21 Dec 2021
21 Dec 2021
Status: a revised version of this preprint is currently under review for the journal AMT.

Impact of 3D Cloud Structures on the Atmospheric Trace Gas Products from UV-VIS Sounders – Part II: impact on NO2 retrieval and mitigation strategies

Huan Yu1, Claudia Emde2, Arve Kylling3, Ben Veihelmann4, Bernhard Mayer2, Kerstin Stebel3, and Michel Van Roozendael1 Huan Yu et al.
  • 1Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
  • 2Ludwig-Maximilians-University (LMU), Meteorological Institute, Munich, Germany
  • 3Norwegian Institute for Air Research (NILU), Kjeller, Norway
  • 4ESA-ESTEC, Noordwijk, the Netherlands

Abstract. Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement Lambertian cloud models based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2-O2) absorption at 477 nm or on the oxygen A-band around 760 nm. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighboring pixels and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example, and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box-cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2-O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows identifying measurements for which the standard NO2 retrieval produces a significant bias, and therefore provides a way to improve the current data flagging approach.

Huan Yu 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-2021-338', Anonymous Referee #1, 14 Jan 2022
  • RC2: 'Comment on amt-2021-338', Anonymous Referee #2, 03 Feb 2022
    • AC2: 'Reply on RC2', Huan Yu, 13 Mar 2022
      • EC1: 'Reply on AC2', Diego Loyola, 15 Mar 2022
        • AC3: 'Reply on EC1', Huan Yu, 10 Apr 2022

Huan Yu et al.

Huan Yu et al.


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Short summary
In this study, we have investigated the impact of 3D clouds on the tropospheric NO2 retrieval from UV-Visible sensors. We applied standard NO2 retrieval methods including cloud corrections to synthetic data generated by the 3D radiative transfer model. A sensitivity study was made for synthetic data, and dependencies on various parameters were investigated. Possible mitigation strategies were investigated and compared based on 3D simulations and observed data.