%0 Journal Article
%T Validation of the METEOSAT storm detection and nowcasting system Cb-TRAM with lightning network data ¨C Europe and South Africa
%A T. Zinner
%A C. Forster
%A E. de Coning
%A H.-D. Betz
%J Atmospheric Measurement Techniques Discussions
%D 2013
%I Copernicus Publications
%R 10.5194/amtd-6-1269-2013
%X In this manuscript, recent changes to the DLR METEOSAT thunderstorm TRacking And Monitoring algorithm (Cb-TRAM) are presented as well as a validation of Cb-TRAM against the European ground-based LIghtning NETwork data (LINET) of Nowcast GmbH and Lightning Detection Network (LDN) data of the South African Weather Service (SAWS). The validation is conducted along the well known skill scores probability of detection (POD) and false alarm ratio (FAR) on the basis of METEOSAT/SEVIRI pixels as well as on the basis of thunderstorm objects. The values obtained demonstrate the limits of Cb-TRAM in specific as well as the limits of satellite methods in general which are based on thermal emission and solar reflectivity information from thunderstorm tops. Although the climatic conditions and the occurence of thunderstorms is quite different for Europe and South Africa, the quality score values are similar. Our conclusion is that Cb-TRAM provides robust results of well-defined quality for very different climatic regimes. The POD for a thunderstorm with intense lightning is about 80% during the day. The FAR for a Cb-TRAM detected thunderstorm which is not at least close to intense lightning activity is about 50%; if the proximity to any lightning activity is evaluated the FAR is even much lower at about 15%. Pixel-based analysis shows that the detected thunderstorm object size is not indiscriminately large, but well within the physical limitations of the method. Nighttime POD and FAR are somewhat worse as the detection scheme can not use high resolution visible information. Nowcasting scores show useful values up to approximatelly 30 min.
%U http://www.atmos-meas-tech-discuss.net/6/1269/2013/amtd-6-1269-2013.pdf