Observation and Modeling of Dart Leader Development in an Altitude‐Triggered Lightning Flash

Li, Cai; Chu, Wangxiang; Wang, Jianguo; Zhou, Mi; Yun-sheng, Yan; Tian, Ruixin; Fan, Yadong

doi:10.1029/2022jd037545

“…Negative downward leaders usually have a distinctive stepped pattern, leading to their classification as 'negative stepped leaders', which has been observed in both natural and triggered lightning strikes (B. M. Hare et al, 2020;Biagi et al, 2014;. Many studies rely on triggered lightning techniques to understand the behavior of natural lightning as in these cases the location and time of the lightning leaders can be easily determined (Cai et al, 2022;Wang et al, 2022Wang et al, , 2019Biagi et al, 2014;Zhang et al, 2014;Gamerota et al, 2014). As the downward negative stepped leaders propagate, they typically branch out across the sky.…”

Section: Features Of Lightning and Nomenclaturementioning

confidence: 99%

“…Following the initial return stroke that neutralizes charges within the channel, secondary leaders known as 'dart leaders' have been observed travelling through the dormant remnant path, initiating a secondary return stroke (Thiemann & Gasiewski, 2014;Gamerota et al, 2014;Cai et al, 2022;Wang et al, 2022). Despite extensive research, the mechanisms by which the dormant plasma channel induces secondary leaders remain a mystery (B. M. Hare et al, 2023).…”

Section: Features Of Lightning and Nomenclaturementioning

confidence: 99%

“…Despite extensive research, the mechanisms by which the dormant plasma channel induces secondary leaders remain a mystery (B. M. Hare et al, 2023). Nevertheless, it is generally accepted that remnants of the hot plasma channel provide a conductive path for the dart leader to follow (Thiemann & Gasiewski, 2014;Gamerota et al, 2014;Cai et al, 2022). A successful dart leader may then induce a secondary return stroke, leading to the occurrence of multiple return strokes (Gamerota et al, 2014), a process which may continue until no new dart leader is initiated (Dwyer & Uman, 2014;Yuan et al, 2020;Shi et al, 2019;Filik et al, 2021).…”

Section: Features Of Lightning and Nomenclaturementioning

confidence: 99%

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Observations of Naturally Occurring Lightning with Event-Based Vision Sensors

Jones,

Hallgren,

Ralph

et al. 2024

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Lightning is an impressive, widespread natural phenomenon, yet many questions about its physics remain unanswered due to its extreme speed, transience, and high energy. These intrinsic characteristics make optical observations capturing its formation, propagation, and discharge challenging with conventional optical cameras. Furthermore, optical sensors with extremely high-speed frame rates and high dynamic ranges are needed. While high speed cameras have been used to capture lightning, their lack of portability, high cost and high data storage requirements can limit lightning research. To address these challenges, the use of neuromorphic technologies, inspired by the sensing and data processing mechanisms of biological photoreceptors, offers a unique approach. Event-based vision sensors offer low latency, less power than a conventional camera, and have sensing capabilities that operate across a dynamic range of over 120dB. This paper demonstrates the effectiveness of Event-Based Vision Sensor in lightning research by presenting data collected during a full lightning storm and provides examples of how event-based data can be used to interpret various lightning features. We used a Prophesee Gen4 Event-Based Vision Sensor to record a thunderstorm over a fifty-minute span on 24 January 2023, from Western Sydney, New South Wales, Australia. During this observation, we recorded numerous Cloud-to-Ground and Cloud-to-Cloud lightning strikes. To assess the Event-Based Vision Sensor’s effectiveness in capturing commonly observed lightning features, we used custom algorithms and in-house post-processing software was used to analyze and interpret the data. We conclude that the Event-Based Vision Sensor has the potential to improve high-speed imagery due to its lower cost, data output, and ease of deployment, ultimately establishing it as an excellent complementary tool for lightning observation.

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“…The model of Kasemir (1960) has historically been referred to as the bidirectional leader model, we will instead refer to it as the equipotential leader model, since the equipotential assumption is the most significant difference between this model and other non-physics-based leader models. A number of studies have used measured field changes to model simple charge configurations along leader channels without considering leader conductivity (Cai et al, 2022;Chen et al, 2013;Gao et al, 2020;Jensen et al, 2023b;Karunarathne et al, 2015;Lu et al, 2011). By contrast relatively few studies have attempted to compare the equipotential model to observed electric field changes associated with lightning (Mazur & Ruhnke, 1993;Pasko, 2014;da Silva & Pasko, 2015), and these studies have been somewhat limited by lack of knowledge of the extent or location of the leader channel.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Electric Fields Driving Lightning Dart Leader Development with BIMAP-3D Observations

Jensen,

Shao,

Sonnenfeld

et al. 2024

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0

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In this paper, a numerical dart leader model has been implemented to understand the leader’s development and the corresponding electric field changes observed by the 3D Broadband Mapping And Polarization (BIMAP-3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre-dart-leader channel has a significant temperature of ~3000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well-defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

show abstract

“…The model of Kasemir (1960) has historically been referred to as the bidirectional leader model, we will instead refer to it as the equipotential leader model, since the equipotential assumption is the most significant difference between this model and other non-physics-based leader models. A number of studies have used measured field changes to model simple charge configurations along leader channels without considering leader conductivity (Cai et al, 2022;Chen et al, 2013;Gao et al, 2020;Jensen et al, 2023b;Karunarathne et al, 2015;Lu et al, 2011). By contrast relatively few studies have attempted to compare the equipotential model to observed electric field changes associated with lightning (Mazur & Ruhnke, 1993;Pasko, 2014;da Silva & Pasko, 2015), and these studies have been somewhat limited by lack of knowledge of the extent or location of the leader channel.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Electric Fields Driving Lightning Dart Leader Development with BIMAP-3D Observations

Jensen,

Shao,

Sonnenfeld

et al. 2024

Preprint

0

View full text Add to dashboard Cite

In this paper, a numerical dart leader model has been implemented to understand the leader’s development and the corresponding electric field changes observed by the 3D Broadband Mapping And Polarization (BIMAP-3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre-dart-leader channel has a significant temperature of ~3000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well-defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

show abstract

Observation and Modeling of Dart Leader Development in an Altitude‐Triggered Lightning Flash

Cited by 6 publications

References 33 publications

Observations of Naturally Occurring Lightning with Event-Based Vision Sensors

Observations of Naturally Occurring Lightning with Event-Based Vision Sensors

Estimating the Electric Fields Driving Lightning Dart Leader Development with BIMAP-3D Observations

Estimating the Electric Fields Driving Lightning Dart Leader Development with BIMAP-3D Observations

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