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Satellite remote sensing products such as Meteosat Second Generation (MSG) Infra Red (IR) dust index and Ozone Monitoring Instrument (OMI) Aerosol Index (AI) are commonly used to infer dust source areas. Here, two methods for dust source identification are compared, (1) a "back-tracking" method applied to 15-minute MSG IR dust index, and (2) a "frequency" method applied to daily OMI AI and daily MODIS DeepBlue Aerosol Optical Thickness (AOT) data.

Using the "back-tracking" method, dust source areas are inferred by tracking individual dust plumes back to their place of origin, allowed by the high temporal resolution of the MSG images. OMI AI and MODIS Deep Blue AOT products are available on daily resolution only, which does not allow for back-tracking of individual dust plumes. Thus, dust source areas are identified by relating the frequencies of occurrence of high dust loadings to source areas.

The spatial distribution of inferred dust source areas not only from the two methods, but also from the two satellite products, shows significant differences. The MSG back-tracking method highlights frequent dust emission from sources within complex terrain, while frequencies of high OMI AI values emphasise topographic basins as important dust source areas. Dust source areas retrieved from DeepBlue AOTs are generally further south towards the Sahel region. This study shows that the temporal resolution of satellite dust products is a key issue in identifying dust source areas. Both, the spatial distribution of dust sources and their annual cycle strongly depend on the acquisition time related to the start of dust emission. (C) 2012 Elsevier Inc. All rights reserved.