P2.22 MISR satellite radiances and the inference of global aerosol properties

Wednesday, 30 June 2010
Exhibit Hall (DoubleTree by Hilton Portland)
Michael J. Garay, Raytheon Corporation, Pasadena, CA; and O. V. Kalashnikova and D. J. Diner

The Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite continues to produce global cloud and aerosol information with a data record extending over 10 years. MISR's unique multi-angle and multi-spectral approach provides sensing capabilities not previously available from space-borne platforms on a routine basis. In comparisons with ground-based AERONET sensors MISR has demonstrated the ability to retrieve aerosol amount (optical depth) and shown sensitivity to aerosol particle type on a global basis, including over bright land surfaces. MISR's operational aerosol retrieval relies on a set of aerosol mixtures that is utilized globally in all seasons over both land and ocean.

We will describe some aspects of the current MISR operational aerosol product, including sensitivity to particle type, and examine avenues being explored for more fully exploiting the instrument's sensitivity, particularly over the oceans. We will also demonstrate the effects of vary viewing geometries, which depend on latitude and season, and discuss how this affects the information available to the aerosol retrieval algorithm. Finally, through radiative transfer simulations and carefully selected case studies performed in regions with appropriate suborbital measurements, we will show how the MISR radiances can be used to directly infer the optical properties of real aerosols. For instance, when the true characteristics of the aerosol are unknown, it is not always possible to find an appropriate match within the existing set of MISR aerosol mixtures, which covers and extensive yet limited solution space due to the look-up table approach that is currently employed. However, it will be shown that in certain circumstances the MISR radiances provide information on the particle phase function that can be exploited directly to infer certain characteristics of the unknown aerosol. Such an approach is particularly relevant in regions that are challenging for satellite remote sensing, such as Southeast Asia, where high humidity and complex aerosol interactions are common and the aerosol climatology is currently not well characterized.

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