30 Sep 2021

30 Sep 2021

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

Enhancing MAX-DOAS atmospheric state retrievals by multispectral polarimetry – studies using synthetic data

Jan-Lukas Tirpitz1,a, Udo Frieß1, Robert Spurr2, and Ulrich Platt1,3 Jan-Lukas Tirpitz et al.
  • 1Institute of Environmental Physics, University of Heidelberg, Heidelberg, Germany
  • 2RT Solutions Inc., Cambridge, MA, USA
  • 3Max Planck Institute for Chemistry, Mainz, Germany
  • anow at: Airyx GmbH, Justus-von-Liebig-Straße 14, 69214 Eppelheim, Germany

Abstract. Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a widely-used measurement technique for the remote detection of atmospheric aerosol and trace gases. The technique relies on the analysis ultra-violet and visible radiation spectra of scattered sunlight (skylight) to obtain information on different atmospheric parameters. From an appropriate set of spectra recorded under different viewing directions (typically a group of observations at different elevation angles) the retrieval of aerosol and trace gas vertical distributions is achieved through numerical inversion methods.

It is well known that the polarisation state of skylight is particularly sensitive to atmospheric aerosol content as well as aerosol properties, and that polarimetric measurement could therefore provide additional information for MAX-DOAS profile retrievals; however such measurement have not yet been used for this purpose. To address this issue, we have developed the RAPSODI (Retrieval of Atmospheric Parameters from Spectroscopic Observations using DOAS Instruments) algorithm. In contrast to existing MAX-DOAS algorithms, it can process polarimetric information, and it can retrieve simultaneously profiles of aerosols and various trace gases at multiple wavelengths in a single retrieval step; a further advantage is that it contains a Mie scattering model, allowing for the retrieval aerosol microphysical properties. The forward model component in RAPSODI is based on a linearized vector radiative transfer model with Jacobian facilities, and we have used this model to create a data base of synthetic measurements in order to carry out sensitivity analyses aimed at assessing the potential of polarimetric MAX-DOAS observations. We find that multispectral polarimetry significantly enhances the sensitivity, particularly to aerosol related quantities. Assuming typical viewing geometries, the degree of freedom for signal (DFS) increases by about 50 % and 70 % for aerosol vertical distributions and aerosol properties, respectively, and by approximately 10 % for trace gas vertical profiles. For an idealised scenario with a horizontally homogeneous atmosphere, our findings predict an improvement in the inversions results' accuracy (root-mean-square deviations to the true values) of about 60 % for aerosol VCDs as well as for aerosol surface concentrations, and by 40 % for aerosol properties. For trace gas VCDs, very little improvement is apparent, although the accuracy of trace gas surface concentrations improves by about 50 %.

Jan-Lukas Tirpitz 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-2021-274', Anonymous Referee #2, 29 Oct 2021
    • AC2: 'Reply on RC1', Jan-Lukas Tirpitz, 04 Jan 2022
  • RC2: 'Comment on amt-2021-274', Anonymous Referee #1, 08 Nov 2021
    • AC1: 'Reply on RC1 and RC2', Jan-Lukas Tirpitz, 04 Jan 2022

Jan-Lukas Tirpitz et al.

Jan-Lukas Tirpitz et al.


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Short summary
MAX-DOAS is a widely-used measurement technique for the remote detection of atmospheric aerosol and trace gases. It relies on the analysis of ultra-violet and visible radiation spectra of skylight. To date, information contained in the skylight's polarisation state has not been utilised. On the basis of synthetic data we carried out sensitivity analyses to assess the potential of polarimetry for MAX-DOAS applications.