To this end, we analyzed a database of over 600,000 tropical convective updrafts extracted from a convection-resolving differential-equation solver run at high spatial and temporal resolutions (100 meters and 10 seconds, respectively). The vertical profiles of w and CMF of each updraft are first fitted with a 6-parameter representation that captures the essence of their morphology (Root Mean Square Error for the w fit was < 1 m/s for ~94% of the columns and less than 10% of the maximum amplitude for ~70% of the cases ). Using a Principal Component Analysis of these parameters, we are able to extract the typical morphologies of w and CMF of the updrafts captured in the database. Next, we use polynomial fits to capture the temporal evolutions of these 6 parameters and elicit the constituent modes of their evolution. This characterization paves the way for evaluating the environmental states that result in the different modes of updraft evolution, and in evaluating which of these updraft evolutions lead to severe weather.
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