S69 A Neural Network Approach to Tornado Forecasting in North Alabama and Southern Middle Tennessee

Sunday, 23 January 2011
Sandra G. LaCorte, University of Alabama, Huntsville, AL; and J. M. Coyne

In the past 30 years (1979-2009), nearly 250 tornadoes have been reported within the County Warning Area (CWA) assigned to the National Weather Service (NWS) in Huntsville, Alabama. For this study, four severe weather parameters that are frequently recognized by forecasters during tornado prediction are analyzed. These parameters, Convective Available Potential Energy (CAPE), Convective Inhibition (CIN), Storm Relative Helicity (SRH), and Lifted Index (LI), are extracted from the North American Regional Reanalysis (NARR) dataset. Parameter values obtained from the NARR dataset are then ingested into a Java-based Neural Network (NN). This NN accounts for both warm-season and cold-season severe weather, and aims to create an operational forecast tool for future tornado prediction. Preliminary results from this study will be presented.
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