Mapping Dust Source Regions in North Africa using MISR Satellite-Derived Cloud Motion Vectors and Aerosol Products

Transported dust has significant impacts throughout the Earth system, with effects on the energy budget, carbon cycle, ocean productivity, and CO2 exchange. To better understand and model the global dust cycle, it is important to be able to precisely identify primary dust source regions. However, areas such as North Africa, which is a major global source of transported desert dust, are sparsely populated and with few sources of ground-truth information regarding dust sources. Advances in satellite remote sensing in the past few decades, especially data from the Total Ozone Mapping Spectrometer (TOMS), has significantly improved our ability to identify source regions in North Africa, at least on a relatively coarse spatial scale. Current satellite instruments promise to yield information at much finer spatial resolution, on scales of a few to a few tens of kilometers, but accurately identifying dust sources is typically a time consuming task often requiring a human-in-the-loop approach.

Here we will describe a new, automatic method of identifying dust sources using observations from the Multi-angle Imaging SpectroRadiometer (MISR) instrument that has been acquiring data from onboard the NASA polar-orbiting Terra EOS satellite since early 2000. MISR's multiangle observations allow for the retrieval of near-instantaneous cloud motion vectors (cloud-track winds) using a stereophotogrammetric technique with a spatial resolution of 17.6 km and a vertical resolution of better than 500 m. MISR also retrieves aerosol column loading (aerosol optical depth) and particle non-sphericity at this same spatial resolution. Taken together, this information yields precise determination of the location of dust source regions, which are associated with high near-surface wind speeds, large aerosol loading, and significant non-sphericity. The combination also helps eliminate false positives that may arise from analysis of any individual dataset. We will discuss the strengths and limitations of this approach, show how the identified source regions relate to surface geomorphological features, and compare our results with those from previous studies of North African dust sources. We will also explore climatological relationships between MISR observations of transported dust and clouds over the Atlantic.