Lightning Decision Support Using VHF Total Lightning Mapping and NLDN Cloud-to-Ground Data in North Alabama

Schultz, Christopher J.; Stano, Geoffrey T.; Meyer, P.; Carcione, Brian; Barron, Todd P.

doi:10.15191/nwajom.2017.0511

Cited by 7 publications

(10 citation statements)

References 27 publications

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“…This approach is different from other lightning initiation and cessation studies that have either followed a particular storm (e.g., Stano et al 2010) or examined lightning within an area (e.g., MacGorman 16 April 20171417 16 April 2017) 466 1657 (18 April 20172308 18 April 2017) 391 2139 (20 April 20170441 21 April 2017) 422 1928 (22 April 20170120 23 April 2017) 352 0627 (27 April 20171143 (27 April 17 May 20170951 (17 May 2017) 471et al 2011). Schultz et al (2017) demonstrated that an Eulerian approach of examining these data from an end-user standpoint provided extra lead time on the first cloud-to-ground strike. Therefore, this study will use each GLM pixel as a decision point to simulate how decision-support partners would view these data for local area decisions or other areas of interest (e.g., a ball field, stadium, or amphitheater).…”

Section: Glm Stoplight Safety Validationmentioning

confidence: 99%

“…This increased lead time is due to the spatial information that total lightning measurements from LMA or GLM have versus traditional ground-based networks such as the National Lightning Detection Network (NLDN) or Earth Networks Total Lightning Network (ENTLN). Schultz et al (2017Schultz et al ( , 2018 also found an increase in operational downtime (i.e., work stoppages) using the LMA data versus NLDN observations. Schultz et al (2017Schultz et al ( , 2018 also states that further work is needed to properly assess how the risk assessment changes with spatial-extent observations.…”

Section: Introductionmentioning

confidence: 95%

“…Schultz et al (2017Schultz et al ( , 2018 also found an increase in operational downtime (i.e., work stoppages) using the LMA data versus NLDN observations. Schultz et al (2017Schultz et al ( , 2018 also states that further work is needed to properly assess how the risk assessment changes with spatial-extent observations. This paper describes the GLM 30-min hazard, or "stoplight," safety product developed by NASA SPoRT (first shown in Schultz et al 2017) and its validation relative to current lightningsafety metrics used to inform industry and the public about cessation of the lightning threat at a specific location.…”

Section: Introductionmentioning

confidence: 95%

“…Work by the SPoRT team in Schultz et al (2017Schultz et al ( , 2018 shows that total lightning from lightning mapping arrays (LMA; Rison et al 1999) provide additional lead time for lightning safety decision support. This increased lead time is due to the spatial information that total lightning measurements from LMA or GLM have versus traditional ground-based networks such as the National Lightning Detection Network (NLDN) or Earth Networks Total Lightning Network (ENTLN).…”

Section: Introductionmentioning

confidence: 99%

“…Schultz et al (2017Schultz et al ( , 2018 also states that further work is needed to properly assess how the risk assessment changes with spatial-extent observations. This paper describes the GLM 30-min hazard, or "stoplight," safety product developed by NASA SPoRT (first shown in Schultz et al 2017) and its validation relative to current lightningsafety metrics used to inform industry and the public about cessation of the lightning threat at a specific location. Also, use within MFSC EMA procedures is discussed to provide feedback on how using total Figure 1.…”

Section: Introductionmentioning

confidence: 99%

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Development and Evaluation of the GLM Stoplight Product for Lightning Safety

