Assessment of the Uncertainty for the Spatial Distribution of Lightning Discharge Density Based on the Smoothed Bootstrap Procedure and WWLLN Data: a Case Study

Bibliografiske detaljer
Parent link:International Journal on Engineering Applications (IREA)
Vol. 10, No. 2.— 2022.— [P. 138-148]
Institution som forfatter: Национальный исследовательский Томский политехнический университет Инженерная школа энергетики Научно-образовательный центр И. Н. Бутакова (НОЦ И. Н. Бутакова)
Andre forfattere: Belikova M. Yu. Marina Yurjevna, Baranovskiy N. V. Nikolay Viktorovich, Karanin A. V. Andrey Vladimirovich, Karanina S. Yu. Svetlana Yurjevna, Skrypnik A. N. Artem Nikolaevich
Summary:Title screen
Thunderstorm activity is the most common natural cause of forest fires. Such forest fires can affect the functioning of industrial and infrastructure facilities. An effective application of the deterministic-probabilistic approach is possible if there is a set of initial data, including cloud-to-ground lightning discharges. It is especially important to understand the boundaries of uncertainty in determining the spatial distribution of the density of lightning discharges in a controlled forest-covered area. The aim of this work is to develop a procedure for assessing the uncertainty of the spatial distribution of lightning discharge density using a smoothed bootstrap algorithm and World Wide Lightning Location Network (WWLLN) data. The novelty of the work is due to the use of WWLLN data in combination with bootstrap algorithm in order to assess uncertainty of spatial distribution of lightning activity. The main findings are: 1) algorithm of bootstrap procedure to assess uncertainty in lightning discharge density within spatial distribution; 2) program realization of this algorithm using QGIS and GRASS software; 3) case study results for the typical boreal zone, namely, Republic of Buryatia (Russian Federation). Conclusions based on the results of bootstrap assessment of lightning discharge density uncertainty are presented regarding spatial distribution of lightning discharges. These results are applicable for forest fire danger prediction in lightning activity conditions.
Sprog:engelsk
Udgivet: 2022
Fag:
Online adgang:https://doi.org/10.15866/irea.v10i2.20850
Format: Electronisk Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=668674

MARC

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200 1 |a Assessment of the Uncertainty for the Spatial Distribution of Lightning Discharge Density Based on the Smoothed Bootstrap Procedure and WWLLN Data: a Case Study  |f M. Yu. Belikova, N. V. Baranovskiy, A. V. Karanin [et al.] 
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300 |a Title screen 
330 |a Thunderstorm activity is the most common natural cause of forest fires. Such forest fires can affect the functioning of industrial and infrastructure facilities. An effective application of the deterministic-probabilistic approach is possible if there is a set of initial data, including cloud-to-ground lightning discharges. It is especially important to understand the boundaries of uncertainty in determining the spatial distribution of the density of lightning discharges in a controlled forest-covered area. The aim of this work is to develop a procedure for assessing the uncertainty of the spatial distribution of lightning discharge density using a smoothed bootstrap algorithm and World Wide Lightning Location Network (WWLLN) data. The novelty of the work is due to the use of WWLLN data in combination with bootstrap algorithm in order to assess uncertainty of spatial distribution of lightning activity. The main findings are: 1) algorithm of bootstrap procedure to assess uncertainty in lightning discharge density within spatial distribution; 2) program realization of this algorithm using QGIS and GRASS software; 3) case study results for the typical boreal zone, namely, Republic of Buryatia (Russian Federation). Conclusions based on the results of bootstrap assessment of lightning discharge density uncertainty are presented regarding spatial distribution of lightning discharges. These results are applicable for forest fire danger prediction in lightning activity conditions. 
461 |t International Journal on Engineering Applications (IREA) 
463 |t Vol. 10, No. 2  |v [P. 138-148]  |d 2022 
610 1 |a труды учёных ТПУ 
610 1 |a электронный ресурс 
610 1 |a assessment 
610 1 |a lightning discharge 
610 1 |a WWLLN 
610 1 |a forest fire danger 
610 1 |a Bootstrap 
610 1 |a uncertainty 
610 1 |a молния 
610 1 |a лесные пожары 
701 1 |a Belikova  |b M. Yu.  |g Marina Yurjevna 
701 1 |a Baranovskiy  |b N. V.  |c specialist in electrical engineering  |c Associate Professor of Tomsk Polytechnic University, Candidate of physical and mathematical sciences  |f 1978-  |g Nikolay Viktorovich  |3 (RuTPU)RU\TPU\pers\34172  |9 17706 
701 1 |a Karanin  |b A. V.  |g Andrey Vladimirovich 
701 1 |a Karanina  |b S. Yu.  |g Svetlana Yurjevna 
701 1 |a Skrypnik  |b A. N.  |g Artem Nikolaevich 
712 0 2 |a Национальный исследовательский Томский политехнический университет  |b Инженерная школа энергетики  |b Научно-образовательный центр И. Н. Бутакова (НОЦ И. Н. Бутакова)  |3 (RuTPU)RU\TPU\col\23504 
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