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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 3, 909-932, 2010
http://www.atmos-meas-tech.net/3/909/2010/
doi:10.5194/amt-3-909-2010
© Author(s) 2010. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
15 Jul 2010
The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light
A. A. Kokhanovsky1, J. L. Deuzé2, D. J. Diner3, O. Dubovik2, F. Ducos2, C. Emde4, M. J. Garay5, R. G. Grainger6, A. Heckel7, M. Herman2, I. L. Katsev8, J. Keller9, R. Levy10, P. R. J. North7, A. S. Prikhach8, V. V. Rozanov1, A. M. Sayer6, Y. Ota11, D. Tanré2, G. E. Thomas6, and E. P. Zege8 1Institute of Environmental Physics, University of Bremen, O. Hahn Allee 1, 28334 Bremen, Germany
2Lab. d'Optique Atmosphérique, UMR CNRS 8518, Bat. P5, Université Lille 1, 59655 – Villeneuve d'Ascq cedex, France
3Jet Propulsion Lab., California Institute of Technology, MS 169-237, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
4Deutsches Zentrum für Luft- und Raumfahrt (DLR), Münchner Straße 20, 82234 Weßling, Germany
5Raytheon Intelligence and Information Systems, 299 N. Euclid Ave., Suite 500, Pasadena, CA 91101, USA
6Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford, OX1 3PU, UK
7School of the Environment and Society, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
8Institute of Physics, National Academy of Sciences of Belarus, Pr. Nezavisimosti 68, 220072, Minsk, Belarus
9Paul Scherrer Institute, Laboratory of Atmospheric Chemistry (LAC), 5232 Villigen PSI, Switzerland
10SSAI, 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, USA
11National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Japan
Abstract. Remote sensing of aerosol from space is a challenging and typically underdetermined retrieval task, requiring many assumptions to be made with respect to the aerosol and surface models. Therefore, the quality of a priori information plays a central role in any retrieval process (apart from the cloud screening procedure and the forward radiative transfer model, which to be most accurate should include the treatment of light polarization and molecular-aerosol coupling). In this paper the performance of various algorithms with respect to the of spectral aerosol optical thickness determination from optical spaceborne measurements is studied. The algorithms are based on various types of measurements (spectral, angular, polarization, or some combination of these). It is confirmed that multiangular spectropolarimetric measurements provide more powerful constraints compared to spectral intensity measurements alone, particularly those acquired at a single view angle and which rely on a priori assumptions regarding the particle phase function in the retrieval process.

Citation: Kokhanovsky, A. A., Deuzé, J. L., Diner, D. J., Dubovik, O., Ducos, F., Emde, C., Garay, M. J., Grainger, R. G., Heckel, A., Herman, M., Katsev, I. L., Keller, J., Levy, R., North, P. R. J., Prikhach, A. S., Rozanov, V. V., Sayer, A. M., Ota, Y., Tanré, D., Thomas, G. E., and Zege, E. P.: The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light, Atmos. Meas. Tech., 3, 909-932, doi:10.5194/amt-3-909-2010, 2010.
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