Date of Award
2021
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Atmospheric and Earth Science
Committee Chair
John R. Mecikalski
Committee Member
Christopher J. Schultz
Committee Member
Kevin Knupp
Subject(s)
GOES (Meteorological satellite), Weather forecasting., Thunderstorms., Lightning., Hail.
Abstract
Every year in North America, severe thunderstorms produce copious amounts of damage to agriculture, infrastructure, and lives. The United States relies heavily on the Next Generation Weather Radar for weather information. The U.S.’s reliance on radar has led to one of the most extensive radar networks in the world. However, this network has gaps in coverage that could put many at risk. Multiple studies have shown that satellite data provides valuable storm information to forecasters. The GOES-R series offers high resolution imagery of cloud tops. An important variable to examine is the overshooting top (OT). One variable that stems from an OT is the Above Anvil Cirrus Plume (AACP). Both elements have been shown to be indicators of severe storms. Another aspect to examine is Flash Extnet Density (FED). The Geostationary Lightning Mapper (GLM) is a valuable tool for tracking lightning in severe storms. It has been shown that increases in lightning correlates to increases in storm intensity. This project aims to bridge the gap between radar data and satellite data. OT and AACP frequency and duration will be examined in both hail scar producing storms and non-hail scar producing storms. MESH values will be used to compare minimum cloud top temperatures (CTT) and maximum FED between hail scar producing storms and non-hail scar producing storms. Finally, a probability will be computed of a hail scar occurring, a severe storm occurring, and a non-severe storm occurring given specific CTT and FED. Within hail scars, OT appeared 100% of the time and AACP appeared 80% of the time. Severe storms that did not produce a hail scar had OT appear 70.8% and AACP form 27% of the time. Non-severe storms also saw OT (10.1%) and AACP (15.8%). There was not a high distinction between hail scar storms, severe storms, and non-severe storms CTT and FED values. Many of these values overlapped with each other and their distributions were close. Maximum MESH showed the highest distinction between the storm types. Hail scar producing storms had a mean MESH value of 49 mm and non-hail scar storms had a mean MESH value of 10 mm.
Recommended Citation
Whiteside, Abigail Elizabeth, "Using GOES-16 to characterize thunderstorms : hail scar producing storms vs. non-hail scar producing storms" (2021). Theses. 355.
https://louis.uah.edu/uah-theses/355