GFDL - Geophysical Fluid Dynamics Laboratory

Identification of anthropogenic and natural dust sources using MODIS Deep Blue level 2 data

March 9th, 2010

Figure. Distribution of natural (red shading) and anthropogenic (blue shading) FOO with αthresh = 0 and (upper left) τthresh = 0.25, (upper right) 0.5, (lower left) 0.75, and (lower right) 1, overplotted on the percentage land use (croplands and pastures) from 10% to 100% (in yellow, the lighter the color the higher the percentage of land use). The units of FOO are percentage of days satisfying the criteria by the total number of days with nonmissing MODIS data per year, and averaged from 2003 to 2006.
Figure. Distribution of natural (red shading) and anthropogenic (blue shading) FOO with αthresh = 0 and (upper left) τthresh = 0.25, (upper right) 0.5, (lower left) 0.75, and (lower right) 1, overplotted on the percentage land use (croplands and pastures) from 10% to 100% (in yellow, the lighter the color the higher the percentage of land use). The units of FOO are percentage of days satisfying the criteria by the total number of days with nonmissing MODIS data per year, and averaged from 2003 to 2006.

Identification of anthropogenic and natural dust sources using Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue level 2 data by Paul Ginoux (NOAA GFDL), Dmitri Garbuzov (Princeton U) and Christina Hsu (NASA) explores a new method to detect anthropogenic and natural dust sources from satellite data in the eastern part of West Africa. The anthropogenic contribution appears to be significant around the lake Chad, but the magnitude of these sources seem weaker than the natural sources, in particular relative to the Bodele depression.