Shallow Clouds Make the Case for Remote Sensing Instrumentation

McFarlane, S. A., U.S. Department of Energy

Cloud Distributions/Characterizations

Radiative Processes

McFarlane, S. A., and W. W. Grabowski (2007). Optical properties of shallow tropical cumuli derived from ARM ground-based remote sensing, Geophys. Res. Lett., 34, L06808, doi:10.1029/2006GL028767.


In this figure, the lines indicate theoretical calculations of cloud droplet size for clouds with various droplet concentrations in which no mixing occurs. The cloud droplet size shows significant variability with height.


In this figure, the lines indicate theoretical calculations of cloud droplet size for clouds with various droplet concentrations in which no mixing occurs. The cloud droplet size shows significant variability with height.

Traditionally, observations of air mixing and cloud droplet size come from in situ aircraft probes, which collect data at very high horizontal resolution. However, it is very expensive to sample numerous clouds with an aircraft, and measuring vertical profiles (especially in shallow clouds) is difficult. The use of remote sensing data allows analysis of significantly more cloud cases than would be possible, or practical, with aircraft data.

Modeling the indirect effects of aerosols requires assumptions about the impact that mixing of dry and cloudy air will have on the size of the cloud droplets and shape of the droplet distribution. To constrain models, observations of the relationship between mixing and cloud droplet size are needed. In a paper published in Geophysical Research Letters in March 2007, ARM researchers used 6 months of shallow cumulus cloud observations to investigate the vertical structure of cloud droplet size as a function of the amount of mixing with dry air. Observations for their study were obtained from remote sensing instruments at Nauru, one of three ARM Climate Research Facility sites in the Tropical Western Pacific region. They found that shallow cumuli were significantly diluted, and cloud droplet size showed large spatial variability with height.

These results illustrate the utility of ARM remote sensing data of shallow cumulus for constraining and validating models of microphysical processes, such as large-eddy simulation models.