| Summary: | The Moderate-resolution Imaging Spectroradiometer (MODIS) onboard NASA’s Terra and Aqua satellites have provided a global distribution of aerosols. The space-based inversion of MODIS measurements requires assumption about the surface and aerosol properties, both are highly heterogeneous in space and time. This thesis has investigated the role of surface reflectance and aerosol properties on the retrieval of aerosols from MODIS over the Indian region. The aerosol properties retrieved by MODIS including total aerosol optical depth (AOD) and aerosol fine mode fraction (AFMF, fractional contribution of fine mode aerosols in the total AOD) were compared with that obtained from Aerosol Robotic Network (AERONET) at Kanpur (26.45◦N,80.35◦E), Indo-Gangetic Basin, northern India. This region is a special region for the study of aerosols as it offers strong aerosol seasonality, where the region is influenced by dust aerosols during pre-monsoon (March to June) and dominated by the fine mode particles in winter (November to February). The MODIS Collection 004 (C004) aerosol products systematically overestimated AOD in the presence of dust and underestimated when fine particles were dominant. The errors in the retrieval of dust AOD were correlated with the apparent reflectance at 2.1 µm, from which the surface reflectance in the visible channels (0.47 µm and 0.66 µm) were estimated using the “dark target” spectral correlation method. The error in the retrieval of AOD were also found to be large in the scattering angle range 120◦150◦, where the scattering properties of the non-spherical dust aerosols differ from that of the assumed spherical particles. AFMF of C004 was found to be highly biased to fine mode at Kanpur. The Collection 005 (C005) aerosol retrieval of the second-generation aerosol algorithm, however, showed improved retrieval of spectral AOD, which is likely to be attributed to the use of updated aerosol models and parameterized surface reflectance. In contrast to the C004 products, fine AOD and fine-model ...
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