Spatial statistics of likely convective clouds in CloudSat data

Spatial characteristics of cloud objects derived from 14 months of CloudSat data are analyzed with the aim of understanding global statistics for atmospheric convection. This study uses meteorological fields provided by NASA's Modern Era Reanalysis for Research and Applications (MERRA) and the European Center's ERA-Interim reanalysis to determine environmental conditions for the cloud objects. Width and aspect ratio statistics for clouds of likely convective origin are presented. Cloud object heights are compared with predictions from entraining plume models. A major finding of this study is that actual cloud depths are usually more than 50% smaller than those predicted by the plume models. This holds for a range of entrainment rate specifications, including rates based on observed cloud widths. A technique for isolating "mature" convective clouds based on their shape is proposed. When this technique is used to select objects, the comparison with the entraining plume model improves dramatically. Another result from this analysis is power law behavior in the cloud width distribution derived from CloudSat objects. After accounting for the difference between one-dimensional and two-dimensional sampling, the slope of the CloudSat distribution appears consistent with that found in earlier studies' cloud imagery. However, when clouds are selected using a minimum depth criterion, the resulting population is sharply peaked at widths close to this minimum depth. Finally, a weakly trimodal distribution of convective cloud depths is found, consistent with results from Johnson et al. (1999).