Methods to estimate lightning activity using WWLLN and RS data

Nikolay V. Baranovskiy, Marina Yu Belikova, Svetlana Yu Karanina, Andrey V. Karanin, Alena V. Glebova

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

Выдержка

The aim of the work is to develop a comprehensive method for assessing thunderstorm activity using WWLLN and RS data. It is necessary to group lightning discharges to solve practical problems of lightning protection and lightningcaused forest fire danger, as well as climatology problems using information on the spatial and temporal characteristics of thunderstorms. For grouping lightning discharges, it is proposed to use clustering algorithms. The region covering Timiryazevskiy forestry (Tomsk region, borders (55.93 - 56.86)x(83.94 - 85.07)) was selected for the computational experiment. We used the data on lightning discharges registered by the WWLLN network in this region on July 23, 2014. 273 lightning discharges were sampling. A relatively small number of discharges allowed us a visual analysis of solutions obtained during clustering.

Язык оригиналаАнглийский
Название основной публикации23rd International Symposium on Atmospheric and Ocean Optics
Подзаголовок основной публикацииAtmospheric Physics
РедакторыGennadii G. Matvienko, Oleg A. Romanovskii
ИздательSPIE
Том10466
ISBN (электронное издание)9781510614130
DOI
СостояниеОпубликовано - 1 янв 2017
Событие23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics - Irkutsk, Российская Федерация
Продолжительность: 3 июл 20177 июл 2017

Конференция

Конференция23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics
СтранаРоссийская Федерация
ГородIrkutsk
Период3.7.177.7.17

Отпечаток

Lightning
lightning
Thunderstorms
estimates
thunderstorms
Estimate
Lightning protection
Climatology
Forestry
forest fires
Forest Fire
Clustering algorithms
Discharge (fluid mechanics)
climatology
Fires
borders
Computational Experiments
Grouping
hazards
Clustering Algorithm

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Цитировать

Baranovskiy, N. V., Belikova, M. Y., Karanina, S. Y., Karanin, A. V., & Glebova, A. V. (2017). Methods to estimate lightning activity using WWLLN and RS data. В G. G. Matvienko, & O. A. Romanovskii (Ред.), 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics (Том 10466). [104665F] SPIE. https://doi.org/10.1117/12.2286780

Methods to estimate lightning activity using WWLLN and RS data. / Baranovskiy, Nikolay V.; Belikova, Marina Yu; Karanina, Svetlana Yu; Karanin, Andrey V.; Glebova, Alena V.

23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. ред. / Gennadii G. Matvienko; Oleg A. Romanovskii. Том 10466 SPIE, 2017. 104665F.

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

Baranovskiy, NV, Belikova, MY, Karanina, SY, Karanin, AV & Glebova, AV 2017, Methods to estimate lightning activity using WWLLN and RS data. в GG Matvienko & OA Romanovskii (ред.), 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. том. 10466, 104665F, SPIE, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, Irkutsk, Российская Федерация, 3.7.17. https://doi.org/10.1117/12.2286780
Baranovskiy NV, Belikova MY, Karanina SY, Karanin AV, Glebova AV. Methods to estimate lightning activity using WWLLN and RS data. В Matvienko GG, Romanovskii OA, редакторы, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. Том 10466. SPIE. 2017. 104665F https://doi.org/10.1117/12.2286780
Baranovskiy, Nikolay V. ; Belikova, Marina Yu ; Karanina, Svetlana Yu ; Karanin, Andrey V. ; Glebova, Alena V. / Methods to estimate lightning activity using WWLLN and RS data. 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. редактор / Gennadii G. Matvienko ; Oleg A. Romanovskii. Том 10466 SPIE, 2017.
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