Monday, 11 January 2016
Heating in tropical deep convective clouds drives large-scale circulations on many scales. Wind divergence profiles are closely linked to the heating profiles. Obtaining robust observations of wind divergence estimates covering wide-range of weather conditions is crucial to understand the relationship between heating profiles, thermodynamic structure, and cloud and precipitation associated with cloud-clusters, which are at different stages of its life cycle. Here, Doppler Radar observations from the DYNAMO field campaign are utilized to estimate the horizontal winds and wind divergence estimates using velocity-azimuth-display (VAD) technique. The wind divergence measurements covers diversified weather conditions sampled over 4 months (2245 hours) of observational period. The divergence profiles are statistically characterized with surface rain rates using regression analysis to examine the association of divergent signals with latent heat release. The observations from the cloud radar and local balloon soundings are used to put the divergence measurements in context with the evolution of cloud population and thermodynamic structure echo tops.
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