Date of Award


Degree Type


Degree Name

Master of Science (MS)


Earth, Atmospheric, and Planetary Sciences

Committee Chair

Daniel T. Dawson II

Committee Member 1

Alexander Gluhovsky

Committee Member 2

Robin Tanamachi


Many aspects of microphysical variations within supercells are not well understood, even though they play a key role in storm dynamics and evolution. Raindrop size distributions (DSDs) provide a lot of insight into a storms microphysics, however, DSDs vary significantly throughout storms. Unfortunately, current radars do not have the capability to directly observe DSDs, making retrieval algorithms based on advanced microphysical models and in-situ disdrometer observations necessary. If these small-scale variations can be better characterized, and differences between convective regimes quantified, it will lead to improved algorithms for retrieving DSD parameters from radars as well as improved microphysical parameterizations within numerical weather prediction models. With better modeling of supercells, tornado predictions and warnings can be improved. While disdrometers can directly measure DSDs, they are severely limited in spatial coverage. In order to improve our understanding of the spatial variation of DSDs across supercells, radar retrieval methods, such as the constrained-gamma method, can be used to retrieve DSD parameters at high spatial resolution across an entire storm. The constrained-gamma method works by finding a relationship between the shape parameter μ and the slope parameter Λ of the underlying gamma distribution. In this study, the constrained gamma method is applied to radar data collected during the 2016 and 2017 VORTEX-SE field program in order to retrieve gamma distributions from polarimetric radar variables. Specifically, new μ-Λ relations will be derived from VORTEX-SE disdrometer data and will be compared to μ-Λ relations found in other studies. The utility of retrievals will then be evaluated using the different relations for characterizing the spatiotemporal variation of DSDs for VORTEX-SE storms. To further improve the μ-Λ relation, the effects of measurement errors will be minimized by using a sorting and averaging technique to group DSDs with similar microphysical properties together.