Tropical deep convective cloud morphology
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Abstract
A cloud-object partitioning algorithm is developed. It takes contiguous CloudSat cloudy regions and identifies various length scales of deep convective clouds from a tropical, oceanic subset of data. The methodology identifies a level above which anvil characteristics become important by analyzing the cloud object shape. Below this level in what is termed the pedestal region, convective cores are identified based on reflectivity maxima. Identifying these regions allows for the assessment of length scales of the anvil and pedestal of the deep convective clouds. Cloud objects are also appended ...
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