Distinct regional meteorological influences on low cloud albedo susceptibility over global marine stratocumulus regions

Abstract

Marine stratocumuli cool the Earth effectively due to their high reflectance of incoming solar radiation and persistent occurrence. The susceptibility of cloud albedo to droplet number concentration perturbations depends strongly on large-scale meteorological conditions. Studies focused on the meteorological dependence of cloud adjustments often overlook the covariability among meteorological factors and their geographical and temporal variability. We use 8 years of satellite observations sorted by day and geographical location to show the global distribution of marine low-cloud albedo susceptibility. We find an overall cloud brightening potential for most marine warm clouds, which is more pronounced over subtropical coastal regions. A weak cloud darkening potential in the annual mean is evident over the remote SE Pacific and SE Atlantic. We show that large-scale meteorological fields from the ERA5 reanalysis data, including lower-tropospheric stability, free-tropospheric relative humidity, sea surface temperature, and boundary layer depth, have distinct covariabilities over each of the eastern subtropical ocean basins where marine stratocumuli prevail. This leads to a markedly different annual cycle in albedo susceptibility over each basin. Moreover, we find that basin-specific regional relationships between key meteorological factors and albedo susceptibilities are absent in a global analysis. Our results stress the importance of considering the geographical distinctiveness of temporal meteorological covariability when scaling up the local-to-global response of cloud albedo to aerosol perturbations.

The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback

“…MCC transitions may also contribute to observed variations in cloud optical depth as a function of temperature (Terai et al., 2016; Wall, Storelvmo, et al., 2022). Future work will seek to quantify remaining morphology feedback components (i.e., cloud amount and altitude), utilize observed morphology behaviors to constrain GCMs (e.g., Zelinka et al., 2022), and investigate aerosol influence separate from meteorological drivers (e.g., Wall, Norris, et al., 2022; Zhang & Feingold, 2022; Zhang et al., 2022) on morphology occurrence, transitions, and radiative properties.…”