Size Distributions and Dynamical Properties of Shallow Cumulus Clouds from Aircraft Observations and Satellite Data

Abstract

In this paper aircraft observations of shallow cumulus over Florida during the Small Cumulus Microphysics Study (SCMS) are analyzed. Size distributions of cloud fraction, mass flux, and in-cloud buoyancy flux are derived. These distributions provide information on the specific contribution of clouds with a certain horizontal size and reveal, for example, which size has the largest effect on cloud fraction or vertical transport. The analysis of four flights shows that the mass flux and buoyancy flux are dominated by intermediate-sized clouds (horizontal dimension of about 1 km). The cloud fraction, on the other hand, is found to be dominated by the smallest clouds observed. These clouds are additionally found to have a negative contribution to the mass flux, yet a positive contribution to the buoyancy flux. About 200 flight intersections of cumuli with horizontal sizes larger than 500 m are used to obtain average horizontal cross-section profiles of vertical velocity, liquid water content, liquid water potential temperature, and virtual potential temperature. A thin shell of descending air just around the cloud emerges as a conspicuous feature. Evidence is found that the descent is mainly caused by evaporative cooling, which results from lateral mixing at the cloud boundary. A Landsat satellite image near the flight region is analyzed to compare the cloud size distributions with the aircraft data. The cloud cover in the image appears to be dominated by much larger clouds than the aircraft observations indicated. To account for the different measurement methodology (two-dimensional versus one-dimensional) an equation with which one can predict the cloud size distribution that results from performing line measurements in a prescribed two-dimensional cumulus field is derived. The equation reveals that the aircraft cloud size distributions are always biased toward smaller cloud sizes. This effect is nevertheless not enough to reconcile the aircraft and satellite data, presumably because the analysis neglects the variability of clouds in the vertical direction.