Stano

Smith

Schultz

2019

J. Operational Meteor.

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The launch of the Geostationary Lightning Mapper (GLM) aboard Geostationary Operational Environmental Satellite-R/S (GOES-16/17), provides new opportunities to support lightning safety, such as the 30-min hazard (“stoplight”) safety product developed by the National Aeronautics and Space Administration’s Short-term Prediction Research and Transition Center. This product plots the spatial extent where lightning occurred over the past 30 min and color codes the data in 10-min bins. Using GLM’s mapping of the spatial footprint of individual flashes, the product identifies when temporal rules for lightning safety have been met based on the needs of decision-support partners [commercial airlines, 10 min; United States Air Force (USAF) 45th Weather Squadron, 20 min; emergency management (EMA)/National Weather Service (NWS), 30 min]. The effort was guided by EMA partners requesting a product that quickly shows the location and age of lightning observations in an easy-to-interpret visualization. Analysis of lightning safety rules of thumb were performed in the framework of the GLM stoplight product to determine the number of times each of the partner criteria would be violated using an Eulerian-based approach simulating an integrated decision support point of view. The temporal criteria for commercial airlines, USAF, and EMA/NWS were violated 9.5%, 3.5%, and 1.4% of the time within this sample, respectively. Examples are provided to show the GLM 30-min hazard product in linear convection, multicellular convection, and electrified snowfall events. Illustrations also demonstrate how this GLM safety product and ground-based, lightning-location systems can work in tandem to maximize lightning safety protocols.

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Section: Glm Stoplight Safety Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development and Evaluation of the GLM Stoplight Product for Lightning Safety

Stano

Smith

Schultz

2019

J. Operational Meteor.

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The Multiplatform Precipitation Feature (MPF) Database: A Storm‐Centric Synthesis of Space‐ and Ground‐Based Precipitation and Lightning Data Sets for Convective Studies

Bang,

Stough,

Lang

et al. 2023

Earth and Space Science

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This paper outlines the construction of a new Multiplatform Precipitation Feature (MPF) framework designed to facilitate storm‐based analyses of data sets from multiple independent observing platforms for convective studies. The MPF approach is applied to ground‐ and space‐based precipitation observations and retrievals from the Global Precipitation Measurement mission Validation Network with space‐based lightning measurements from the Lightning Imaging Sensor on board the International Space Station to create a prototype MPF database. The data are synthesized in a thunderstorm‐like, feature‐based framework that enables broad statistical analyses of the storm‐based relationships between the microphysics, kinematics, and electrical properties of convection that can contribute insight into their morphological, regional, and seasonal variations. This manuscript details how MPFs are defined from precipitation data and how observations from multiple additional platforms are combined within the context of an MPF thunderstorm boundary and used to characterize the feature. A demonstration of the prototype database as a proof‐of‐concept showcases its flexibility to conduct both large‐scale storm‐based statistical studies as well as MPF‐facilitated thunderstorm case studies.

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Introducing Lightning Threat Messaging Using the GOES-16 Day Cloud Phase Distinction RGB Composite

Elsenheimer¹,

Gravelle

2019

Weather and Forecasting

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In 2001, the National Weather Service (NWS) began a Lightning Safety Awareness Campaign to reduce lightning-related fatalities in the United States. Although fatalities have decreased 41% since the campaign began, lightning still poses a significant threat to public safety as the majority of victims have little or no warning of cloud-to-ground lightning. This suggests it would be valuable to message the threat of lightning before it occurs, especially to NWS core partners that have the responsibility to protect large numbers of people. During the summer of 2018, a subset of forecasters from the Jacksonville, Florida, NWS Weather Forecast Office investigated if messaging the threat of cloud-to-ground (CG) lightning in developing convection was possible. Based on previous CG lightning forecasting research, forecasters incorporated new high-resolution Geostationary Operational Environmental Satellite (GOES)-16 Day Cloud Phase Distinction red–green–blue (RGB) composite imagery with Multi-Radar Multi-Sensor isothermal reflectivity and total lightning data to determine if there was enough confidence to message the threat of CG lightning before it occurred. This paper will introduce the Day Cloud Phase Distinction RGB composite, show how it can add value for short-term lightning forecasting, and provide an operational example illustrating how fusing these datasets together may be able to provide confidence and extend the lead time when messaging the threat of cloud-to-ground lightning before it occurs.

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Lightning Decision Support Using VHF Total Lightning Mapping and NLDN Cloud-to-Ground Data in North Alabama

Abstract: (Manuscript

Cited by 7 publications

References 27 publications

Development and Evaluation of the GLM Stoplight Product for Lightning Safety

Development and Evaluation of the GLM Stoplight Product for Lightning Safety

The Multiplatform Precipitation Feature (MPF) Database: A Storm‐Centric Synthesis of Space‐ and Ground‐Based Precipitation and Lightning Data Sets for Convective Studies

Introducing Lightning Threat Messaging Using the GOES-16 Day Cloud Phase Distinction RGB Composite

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