Cloud condensation nuclei (CCN) are essential components of aerosol-cloud interactions (ACI). Thus, a precise knowledge about their number concentrations (Nccn) is crucial for climate models and ACI studies. This study presents a comprehensive evaluation of the recently published CAMS-derived total Nccn using direct observations from 25 ground-based sites. The analysis specifically focuses on the temporal variability, the applicability of CAMS-derived Nccn across different environments and pollution regimes and in particular, the sensitivity of CCN to supersaturation. For the latter aspect, a bias shift is identified in simulated Nccn that correlates to the ratio of the two dominant CCN species, likely reflecting assumptions in the underlying size distributions and/or emissions fractions. To address this issue, we developed an observation-based parametrization that is applied to CAMS-derived total Nccn without modifying aerosol size distributions or species concentrations. This approach substantially reduces biases leading the way to an improved version of CAMS-derived Nccn.