<p>Satellite quantification of aerosol effects on clouds relies on aerosol optical depth (AOD) as a proxy for aerosol concentration or cloud condensation nuclei (CCN). However, the lack of error characterization of satellite-based results hampers their use for the evaluation and improvement of global climate models. We show that the use of AOD for assessing aerosol-cloud interactions (ACI) is inadequate over vast oceanic areas in the subtropics. Instead, we postulate that a more physical approach that consists of matching vertically resolved aerosol data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite at the cloud-layer height with Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) cloud retrievals reduces uncertainties in satellite-based ACI estimates. Combined aerosol extinction coefficients (σ) below cloud-top (σ<sub>BC</sub>) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (<i>N</i><sub>d</sub>) from Aqua-MODIS yield high correlations across a broad range of σ<sub>BC</sub> values, with σ<sub>BC</sub> quartile correlations > 0.78. In contrast, CALIOP-based AOD yields correlations with MODIS <i>N</i><sub>d</sub> of less than 0.62 for the two lower AOD quartiles. Moreover, σ<sub>BC</sub> explains 41 % of the spatial variance in MODIS <i>N</i><sub>d</sub>, whereas AOD only explains 17 %, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with σ<sub>BC</sub>, near-surface σ weakly correlates in space with MODIS <i>N</i><sub>d</sub>, accounting for a 16 % variance. It is concluded that the linear regression calculated from ln(<i>N</i><sub>d</sub>)−ln(σ<sub>BC</sub>) (the standard method for quantifying ACI) is more physically meaningful than that derived from the <i>N</i><sub>d</sub>−AOD pair.</p>