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A Spatiotemporal Lightning Risk Assessment Using Lightning Mapping Data

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  • 1 a Department of Geosciences, Texas Tech University, Lubbock, Texas
  • | 2 b NASA Marshall Space Flight Center, Huntsville, Alabama
  • | 3 c School of Sustainability, Arizona State University, Tempe, Arizona
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Abstract

A lightning risk assessment for application to human safety was created and applied in 10 west Texas locations from 2 May 2016 to 30 September 2016. The method combined spatial lightning mapping data, probabilistic risk calculation adapted from the International Electrotechnical Commission Standard 62305-2, and weighted average interpolation to produce risk magnitudes that were compared with tolerability thresholds to issue lightning warnings. These warnings were compared with warnings created for the same dataset using a more standard lightning safety approach that was based on National Lightning Detection Network (NLDN) total lightning within 5 n mi (1 n mi = 1.852 km) of each location. Four variations of the calculation as well as different units of risk were tested to find the optimal configuration to calculate risk to an isolated human outdoors. The best-performing risk configuration using risk (10 min)−1 or larger produced the most comparable results to the standard method, such as number of failures, average warning duration, and total time under warnings. This risk configuration produced fewer failures than the standard method but longer total time under warnings and higher false alarm ratios. Median lead times associated with the risk configuration were longer than the standard method for all units considered, whereas median down times were shorter for risk (10 min)−1 and risk (15 min)−1. Overall, the risk method provides a baseline framework to quantify the changing lightning hazard on the storm scale and could be a useful tool to aid in lightning decision support scenarios.

Murphy’s current affiliation: Earth System Science Center, The University of Alabama in Huntsville, Huntsville, Alabama.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kelley Murphy, km0109@uah.edu

Abstract

A lightning risk assessment for application to human safety was created and applied in 10 west Texas locations from 2 May 2016 to 30 September 2016. The method combined spatial lightning mapping data, probabilistic risk calculation adapted from the International Electrotechnical Commission Standard 62305-2, and weighted average interpolation to produce risk magnitudes that were compared with tolerability thresholds to issue lightning warnings. These warnings were compared with warnings created for the same dataset using a more standard lightning safety approach that was based on National Lightning Detection Network (NLDN) total lightning within 5 n mi (1 n mi = 1.852 km) of each location. Four variations of the calculation as well as different units of risk were tested to find the optimal configuration to calculate risk to an isolated human outdoors. The best-performing risk configuration using risk (10 min)−1 or larger produced the most comparable results to the standard method, such as number of failures, average warning duration, and total time under warnings. This risk configuration produced fewer failures than the standard method but longer total time under warnings and higher false alarm ratios. Median lead times associated with the risk configuration were longer than the standard method for all units considered, whereas median down times were shorter for risk (10 min)−1 and risk (15 min)−1. Overall, the risk method provides a baseline framework to quantify the changing lightning hazard on the storm scale and could be a useful tool to aid in lightning decision support scenarios.

Murphy’s current affiliation: Earth System Science Center, The University of Alabama in Huntsville, Huntsville, Alabama.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kelley Murphy, km0109@uah.edu
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