Articles | Volume 25, issue 6
https://doi.org/10.5194/acp-25-3841-2025
https://doi.org/10.5194/acp-25-3841-2025
Research article
 | Highlight paper
 | 
02 Apr 2025
Research article | Highlight paper |  | 02 Apr 2025

Pristine oceans are a significant source of uncertainty in quantifying global cloud condensation nuclei

Goutam Choudhury, Karoline Block, Mahnoosh Haghighatnasab, Johannes Quaas, Tom Goren, and Matthias Tesche

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1863', Anonymous Referee #1, 05 Sep 2024
  • RC2: 'Comment on egusphere-2024-1863', Marc Daniel Mallet, 11 Sep 2024
  • AC1: 'Comment on egusphere-2024-1863', Goutam Choudhury, 30 Oct 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Goutam Choudhury on behalf of the Authors (30 Oct 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Nov 2024) by Timothy Garrett
RR by Marc Daniel Mallet (06 Dec 2024)
RR by Anonymous Referee #1 (21 Dec 2024)
ED: Publish subject to minor revisions (review by editor) (21 Dec 2024) by Timothy Garrett
AR by Goutam Choudhury on behalf of the Authors (06 Jan 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (14 Jan 2025) by Timothy Garrett
ED: Publish subject to technical corrections (05 Feb 2025) by Ken Carslaw (Executive editor)
AR by Goutam Choudhury on behalf of the Authors (10 Feb 2025)  Author's response   Manuscript 
Download
Executive editor
Measurement datasets of cloud condensation nuclei (CCN) are vital for our understanding of aerosol-cloud interaction and reliable climate modelling. This study analyses and compares the only two global CCN datasets derived from satellite and reanalysis data. These key datasets are found to disagree over pristine oceans in terms of their climatology as well as seasonal and annual variations. Given the importance of CCN as a fundamental property in climate model simulations, further research is needed to reconcile these differences and to produce an observation-based dataset that can be confidently used to evaluate our understanding.
Short summary
Aerosol particles in the atmosphere increase cloud reflectivity, thereby cooling the Earth. Accurate global measurements of these particles are crucial for estimating this cooling effect. This study compares and harmonizes two newly developed global aerosol datasets, offering insights for their future use and refinement. We identify pristine oceans as a significant source of uncertainty in the datasets and, therefore, in quantifying the role of aerosols in Earth's climate.
Share
Altmetrics
Final-revised paper
Preprint