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

Quantifying global cloud condensation nuclei (CCN) concentrations is crucial for reducing uncertainties in radiative forcing resulting from aerosol–cloud interactions. This study analyses two novel, independent, open-source global CCN datasets derived from spaceborne Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis and examines the spatio-temporal variability of CCN concentrations pertinent to liquid clouds. The results reveal consistent large-scale patterns in both CALIOP and CAMS datasets, although CALIOP values are approximately 79 % higher than those from CAMS. Comparisons with the existing literature demonstrate that these datasets effectively bound regionally observed CCN concentrations, with CALIOP typically representing the upper bound and CAMS the lower bound. Monthly and annual variations in CCN concentrations obtained from the two datasets largely agree over the Northern Hemisphere and align with previously reported variations. However, inconsistencies emerge over pristine oceans, particularly in the Southern Hemisphere, where the datasets show not only opposing seasonal changes but also contrasting annual trends. Seasonal cycles in these regions are well represented in CAMS, consistent with previous in situ observations, while annual trends seems to be better captured by CALIOP. A comparative study of trends in CCN and cloud droplet concentrations suggests that dust-influenced and pristine maritime environments are primary regions that limit our current understanding of CCN–cloud droplet relationships. Long-term CCN observations in these regions are crucial for improving global datasets and advancing our understanding of aerosol–cloud interactions.