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Volume 3, issue 4 | Copyright

Special issue: The 2009 WE-Heraeus-Seminar on satellite remote sensing of...

Atmos. Meas. Tech., 3, 909-932, 2010
https://doi.org/10.5194/amt-3-909-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  15 Jul 2010

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 A. A. Kokhanovsky et al.
  • 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.

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