Cloud condensation nuclei concentrations derived from the CAMS reanalysis

Determining number 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, and a process key for aerosol-cloud interactions (ACI).  Here, we present a new CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1) which combines aerosol modeling with observations to better explore magnitude, source, temporal and spatial distribution of CCN numbers. The dataset features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years from 2003 to 2021 with daily frequency. CCN are derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework which are suitable for global models. The emitted aerosols in CAMSRA 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. Thus, this dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies. We will illustrate the distribution and variability of such derived CCN, evaluate them with observations and have a look at some specific features this dataset provides. Data description paper (preprint): https://essd.copernicus.org/preprints/essd-2023-172/