is compared with the Cl climatology cloud cover. The time persistence of high clouds is studied and maps of the frequency of occurence of different cloud classes are built from the previous analysis. After isolating high cloud cells on the classified images, a description of the shape and radiative properties of these individual cells is undertaken. Preliminary results on cloud cell size distribution are presented.

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