Robust Susceptibility of Cloud Cover and Radiative Effects to Biases in Retrieved Droplet Concentrations

The quantification of cloud droplet number concentration (N-d) is essential in gaining insights into the aerosol-cloud interactions (ACI), contributing to the most significant source of anthropogenic climate forcing uncertainty. This study compared the retrieved N-d from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) at pixel and scene levels and analyzed the changes in the susceptibility of cloud albedo (CA), cloud fraction (CF), and cloud radiative effect (CRE) to N-d. The results show that the differences between the pixel-level cloud products from VIIRS and MODIS are caused by a combination of factors including cloud detectability, spatial resolution, and wavelengths of channels. As cloud top inhomogeneity increases, the differences become more significant. This deviation finally results in VIIRS achieving a global average of 40% higher N-d than MODIS. Although the non-systematic differences cause an inevitable variability in the dependence of CA, CF, and CRE on N-d, the strong susceptibilities of these cloud properties to N-d are similar for both VIIRS and MODIS. This study found minimal impact on the susceptibilities, whether using the average N-d or that of the top 10% reflective clouds. This study further supports the conclusion that cloud cover and radiative effect are highly susceptible to variations in N-d, which can reduce uncertainty when evaluating the cooling effect of ACI in the context of global warming.