Sunday, 6 January 2013
Exhibit Hall 3 (Austin Convention Center)
Tropical convection is an important influence on global climate. Not only does the convection in tropical regions significantly impact daily to yearly variability, it also may impact global circulation (Johnson et al., 1999). Tropical convection is represented by a trimodal size distribution, consisting of shallow trade wind cumulus, cumulus congestus, and deep cumulonimbus. Of importance to this study is the middle mode of congestus. According to Johnson et al. (1999), cumulus congestus can account for half the total convection and over a quarter of the convective rainfall over the tropics. It is important, therefore, to better understand and model these mid-sized tropical clouds. Observational data from field campaigns is useful for this task. The Ice in Clouds Experiment Tropical (ICE-T) field campaign studied growing cumulus type clouds (including congestus) in a summer time, tropical, maritime environment near the U.S. Virgin Islands during July of 2011, the purpose of which was to evaluate ice nucleation and in-cloud properties of growing cumulus clouds through collection of data onboard the NSF/NCAR C130 research aircraft.
Video from the forward viewing camera was used to select cumulus and cumulus congestus type clouds and to determine when and if there were multiple passes through the same cloud. A definition of cloud based on liquid water content was also used to select clouds of interest. Statistics including the mean, minimum and maximum, and standard deviation were calculated for various microphysical properties. Each variable was examined as a function of height as well as with respect to the other variables. Increases with height are found for raindrop number concentration and diameter, cloud droplet diameter, updraft speed, and liquid water content. A decrease with height is seen in cloud droplet concentration. Measured values of liquid water content were also compared to predicted adiabatic values. The statistical results of the study are compared to simulations of similar congestus clouds from a cloud resolving model. This comparison is useful in evaluating model representations of these types of cumulus clouds, as well as illuminating areas of parameterization improvement.
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