High-Resolution Image

A new satellite algorithm has been developed to retrieve aerosol optical thickness (AOT) and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels and the aerosol signal can be more readily separated. The cover figure shows the 490 nm AOT retrieved by the Deep Blue algorithm over the Sahara Desert and Arabian Peninsula using measurements from the SeaWiFS instrument for 25-28 February, 2000. The results are overlaid onto the MODIS "Blue Marble" image (which represents the cloud-free RGB signature of the earth's surface after atmospheric correction). The opacity of the AOT depends on the dust loading; the larger the loading, the more opaque the image. Two types of gaps can be seen, the first due to the orbital gaps in the coverage of the SeaWiFS instrument, the second due to effective screening by the algorithm of cloud features. The evolution of three main dusts feature can be seen during this time period: 1) a dust storm developing over the western Sahara, flowing off the coast of Mauritania out over the Atlantic and curling back toward the western coast of the Iberian Peninsula; 2) a small, dense plume of dust developing in the low-lying region where the border of Mali, Niger, and Algeria meet; and 3) dust from the Bodele Depression north of Lake Chad picking up in intensity over the four days.

For more information, see Aerosol Properties Over Bright-Reflecting Source Regions, by N. C. Hsu, S. C. Tsay, M. D. King, and J. R. Herman, IEEE Trans. Geosci. Remote Sens., 42 (3), 557-569, 2004.