Establishment of lightning detection sensors network in India: generation of essential climate variable and characterization of cloud-to-ground lightning occurrences

Taori, A.; Suryavanshi, Arun; Pawar, S. D.; Seshasai, M. V. R.

doi:10.1007/s11069-021-05042-8

Cited by 10 publications

(2 citation statements)

References 34 publications

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“…Schultz et al [2011] montrent que cet algorithme est plus performant avec l'activité électrique totale qu'avec des éclairs nuage-sol uniquement. Les orages informent aussi des variations atmosphériques à plus long terme, les éclairs étant même depuis 2018 considérés comme une variable climatique essentielle [Taori et al, 2021]. L'augmentation des températures globales entraînerait une augmentation du taux d'éclairs, eux-mêmes libérant des gaz à effet de serre (les oxydes d'azote, Price et al [1997]).…”

Section: Orages Et Atmosphèreunclassified

Localization and quantification of the acoustical power of lightning flashes

Bestard

Farges²,

Coulouvrat

2022

The Journal of the Acoustical Society of America

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Lightning is an ubiquitous source of infrasound, and an essential climate variable. To observe lightning flashes, thunder measurement efficiently complements electromagnetic methods. Using acoustical arrays, time delays between sensors inform on the direction of sound arrival, while the difference between emission time and sound arrival provides the source distance. Combining two allows a geometrical reconstruction of lightning flashes viewed as sets of sound sources. The measured sound amplitude can also be back-propagated, compensating for absorption and density stratification. This allows us to evaluate the acoustical power of each detected source and the total power of an individual flash. This methodology has been carried out to analyse data from two campaigns in Southern continental France in 2012 and in Corsica in 2018. In Corsica, power from reconstructed sources could also be forward-propagated towards several isolated microphones and compared to measurement there, providing an additional validation of the method. A large number of events from the two campaigns has been analysed, including negative and positive cloud to ground discharges and intra-cloud ones. The analysis outlines the method efficiency, and the strong variability of lightning as sound sources, in terms of both power spatial distribution and global values.

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Section: Orages Et Atmosphèreunclassified

Localization and quantification of the acoustical power of lightning flashes

Bestard

Farges²,

Coulouvrat

2022

The Journal of the Acoustical Society of America

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“…In a parallel effort, NRSC has initiated another Lightning Detection Sensor Network (LDSN) which is capable of detecting the cloud to ground lighting flashes with desired geolocation accuracies for the generation of Lightning Essential Climate Variable (L-ECV) as per the World Meteorological Organization (WMO) in the year 2016. The initial findings and L-ECV generation method are elaborated by Taori et al (2021Taori et al ( , 2022.…”

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confidence: 99%

On the Cloud to Ground Lightning Flash Current Estimates of the Lightning Detection Sensor Network (LDSN)

Degala,

Arun,

Taori

et al. 2024

Preprint

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The atmospheric lightning is one of the natural disasters which need to be considered in the sustainable development. The National Remote Sensing Centre (NRSC) has installed 46 lightning detection sensors (LDS) across the country. These sensors work in radio frequencies having their detection range up to 1000 km with more than 98% detection efficiency within 300 km range. The network is put in a way that sensors have about 50% sensor-to-sensor overlap in their detection ranges to enable high geolocation accuracy and maintain redundancy. The NRSC-LDS network (LDSN) estimates the current associated with each cloud to ground (CG) lightning flash which can be utilized for the risk assessment. The current estimates from one network to the other need to be inter-calibrated and harmonized. Present study compares the LDSN current estimates with Lightning Location Network (LLN) estimates and results are discussed with their impact on the estimation of vulnerable zones. A case study of lightning-induced fire event is presented to showcase the importance of the currents associated with lightning for future planning.

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