17 Jul 2023
 | 17 Jul 2023
Status: this preprint is currently under review for the journal ESSD.

Cloud condensation nuclei concentrations derived from the CAMS reanalysis

Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas

Abstract. Determining concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, a process key for aerosol-cloud interactions (ACI). However, due to sparse coverage of in-situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source, temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN is one of the goals for quantifying ACI processes and achieving uncertainty reduced estimates of their associated radiative forcing.

Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service (CAMS) reanalysis (RA: EAC4) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models. The emitted aerosols in CAMS are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Furthermore, the reanalysis interpolates for cases of poor or missing retrievals and thus allows for a full spatio-temporal quantification of CCN.

This paper illustrates the temporal and spatial structure of CCN and their abundance in the atmosphere. A brief evaluation with ground based in-situ measurements demonstrates the improvement of the modeled CCN over the sole use of AOD as a proxy for CCN.

The CCN dataset, which is now freely available to users (Block, 2023), features 3-D CCN concentrations of global coverage for various supersaturations and aerosol species covering the years from 2003 to 2021 with daily frequency. This dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies.

Karoline Block 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 essd-2023-172', Anonymous Referee #1, 01 Aug 2023
  • RC2: 'Comment on essd-2023-172', Anonymous Referee #2, 01 Sep 2023

Karoline Block et al.

Data sets

Cloud condensation nuclei (CCN) numbers derived from CAMS reanalysis EAC4 (Version 1) Karoline Block

Karoline Block et al.


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Short summary
Aerosols being able to act as condensation nuclei for cloud droplets (CCN) are a key elements in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It was obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCN in the atmosphere and their temporal and spacial occurrence.