Modeling of Time of Arrival Method for Lightning Locating Systems

Vahabi-Mashak, Saeed; Abdul‐Malek, Zulkurnain; Mehranzamir, Kamyar; Afrouzi, Hadi Nabipour; Salimi, Behnam; Wooi, Chin-Leong

doi:10.1155/2015/870290

Cited by 11 publications

(5 citation statements)

References 28 publications

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“…This website is generated by Blitzortung.org, which is a lightning detection network consisting of more than 500 lightning receivers that measure electromagnetic discharges in the atmosphere with very low frequency (VLF) receivers based on the time of arrival and time of group arrival method. See Vahabi-Mashak et al (2015) and Dowden et al (2002) for more information on the methods.…”

Section: Determining Tornado Event Datementioning

confidence: 99%

The Hunt for Missing Tornadoes: Using Satellite Imagery to Detect and Document Historical Tornado Damage in Canadian Forests

Kunkel

Hanesiak

Sills

2023

Journal of Applied Meteorology and Climatology

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Historical tornado events from 1982-2020 were documented within Canada’s forested regions using high-resolution satellite imagery. Tornado forest disturbances were identified using a three-step process: 1) detecting; 2) assessing; and 3) dating e ach event. A grid of 120 km x 120 km boxes was created covering Canada (excluding the extreme north). Of the 484 boxes, 367 were manually searched. Once a long, narrow region of tree damage was detected, it was first cross-referenced with known tornado databases to ensure it was a unique event. Once events were classified as either tornadic or downburst, the coordinates of the start, worst damage and end locations were documented, as well as the direction of motion, damage indicators, degree of damage, estimated maximum wind speed, and F/EF rating. In total, 231 previously unknown tornadoes were identified. In Ontario, 103 events were discovered, followed by 98 in Quebec, 9 in Manitoba, 6 in Saskatchewan, 9 in Alberta, 5 in British Columbia and 1 in New Brunswick. The largest number of discovered tornadoes occurred in 2015, while the largest number of strong F2 tornadoes occurred in 2005. Most of the discovered tornadoes occurred in July for both F/EF1 and F/EF2 ratings. Most tornado tracks had widths between 200-400 m, and more than 50% of the tornadoes had a path length less than 10 km. Of all the events discovered, 125 events could be fully dated, while 19 were dated only by month, 41 only by year, and 46 remained undated.

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Section: Determining Tornado Event Datementioning

confidence: 99%

The Hunt for Missing Tornadoes: Using Satellite Imagery to Detect and Document Historical Tornado Damage in Canadian Forests

Kunkel

Hanesiak

Sills

2023

Journal of Applied Meteorology and Climatology

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“…As MDF computes the triangulation area of the radiation direction and TDOA determines the intersection of hyperbolas, a combination of MDF and TDOA is one of the best choices for a combined LLS. Each technique can provide independent results and, finally, it is possible to find more accurate output by employing optimization techniques such as particle swarm optimization (PSO) [42]. The localization of lightning protection systems usually relies on analyzing the CG lightning flashes captured by the lightning locating system.…”

Section: Lightning Detection Techniquesmentioning

confidence: 99%

Implementation of Ground-Based Lightning Locating System Using Particle Swarm Optimization Algorithm for Lightning Mapping and Monitoring

et al. 2023

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Cloud-to-ground (CG) lightning is a natural phenomenon that poses significant threats to human safety, infrastructure, and equipment. The destructive impacts of lightning strikes on humans and their property have been a longstanding concern for both society and industry. Countries with high thunderstorm frequencies, such as Malaysia, experience significant fatalities and damage due to lightning strikes. To this end, a lightning locating system (LLS) was developed and deployed in a 400 km2 study area at the University Technology Malaysia (UTM), Johor, Malaysia for detecting cloud-to-ground lightning discharges. The study utilized a particle swarm optimization (PSO) algorithm as a mediator to identify the best location for a lightning strike. The algorithm was initiated with 30 particles, considering the outcomes of the MDF and TDOA techniques. The effectiveness of the PSO algorithm was found to be dependent on how the search process was arranged. The results of the detected lightning strikes by the PSO-based LLS were compared with an industrial lightning detection system installed in Malaysia. From the experimental data, the mean distance differences between the PSO-based LLS and the industrial LLS inside the study area was up to 573 m. Therefore, the proposed PSO-based LLS would be efficient and accurate to detect and map the lightning discharges occurring within the coverage area. This study is significant for researchers, insurance companies, and the public seeking to be informed about the impacts of lightning discharges.

