Preprints
https://doi.org/10.5194/acp-2021-999
https://doi.org/10.5194/acp-2021-999

  07 Jan 2022

07 Jan 2022

Review status: this preprint is currently under review for the journal ACP.

Addressing the difficulties in quantifying the Twomey effect for marine warm clouds from multi-sensor satellite observations and reanalysis

Hailing Jia1, Johannes Quaas1, Edward Gryspeerdt2,3, Christoph Böhm4, and Odran Sourdeval5 Hailing Jia et al.
  • 1Leipzig Institute for Meteorology, Universität Leipzig, Leipzig, Germany
  • 2Space and Atmospheric Physics Group, Imperial College London, UK
  • 3Grantham Institute for Climate Change and the Environment, Imperial College London, UK
  • 4Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
  • 5Laboratoire d’Optique Atmosphérique, Université de Lille, CNRS, Lille, France

Abstract. Aerosol–cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, in which the Twomey effect plays a fundamental role. Satellite-based estimates of the Twomey effect are especially challenging, mainly due to the difficulty in disentangling aerosol effects on cloud droplet number concentration (Nd) from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of a) updraft, b) precipitation, c) retrieval errors, as well as (d) vertical co-location between aerosol and cloud, on the assessment of Nd-toaerosol sensitivity (S) in the context of marine warm (liquid) clouds. Our analysis suggests that S increases remarkably with both cloud base height and cloud geometric thickness (proxies for vertical velocity at cloud base), consistent with stronger aerosol-cloud interactions at larger updraft velocity. In turn, introducing the confounding effect of aerosol–precipitation interaction can artificially amplify S by an estimated 21 %, highlighting the necessity of removing precipitating clouds from analyses on the Twomey effect. It is noted that the retrieval biases in aerosol and cloud appear to underestimate S, in which cloud fraction acts as a key modulator, making it practically difficult to balance the accuracies of aerosol–cloud retrievals at aggregate scales (e.g., 1° × 1° grid). Moreover, we show that using column-integrated sulfate mass concentration (SO4C) to approximate sulfate concentration at cloud base (SO4B) can result in a degradation of correlation with Nd, along with a nearly twofold enhancement of S, mostly attributed to the inability of SO4C to capture the full spatio-temporal variability of SO4B. These findings point to several potential ways forward to account for the major influential factors practically by means of satellite observations and reanalysis, aiming at an optimal observational estimate of global radiative forcing due to the Twomey effect.

Hailing Jia et al.

Status: open (until 18 Feb 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Hailing Jia et al.

Hailing Jia et al.

Viewed

Total article views: 311 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
231 75 5 311 14 4 3
  • HTML: 231
  • PDF: 75
  • XML: 5
  • Total: 311
  • Supplement: 14
  • BibTeX: 4
  • EndNote: 3
Views and downloads (calculated since 07 Jan 2022)
Cumulative views and downloads (calculated since 07 Jan 2022)

Viewed (geographical distribution)

Total article views: 315 (including HTML, PDF, and XML) Thereof 315 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Discussed

Latest update: 23 Jan 2022
Download
Short summary
Aerosol–cloud interaction is the most uncertain component of the anthropogenic forcing of the climate. By combining satellite and reanalysis data, we show that the strength of the Twomey effect (S) increases remarkably with vertical velocity. Both the confounding effect of aerosol–precipitation interaction and the lack of vertical co-location between aerosol and cloud are found to overestimate S, whereas the retrieval biases in aerosol and cloud appear to underestimate S.
Altmetrics