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A Study of In-Cloud and Cloud-to-Ground Lightning in Tornado-Bearing Supercells in the Midwest

A Study of In-Cloud and Cloud-to-Ground Lightning in Tornado-Bearing Supercells in the Midwest. Ben Herzog and Patrick S. Market Dept. of Soil, Environmental & Atmospheric Sciences University of Missouri Columbia, MO. Introduction.

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A Study of In-Cloud and Cloud-to-Ground Lightning in Tornado-Bearing Supercells in the Midwest

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  1. A Study of In-Cloud and Cloud-to-Ground Lightning in Tornado-Bearing Supercells in the Midwest Ben Herzog and Patrick S. Market Dept. of Soil, Environmental & Atmospheric Sciences University of Missouri Columbia, MO

  2. Introduction • Knapp (1994) indicated a correlation between cloud to ground (CG) lightning flash frequency and the time of tornado touchdown

  3. Objectives • To verify Knapp’s (1994) work • To determine if identifying CG as well as in cloud (IC) lightning flash frequency trends could be used as an effective forecasting tool to determine tornado touchdown.

  4. Methodology • Find tornadic thunderstorms • Storm Prediction Center storm reports • Verify tornadoes from the National Climatic Data Center • Obtain Data • March 2007 – June 2007 • Rocky - Appalachian Mountains • Radar data from National Climatic Data Center • Lightning data from Vaisala, Inc

  5. Methodology (cont.) • Break each storm into 5 minute periods to identify flash trends • Start 60 minutes before first touchdown • Create spread sheets on each storm containing: • Total number of flashes per five minutes • Number of cloud to ground (CG) flashes per five minutes • Number of in cloud (IC) flashes per five minutes • Number of negative CG (CGN) flashes per five minutes • Number of positive CG (CGP) flashes per five minutes • Create a spread sheet containing all data from every storm

  6. Analysis • 30 total storms analyzed • 26092 total flashes analyzed • Some five minute spans had 0 flashes • Some five minute spans had over 300 flashes • 53.4% of flashes were CG • 89.7% of CG flashes were negative • 10.3% of CG flashes were positive • 46.6% of flashes were IC

  7. Analysis Total Flashes

  8. Analysis CG Flashes

  9. Analysis IC Flashes

  10. Analysis Negative CG Flashes

  11. Analysis Positive CG Flashes

  12. Analysis CGN Flashes CGP Flashes

  13. Results • As suggested in the study by Knapp, there is an identifiable pattern before tornado touchdown • Approximately 30 minutes before touchdown, there is a maxima in flash frequency • Approximately 20 minutes before touchdown, there is a minima in flash frequency • Approximately 10 minutes before touchdown, there is another maxima in flash frequency • Approximately 5 minutes before touchdown, there is another minima in flash frequency

  14. Results (cont.) • The cloud to ground flashes show this pattern especially well • The negative CG flashes also show this pattern • There are very few PCG flashes, so finding a pattern in the flash trend may be of little utility. However, at T-30 minutes before touchdown, we found 0 total PCG flashes. At that same time, the maximum number of NCG flashes occurred.

  15. Results (cont.) • There is a pattern associated with the in cloud flashes • There is a pattern of maxima and minima of flashes in IC storms, but it is not nearly as pronounced of a pattern as the CG flashes

  16. Future Work • Obtain data on storms from different years and see is the flash frequency pattern matches 2007 • Classify the storms into different categories • High precipitation supercells • Low precipitation supercells • Classic supercells • Squall lines • Mesoscale convective complexes

  17. Acknowledgements • Knapp, David I., 1994: Using Cloud-to-Ground Lightning Data to Identify Tornadic Thunderstorm Signatures and Nowcast Severe Weather. National Weather Digest, 19(2), 35-42

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