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Dual-Doppler Derived Vorticity as a Predictor of Hail Size in Severe ThunderstormsWhite, Trevor Stewart 03 February 2017 (has links)
One of the primary missions of the National Weather Service (NWS) is to use a network of more than 150 NEXRAD radar installations to monitor weather for threats to life and property. Large hail produced by severe thunderstorms is a major focus of this mission. An algorithm known as the Maximum Estimated Size of Hail (MESH) algorithm is in operational use to diagnose the presence and size of hail. This study aims to use dual-Doppler observations as well as the MESH algorithm to test the idea that storms that rotate produce larger hail. Previous studies have used polarimetric radar products to detect the presence of large hail and dual-Doppler methods have been used to study embryonic hail, but no research has tested the theory of hail and rotating storms with observational evidence. A set of 59 case studies was gathered; each included a hail report submitted by a trained weather spotter or NWS employee and complete radar observations through the depth of a storm from two radars. The radar observations were resampled to a three-dimensional Cartesian grid and a dual-Doppler analysis was run on each case study. A strong correlation (stronger even than the MESH algorithm) was found between measured vorticity and hail size, lending credence to the idea that rotating storms do indeed have a higher ceiling for hail production. However, no correlation was found between MESH error and rotation. Further research will be required to evaluate whether or not this relationship can be used to augment the MESH algorithm so as to improve its skill. / Master of Science / The National Weather Service (NWS) uses a nationwide network of long-range weather radars to monitor the atmosphere over the United States. One of the primary applications of that network is to protect life and property by identifying and monitoring storms capable of producing large hail. The probable size of hail is estimated using an algorithm on raw radar data. This study uses multi-radar analysis methods to establish a metric for storm rotation, which is used in conjunction with the operational hail size algorithm to test the theory that rotating storms produce larger hail. A set of 59 case studies, each composed of data from a pair of radars as well as a measured hail size from a storm spotter, was gathered and analyzed. Analysis resulted in three values per case study: actual hail size, predicted hail size, and storm rotation intensity. Storm rotation and actual hail size were found to be strongly correlated, lending credence to the idea that rotation increases a storm’s hail production ceiling. However, no strong correlation was found between the operational algorithm’s error and storm rotation. Additional research will be required to determine if the relationship between rotation and actual hail size can be used to improve the skill of current operational algorithms.
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