a study of in cloud and cloud to ground lightning in tornado bearing supercells in the midwest
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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

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
Introduction
  • Knapp (1994) indicated a correlation between cloud to ground (CG) lightning flash frequency and the time of tornado touchdown
objectives
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.
methodology
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
methodology cont
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
analysis
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
analysis7
Analysis

Total Flashes

analysis8
Analysis

CG Flashes

analysis9
Analysis

IC Flashes

analysis10
Analysis

Negative CG Flashes

analysis11
Analysis

Positive CG Flashes

analysis12
Analysis

CGN Flashes

CGP Flashes

results
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
results cont
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.
results cont15
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
future work
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
acknowledgements
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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