Combining CALIPSO and Meteosat Images to Study the Distribution of Atmospheric Dust

The identification and tracking of atmospheric dust is important to many disciplines due to its impact on the climate and ecological system. Sensors on-board existing imaging satellites such as MSG and CALIPSO provide good horizontal and vertical resolution, respectively, and therefore the resolution of any dust products derived solely from one sensor will be limited in the same manner as the sensor. We propose a new method of identifying dust distributions in the atmosphere using data from two separate satellite sources, the SEVIRI on-board MSG and the CALIPSO lidar. The approach employs a supervised classification method using texture data derived from a bank of Gabor filters. Once the dust has been identified, the SEVIRI data is augmented with vertical CALIPSO data to produce a 2frac12D dust cloud top height distribution.