Start
December 1, 2021 - 1:00 pm
End
December 1, 2021 - 2:00 pm
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School of Meteorology (Defense)School of Meteorology MS Thesis Defense
A Statistical Approach to Diagnosing Storm Mode (Linear vs Isolated) Using Synoptic Scale Variables
David Stang
Wednesday, December 1st
1:00pm
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https://oklahoma.zoom.us/j/92145193800?pwd=U2NaaVBwenpXcUpXdk5WZVVyRXFmdz09
Determining storm mode (linear or isolated) is a crucial component of any severe weather forecast. Isolated storms are associated with a greater likelihood of significant (EF2+) tornadoes and very large (2”+) hail, while linear storms are more likely to produce straight-line wind damage. Current operational Convection Allowing Models (CAMs), which are often used to diagnose storm mode, only run up to 48-60 hours into the future and can quickly lose accuracy with increasing lead time. To improve forecast accuracy and messaging on Day 3+ outlooks, a forecast tool was created to predict storm mode using only synoptic-scale variables. The approach uses a blend of theoretical modeling, stochastic modeling, and statistical modeling. The formulation generally performed well with reproducing past events and predicting future events 84+ hours in advance using 0.5° Global Forecasting System (GFS) and 0.5° Global Ensemble Forecasting System (GEFS) outputs.