32nd Conference on Broadcast Meteorology/31st Conference on Radar Meteorology/Fifth Conference on Coastal Atmospheric and Oceanic Prediction and Processes

Wednesday, 6 August 2003: 4:00 PM
Statistical Determination of the Characteristic Time for Precipitation Development in Cumulus Clouds using Radar
Sabine Göke, University of Illinois, Urbana, IL; and H. T. Ochs and R. M. Rauber
Poster PDF (119.1 kB)
We are testing a new method of analyzing radar data using data from the Small Cumulus Microphysics Study (SCMS). The broad objective of this method is to determine if there is a statistical difference between the rates of development of precipitation in two populations of clouds. To perform this analysis, radar echoes are tracked using PPI scans from the NCAR CP2 X-band radar. The PPI scans through the cloud's maximum reflectivity are used to construct time-height cross sections of reflectivity from about -20 to 10 dBz. The characteristic time for the growth of precipitation is defined by the time between the first appearances of the -15 and the 5 dBz reflectivity contours. The liquid water content at the 5 dBz level is defined as the characteristic liquid water content for precipitation development. Since developing clouds in SCMS were found to have nearly adiabatic cores, the liquid water content at the 5 dBz level is assumed to be the adiabatic content at that level. A scatter plot of the characteristic time for precipitation development versus the characteristic liquid water content is produced, where each point represents the analysis of one growing cumulus cloud. An important advantage of this analysis technique is that it is not necessary to know the cloud updraft.

For SCMS clouds, it has been suggested that there are significant differences in the rates of precipitation development between clouds ingesting a more continental CCN (Cloud Condensation Nuclei) concentration and those with a maritime concentration. Since we know the CCN concentrations for each day of SCMS, we can identify each point on the scatter plot as being characteristic of continental or maritime CCN and perform a test to determine if the continental and maritime populations are different statistically. The results of the analysis will be presented at the conference.

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