In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level–2 products) and global gridded products at a latitude and longitude resolution of 1° (Level–3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level–2 and –3 results will be presented.
Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including (i) surface reflectance, (ii) vegetation indices, leaf area index, and FPAR, (iii) albedo and nadir BRDF-adjusted reflectance, (iv) normalized water-leaving radiance, (v) chlorophyll-a concentration, and (vi) sea surface temperature.
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