The goal of this study is to improve seasonal tornado outbreak forecasting by creating a statistical model that forecasts tornado outbreak frequency in the US using teleconnection indices as predictors. For this study, a tornado outbreak is defined as more than 6 tornado reports associated with a single synoptic system and an event N15 rating index of 0.5 or higher. The tornado outbreak season is confined to all months after February for a given calendar year. Monthly teleconnection indices are derived from a rotated principal component analysis (RPCA) of the geopotential height fields. Various regression techniques were trained with a sample of monthly teleconnection indices, tested on new data, and optimized to achieve the highest predictive skill. The outcome of this study could potentially allow forecasters the ability to predict tornado outbreak potential on a climatological scale with months of lead-time, allowing for better preparation strategies for tornado outbreak seasons.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-5911 |
| Date | 17 May 2014 |
| Creators | Sparrow, Kent Harris |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
Page generated in 0.0022 seconds