Locating cloud-to-ground lightning flashes with simultaneous two-station measurements

Sonnadara, D.U.J.; Weerasekera, AB; Fernando, Imk; Lelwala, R; Jayaratne, K.P.S.C.; Ariyaratne, T. R.; Namasivayam, Sudalaimuthu; Bandara, K.R. Abhayasinghe

doi:10.4038/sljp.v1i0.166

Cited by 5 publications

(6 citation statements)

References 2 publications

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“…The system is able to reduce the detection error by 80% relative to previous measurements [36]- [38]. Sonnadara et al [37] studied the reconstruction of lightning strike locations on the basis of CG lightning flashes by using two wideband MDF stations. The direction finder's uncertainty localization accuracy of ±5 km within a 100 km radius was successfully optimized.…”

Section: Magnetic Direction Findermentioning

confidence: 99%

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Lightning Mapping: Techniques, Challenges, and Opportunities

et al. 2020

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Despite the significant progress in the understanding of the phenomenon of lightning and the physics behind it, locating and mapping its occurrence remain a challenge. Such localization and mapping of very high frequency (VHF) lightning radiation sources provide a foundation for the subsequent research on predicting lightning, saving lives, and protecting valuable assets. A major technical challenge in attempting to map the sources of lightning is mapping accuracy. The three common electromagnetic radio frequencybased lightning locating techniques are magnetic direction finder, time of arrival, and interferometer (ITF). Understanding these approaches requires critically reviewing previous attempts. The performance and reliability of each method are evaluated on the basis of the mapping accuracy obtained from lightning data from different sources. In this work, we review various methods for lightning mapping. We study the approaches, describe their techniques, analyze their merits and demerits, classify them, and derive few opportunities for further research. We find that the ITF system is the most effective method and that its performance may be improved further. One approach is to improve how lightning signals are preprocessed and how noise is filtered. Signal processing can also be utilized to improve mapping accuracy by introducing methods such as wavelet transform in place of conventional cross-correlation approaches. INDEX TERMS interferometer, lightning mapping, magnetic direction finder, time of arrival.

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Section: Magnetic Direction Findermentioning

confidence: 99%

“… Location accuracy is limited to the range of 0.5-1 km. VOLUME XX, 2020 [37]  CG lightning flashes were located on the basis of two wideband MDF stations.  Two MDF stations operated on the basis of two orthogonally looped antennas with a distance of 65 km.…”

Section: Refmentioning

confidence: 99%

Lightning Mapping: Techniques, Challenges, and Opportunities

et al. 2020

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“…The statistical analysis involved was based on the geometrical of magnetic finding. The system resulted in a detection error reduction by 80% from those in previous measurements [32][33][34]. Sonnadara et al [33] studied the reconstruction of the lightning strike locations based on CG lightning flashes by using two wideband MDF stations.…”

Section: Magnetic Direction Findermentioning

confidence: 99%

Lightning Mapping: Techniques, Challenges, and Opportunities

Alammari¹,

Alkahtani²,

Ahmad³

et al. 2020

Preprint

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Despite the significant progress made in studying the lightning phenomenon, precise location and mapping of its occurrence remain a challenge. Lightning mapping can be determined by studying the electromagnetic radiation accompanying the lightning discharges. It can contribute substantially to efforts made to protect lives and valuable assets. There are three main methods used to locate lightning, which are Magnetic Direction Finder (MDF), Time of Arrival (TOA), and Interferometer (ITF). A thorough study of these methods provides researchers with a guide to better understand and progress in this field. This paper reviews existing approaches used to locate and map lightning within these three methods. We study the implemented techniques, analyze their merits and demerits, and sort them in a way that facilitates extracting opportunities for further improvements. We conclude that for better development in determining the location and map of lightning, improving the processing of lightning signals and filtering the associated noise with it is essential. This includes introducing new processing methods such as wavelet transformation instead of the traditional cross-correlation. The use of artificial intelligence may also contribute a lot, particularly deep learning, to determining the type of lightning, which enables better mapping for the lightning and its occurrence. We also could conclude that unlike MDF and TOA, which can locate the lightning strike points, ITF can produce lightning discharge propagation images that can unveil the mechanism of lightning discharges. Finally, this paper serves as a reference for researchers focusing on lightning mapping to give them insight into the field.

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“…Using this as the selecting criterion, the records were passed through a computer program to select simultaneous hits. A detailed description of the filtering method is given elsewhere [1][2] . Whenever there was a mismatch between the recorded multiplicities by the two stations, the highest multiplicity of the two was taken as the correct multiplicity, attributing the difference to either attenuation of the signal due to the distance or differed threshold settings in the two DF stations.…”

Section: Methodsmentioning

confidence: 99%

“…In late 1998, a lightning direction finding (DF) network was implemented in Sri Lanka to record data pertaining to cloud-to-ground (CG) lightning flashes [1][2] . Such networks are widely used in many countries to gather data on lightning on a continuous basis.…”

Section: Introductionmentioning

confidence: 99%

Some Properties of Lightning Ground Flashes Observed in and around Sri Lanka, and their Seasonal Variations

et al. 2002

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Two lightning locating systems were utilised in obtaining the cloud-to-ground flash characteristics in Sri Lanka and in the surrounding area of the Indian Ocean. Over 5,000 flashes were recorded during the year 1999 covering 39 thunder days. The lightning data are presented in terms of polarity, multiplicity, and first return stroke peak current. The percentage of positive flashes observed in this study is fairly lower than that of temporal regions but when compared with similar studies in tropical regions there is no clear difference. Out of the 3% of the positive flashes reported, 95% were single stroke. On the contrary only 56% of the reported negative flashes were single stroke. The highest percentage of single stroke negative flashes was 74% in June and lowest was 38% in February. The monthly variation of the percentage of positive flashes ranged from 17% in June to 1% in September. The highest monthly average multiplicity of negative flashes of 2.6 was recorded in February and for all other months it was below 2. The monthly averages of the negative first stroke peak currents ranged from about 39kA in August to about 56kA in September.

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Locating cloud-to-ground lightning flashes with simultaneous two-station measurements

Cited by 5 publications

References 2 publications

Lightning Mapping: Techniques, Challenges, and Opportunities

Lightning Mapping: Techniques, Challenges, and Opportunities

Lightning Mapping: Techniques, Challenges, and Opportunities

Some Properties of Lightning Ground Flashes Observed in and around Sri Lanka, and their Seasonal Variations

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