This study investigates the effects of wind-blown mineral dust on the IR radiances observed by narrowband and high spectral resolution satellite sensors. To adequately compute the monochromatic radiances in dust laden conditions, we developed a radiative transfer code LBL-MS (Line-By-Line with Multiple Scattering) by combining a modified line-by-line algorithm and a discrete-ordinate technique. The LBL-MS code enables computation of the monochromatic radiances and irradiances correctly accounting for gaseous absorption and for both absorption and multiple-scattering by atmospheric aerosols. We also developed high resolution spectral optical models of dust mixtures required for computations of monochromatic radiances. Several external mixtures of individual minerals as well as mixtures of aggregates representative of Asian and Saharan dust sources were considered. Simulations were performed for various atmospheric conditions characterized by different temperature and water vapor profiles allowing the loading of dust and its vertical distribution to vary.

We demonstrate that the presence of dust decreases the brightness temperature observed by satellite sensors depending mainly on dust burden, vertical distribution and composition. The moderate dust loading can result in a decrease of brightness temperature by 5-10 K in the IR window over the oceans. Our analysis revealed that narrowband sensors (e.g., MODIS, AVHRR, GOES) have different sensitivity to dust composition depending on a particular channel. In addition, we found that dust has a unique spectral radiative signature (termed here an “inverse slope”) which separates the IR radiative effect of dust from that of clouds and atmospheric gases. This funding is supported by the data from the NPOESS Airborne Sounder Testbed Interferometer (NAST-I) acquired during test flights over the Yellow Sea in Spring of 2001.

We conclude that narrowband satellite sensors are capable of detecting dust but the quantitative characterization of dust properties requires the high spectral resolution observations. In turn, dust must be included in atmospheric correction algorithms if the retrievals of the sea surface temperature, atmospheric water vapor and trace gases from the thermal IR radiances are to be of high accuracy.