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Applications and Performance of a Lightning Risk Assessment using Geostationary Lightning Mapper (GLM) DataLightning is a hazard globally, particularly in lesser-developed countries. Cloud-to-ground lightning strikes are a threat to human safety, motivating a desire to monitor location-based lightning risk to mitigate harm. A lightning risk assessment for human safety was created that uses a combination of probabilistic risk calculation and spatial lightning mapping data to produce a risk magnitude. This risk magnitude evolves with time and changing conditions and is compared to tolerability thresholds in order to evaluate safety. The risk assessment using lightning mapping array (LMA) flash extent density (FED) data was found to perform comparatively (with respect to issuing lightning warnings) to a more standard method of monitoring lightning safety where National Lightning Detection Network (NLDN) flashes were monitored within a 5 nautical mile radius of a location of interest.
This research investigates the replacement of LMA FED with FED from the Geostationary Lightning Mapper (GLM) within the risk assessment framework. Using GLM FED would allow for risk to be calculated outside of LMA domains and anywhere within the GLM field of view, including areas outside of the United States (US). A few applications of the risk method with GLM FED are shown and discussed for locations both in and outside of the US. Additionally, the performance of the risk method is compared based on the type of lightning input source (LMA vs GLM). The end goal of this work is to provide forecasters and end users with a tool to help monitor lightning risk in decision support scenarios.
Document ID
20220000040
Acquisition Source
Marshall Space Flight Center
Document Type
Presentation
Authors
Kelley Murphy
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Roger E Allen
(Jacobs (United States) Dallas, Texas, United States)
Christopher J Schultz
(Marshall Space Flight Center Redstone Arsenal, Alabama, United States)
Eric C Bruning
(Texas Tech University Lubbock, Texas, United States)
Kristopher D White
(National Weather Service Silver Spring, Maryland, United States)
Ashley Ravenscraft
(National Weather Service Silver Spring, Maryland, United States)
Matthew E Anderson
(National Weather Service Silver Spring, Maryland, United States)
Date Acquired
January 14, 2022
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: The 102nd Annual American Meteorological Society (AMS) Meeting
Location: Houston, TX
Country: US
Start Date: January 23, 2022
End Date: January 28, 2022
Sponsors: American Meteorological Society
Funding Number(s)
WBS: 281945
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
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