The behavior of total lightning activity in severe Florida thunderstorms

Williams, Earle; Boldi, B.; Matlin, A.; Weber, M.; Hodanish, Steve; Sharp, Dave; Goodman, S. J.; Raghavan, R.; Buechler, Dennis E.

doi:10.1016/s0169-8095(99)00011-3

Cited by 244 publications

(211 citation statements)

References 25 publications

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“…Figures 6c and 6d depict the distributions of these quantities. The total FR measures confirm many previous studies in which severe thunderstorms were characterized by greater FRs than nonsevere storms (e.g., Williams et al 1999;Schultz et al 2011;Rudlosky and Fuelberg 2013). Figure 7c indicates that roughly 75% of nonsevere LD thunderstorms possessed maximum FRs below 25 fpm while 75% of severe LD thunderstorms possessed maximum FRs above 25 fpm.…”

Section: B Severe Versus Nonsevere Thunderstorm Lightning Trendssupporting

confidence: 88%

“…The results indicate that 25 fpm could provide an anecdotal threshold differentiating between severe and nonsevere convection. Although this value is much smaller than the 60 fpm suggested by Williams et al (1999), it is very similar to the base flash rate threshold employed by the Earth Networks' DTA, and this relationship merits further investigation. Thought an LJA implementation is much more than a single flash rate threshold [i.e., warnings issued based purely on FR threshold exceedance have also struggled with POD and FAR (e.g., Meyer et al 2015)], the potential utility of 25 fpm as a regionally useful indicator for the central Appalachians should be explored.…”

Section: Discussionmentioning

confidence: 56%

“…Although an effort is made to qualitycontrol the reports published within Storm Data, the National Weather Service (NWS) does not guarantee the accuracy of the reports (www.ncdc.noaa.gov/ stormevents/faq.jsp). In addition to several studies that have documented temporal inconsistencies and spatial errors in the reporting of severe weather (e.g., Witt et al 1998a,b;Williams et al 1999), it must also be acknowledged that some severe weather events may not be documented at all. Despite these issues, Storm Data is generally regarded as the most accessible and respected severe weather archive available for analysis.…”

Section: Severe Weather Reportsmentioning

confidence: 99%

“…Total lightning, which is the sum of intracloud (IC) and cloud-toground (CG) lightning, occurs in much greater quantities than CG lightning alone (e.g., Goodman et al 1988;MacGorman et al 1989MacGorman et al , 2011Boccippio et al 2001) and offers more comprehensive insight into storm electrification. Many studies have documented sharp increases (i.e., a "jump") in the total lightning flash rate of severe thunderstorms prior to the onset of severe weather 1 at the surface (e.g., Goodman et al 1988;Williams et al 1999;Goodman et al 2005;Schultz et al 2009Schultz et al , 2011Darden et al 2010;Gatlin and Goodman 2010;Rudlosky and Fuelberg 2013).…”

Section: Introductionmentioning

confidence: 99%

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The utility of total lightning trends in diagnosing single-cell thunderstorm severity: Examples from the central Appalachians region

Miller¹,

Ellis²,

Keighton³

2015

J. Operational Meteor.

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: The utility of total lightning trends in diagnosing single-cell thunderstorm severity: Examples from the central Appalachians region. J. Operational Meteor., 3 (8) ABSTRACTThe performance of a total lightning jump algorithm for guiding severe thunderstorm warnings within a weakly sheared environment was investigated using data from the Earth Networks Total Lightning Network. Total lightning observations from two summers for a study domain within the central Appalachian Mountains region were clustered into likely thunderstorms using single-linkage clustering. The spatial and temporal characteristics of each flash cluster were evaluated and used to assign a "storm index" (SI) score to each cluster. Small, short-lived, slow-moving, circular clusters-consistent with single-cell thunderstormswere given large SI scores, and large, long-lived, fast-moving, linear clusters-inconsistent with the single-cell mode-received smaller SI scores. Statistical testing revealed that days with a simple majority of lightningdefined (LD) single-cell storms possessed significantly weaker 0-6-km wind shear than days with a majority of non-single-cell storms. After classifying 470 clusters as either LD single-cell or multicell/supercell, the 2σ lightning jump algorithm was applied to the flashes associated with each cluster. Total lightning jumps identified by the algorithm were aligned with severe weather report data to evaluate the accuracy of the algorithm. Although probability of detection values for both categories compared well to previous studies, false alarm rates were significantly larger than previously documented. The algorithm performed unsatisfactorily among the LD single-cell and multicell/supercell storms studied, and its performance deteriorated further when applied to a subset of storms most clearly defined as single-cell. However, severe LD storms demonstrated greater flash rates, a promising characteristic for future lightning-based warning tools.