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“…As MDF computes the triangulation area of the radiation direction and TDOA determines the inter-section of hyperbolas, a combination of MDF and TDOA is one of the best choices for a combined LLS. Each technique can provide independent results and finally, it is possible to find more accurate output by employing optimization techniques such as Particle Swarm Optimization (PSO) (Vahabi-Mashak et al, 2015). Localization of the lightning protection systems is com-monly based on the analysis of the captured CG lightning flashes by the lightning locating system (López and Passi, 1991;Chen et al, 2013;Mehranzamir et al, 2020).…”

Section: Lightning Detection Techniquesmentioning

confidence: 99%

Particle Swarm Optimization (PSO) algorithm for Ground-based Lightning Locating System (GLLS) in Johor, Malaysia: Hazard mitigation implications

Mehranzamir

Pour

Afrouzi

et al. 2022

Preprint

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The cloud to ground (CG) lightning has negative impacts on humans and properties. A lightning strike is a great concern to mankind and industry because of its detrimental impact on human safety, hazard, and equipment failures. There are different lightning detection methods, including time difference of arrival (TDOA) and magnetic direction finding (MDF). Using combined techniques is an innovative approach to achieve higher location accuracy and detection efficiency of lightning flashes. In this investigation, a Lightning locating system (LLS) was designed and implemented at University Technology Malaysia (UTM), Johor, Malaysia to detect the cloud to ground lightning discharges in a study area of 400 km2. A particle swarm optimization (PSO) algorithm was applied in this study as the combination mediator to find the optimum point of the lightning strike. The PSO was initialized by 30 particles based on the results of the MDF and TDOA methods. The performance of the PSO-based algorithm is known to be affected by the arrangement of the searching process. The results of the detected lightning strikes by the PSO-based LLS were validated using an industrial lightning detection system for December and March. In addition, the whole study area was divided into 36 equal sections to analyze the abundance of CG discharges in each section. From the experimental data, the mean distance differences between the PSO-based LLS and the industrial LLS inside the study area varied from 0 to 573 m. Therefore, the proposed PSO-based LLS is efficient and accurate to detect and map the lightning discharges occurring within the coverage area. Although an industrial LLS monitors a large area or a country with several sensors, the detected lightning discharges and the statistical data analysis of the captured flashes are not obtainable by public individuals. Meanwhile, estimation and localization of lightning strikes are necessary for the public to mitigate the problems related to lightning discharges. Moreover, this study will be significant for the researchers, the insurance companies, and public users to be aware of the detected storms and estimation of imminent rainfalls. The PSO-based LLS provides an accurate lightning detection system for a specific local region and can be implemented to regional scale in other parts of the world.

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Modeling of Time of Arrival Method for Lightning Locating Systems

Cited by 11 publications

References 28 publications

The Hunt for Missing Tornadoes: Using Satellite Imagery to Detect and Document Historical Tornado Damage in Canadian Forests

The Hunt for Missing Tornadoes: Using Satellite Imagery to Detect and Document Historical Tornado Damage in Canadian Forests

Implementation of Ground-Based Lightning Locating System Using Particle Swarm Optimization Algorithm for Lightning Mapping and Monitoring

Particle Swarm Optimization (PSO) algorithm for Ground-based Lightning Locating System (GLLS) in Johor, Malaysia: Hazard mitigation implications

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