Surface-based assessment of cloud albedo responses to aerosol and meteorological drivers

Remote sensing from both the surface and space has become widely used to measure the influence of aerosol on cloud microphysics. However, the quantification of aerosol-cloud interactions is sensitive to the scale of the observations and approach to calculating representative metrics, resulting in large uncertainty. Surface based remote sensing typically operates at smaller scales and quantifies the aerosol-cloud microphysical response but not the radiative response. Also, readily available, coincident measures of ancillary variables such as liquid water, vertical velocity, and meteorological variables with surface-based approaches have been considered in calculating metrics, allowing for some separation of the aerosol signal from dynamical processes. Space-based remote sensing is more suitable for measuring the radiative response at larger-scales in an adjusted system where the net aerosol and meteorological influences have contributed to the response signal.

We present new results based on surface data from a mid-latitude continental site (ARM SGP) that evaluate how the aerosol-cloud albedo signal manifests at smaller-scales in a larger, adjusted system. Specifically, we use a multivariate statistical analysis to determine the portion of variability in cloud albedo due to meteorological factors, and to aerosol variability. We find that, as expected, the bulk of the variability in cloud albedo is highly correlated with variability in meteorological factors. We also find a discernible relationship between aerosol and cloud albedo that exhibits a pattern incongruous with meteorological factors. This analysis will provide observational constraints on aerosol-cloud forcing in an adjusting system, and an understanding of the relative role of processes that dictate cloud albedo.