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Section: B Severe Versus Nonsevere Thunderstorm Lightning Trendssupporting

confidence: 88%

Section: Discussionmentioning

confidence: 56%

Section: Severe Weather Reportsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The utility of total lightning trends in diagnosing single-cell thunderstorm severity: Examples from the central Appalachians region

Miller¹,

Ellis²,

Keighton³

2015

J. Operational Meteor.

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show abstract

“…Previous research has shown that rapid increases in lightning activity (i.e., lightning jumps) are highly correlated with the occurrence of severe weather (Williams et al 1999;Schultz et al 2009, hereafter S09; Gatlin and Goodman 2010)-using lightning data from available three-dimensional lightning networks throughout the United States. Furthermore, recent studies (S09; Gatlin and Goodman 2010;Schultz et al 2011, hereafter S11) have quantified the lightning jump based on statistical performance metrics, including probability of detection (POD) and false alarm ratio (FAR).…”

Section: Introductionmentioning

confidence: 99%

Automated storm tracking and the lightning jump algorithm using GOES-R Geostationary Lightning Mapper (GLM) proxy data

Schultz¹,

Schultz²,

Carey³

et al. 2016

J. Operational Meteor.

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This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA)-which are important elements in the transition of the LJA concept from a research to an operational-based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid) and lightning information (flash rate density). Evaluations show that the spatial scale of tracked features or storm clusters has a large impact on the lightning jump system performance, where increasing spatial scale results in a decreased dynamic range of the system's performance. This framework also serves as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection and false alarm ratio statistics. Of the algorithm parameters tested, the sigma-level (i.e., a metric of lightning jump strength) and flash rate threshold influence the system's performance the most. Finally, minor changes in verification methods can dramatically impact the evaluation of the lightning jump system.

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Lightning Locators

Shirer¹,

Roeder²,

Shirer³

et al. 2002

Encyclopedia of Imaging Science and Technology

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Locating lightning in real time is an old problem. Radio techniques developed in the early to mid‐twentieth century used crossed‐loop cathode‐ray direction finders (CRDF) that provide the bearing but not the range to the lightning source. Direction‐finding (DF) systems typically sense the radio signal, known as atmospherics , spherics , or ‘ sferics , that is emitted by lightning and that most listeners of AM radios interpret as interference, static , or radio noise . Quite generally, lightning radiates electromagnetic pulses that span an enormous range of frequencies. In this article, the radio signal refers to the portion of the electromagnetic spectrum that covers frequencies less than 3 × 10 8 kilohertz (denoted kHz), or 300 GHz, and the optical signal refers to frequencies greater than 3 × 10 8 kHz. Also, when not qualified here, electromagnetic radiation refers to the radio signal. Lightning sensing systems have important applications in meteorology. Certainly, these systems can help to detect and forecast the arrival of thunderstorms by monitoring their positions, motions, and intensities. Such systems are also important for lightning safety and for protecting natural resources in a diverse set of real‐time applications, including fire and personnel safety, aircraft routing, missile launch decisions, power grid operation, and weather forecasting. Lightning is a significant threat to people but far too often is underrated. Lightning sensing systems, especially those that detect intracloud lightning, are being investigated as tools for predicting severe thunderstorms, including tornadoes, microbursts, and hail. Lightning data are also being investigated as possible input for small‐scale numerical weather forecast models to supplement the usual observations of pressure, temperature, humidity, and winds. This article is not an exhaustive survey of all real‐time and research lightning location systems, but it provides a comprehensive overview of the topic. It is split into two major parts; the first reviews the many important concepts and defines the terminology used to describe them, and the second covers the different major types of operational lightning location systems by describing an example of each in detail. Many of the lightning facts herein are documented thoroughly in the references. The methods and detection systems reviewed in this article are also described on various World Wide Web (www) sites. The addresses for many of these sites are given.

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The behavior of total lightning activity in severe Florida thunderstorms

Cited by 244 publications

References 25 publications

The utility of total lightning trends in diagnosing single-cell thunderstorm severity: Examples from the central Appalachians region

The utility of total lightning trends in diagnosing single-cell thunderstorm severity: Examples from the central Appalachians region

Automated storm tracking and the lightning jump algorithm using GOES-R Geostationary Lightning Mapper (GLM) proxy data

Lightning Locators

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