Due to the well-defined vertical profile of O2 in the atmosphere, the strong A-band (757-774 nm) has long been used to estimate vertical distributions of aerosol/cloud from space. We extend this approach to include part of the O2 B-band (684-688 nm) as well. SCIAMACHY onboard ENVISAT is the first instrument to provide spectral data at moderate resolution (0.2-1.5 nm) in the UV/VIS/NIR including both the O2 A- and B-bands. Using SCIAMACHY specifications, we make combined use of these bands in an optimal estimation algorithm. Theoretical studies show that our algorithm is applicable both over bright and dark surfaces for the retrieval of a lognormal approximation of the vertical profile of particulate matter, in addition to its optical thickness. Synthetic studies and information content analyses prove that such a combined use provides additional information on the vertical distribution of atmospheric scatterers, attributable to differences in the absorption strengths of the two bands and their underlying surface albedos.
Due to the high computational cost of the retrieval, we restrict application to real data to a case study over Kanpur through the year 2003. Comparison with AERONET data shows a commonly observed seasonal pattern of haziness, manifesting a correlation coefficient of r = 0.92 for non-monsoon monthly mean AOTs. The retrieved particulate optical thickness is found to be anti-correlated with the relative contrast of the Lambertian equivalent reflectivity (LER) at 682 nm and 755 nm by a coefficient of 0.788, confirming the hypothesis made in Sanghavi et al. (2010).
Our case study demonstrates a stable physics-based retrieval of particulate matter using only SCIAMACHY data. The feasibility of our approach is enhanced by the information provided by measurements around the O2 B-band in addition to the A-band. Nonetheless, operational application to SCIAMACHY data remains challenged by radiometric uncertainties, yielding simultaneous retrieval of particle microphysical parameters impracticable and leading to over-reliance on climatological data. Addressing these issues in future instruments similar to SCIAMACHY, coupled with computational resources and speed-up of the current line-by-line radiative transfer calculations, can allow our approach to be extended to the global scale, particularly as it is not limited to dark surfaces.
