Preprints
https://doi.org/10.5194/amt-2021-212
https://doi.org/10.5194/amt-2021-212

  06 Aug 2021

06 Aug 2021

Review status: a revised version of this preprint is currently under review for the journal AMT.

Optimization of Aeolus Optical Properties Products by Maximum-Likelihood Estimation

Frithjof Ehlers1, Thomas Flament2, Alain Dabas2, Dimitri Trapon2, Adrien Lacour2, Holger Baars3, and Anne Grete Straume-Lindner1 Frithjof Ehlers et al.
  • 1ESA-ESTEC, Keplerlaan 1, 2201 AZ Noordwijk, Netherlands
  • 2Météo-France, CNRS, Toulouse, France
  • 3Leibniz-Institut für Troposphärenforschung e.V., Permoserstraße 15, 04318 Leipzig, Germany

Abstract. The European Space Agency (ESA) Earth Explorer Mission, Aeolus, was launched in August 2018 and embarks the first Doppler Wind Lidar in space. Its primary payload, the Aeolus LAser Doppler INstrument (Aladin) is a Ultra Violet (UV) High Spectral Resolution Lidar (HSRL) measuring atmospheric backscatter from air molecules and particles in two separate channels. The primary mission product is globally distributed line-of-sight wind profile observations in the troposphere and lower stratosphere. Atmospheric optical properties are provided as a spin-off product. Being and HSRL, Aeolus is able to independently measure the particle extinction coefficients, co-polarized particle backscatter coefficients and the co-polarized lidar ratio. This way, the retrieval is independent of a-priori information. The optical properties are retrieved using the Standard Correct Algorithm (SCA), which is an algebraic inversion scheme to a (partly) ill-posed problem and therefore sensitive to measurement noise. In this work, we rephrase the SCA into a physically constrained Maximum Likelihood Estimation (MLE) problem and demonstrate predominantly positive impact and considerable noise suppression capabilities. These improvements originate from the use of all available information within the SCA in conjunction with the expected physical bounds concerning the expected range of the lidar ratio. The new MLE algorithm is equally evaluated against the SCA on end-to-end simulations of two homogeneous scenes and for real Aelous data collocated with measurements by a ground-based lidar and the CALIPSO satellite to consolidate and to illustrate the improvements. The largest improvements were seen in the retrieval of the extinction coefficients and lidar ratio ranging up to one order of magnitude or more in some cases due to an effective noise dampening.

Frithjof Ehlers et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-212', Anonymous Referee #1, 21 Aug 2021
    • AC1: 'Reply on RC1', Frithjof Ehlers, 01 Oct 2021
  • RC2: 'Comment on amt-2021-212', Anonymous Referee #2, 31 Aug 2021
    • AC2: 'Reply on RC2', Frithjof Ehlers, 01 Oct 2021
  • RC3: 'Comment on amt-2021-212', Anonymous Referee #3, 08 Sep 2021
    • AC3: 'Reply on RC3', Frithjof Ehlers, 01 Oct 2021

Frithjof Ehlers et al.

Frithjof Ehlers et al.

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Short summary
The Aeolus satellite observes the earth and can locate any kind of particles (aerosols or clouds) vertically. These observations are typically very noisy, which needs to be accounted for. This work achieves to dampen the noise in Aeolus' aerosol and cloud data, which is provided publicly by ESA, so that the scientific community can make better use of it. This makes the data potentially more useful for weather prediction and climate research.