Cloud-to-ground lightning dipole moment from simultaneous observations by ELF receiver and combined direction finding and time-of-arrival lightning detection system

2011 ◽  
Vol 116 (D8) ◽  
Author(s):  
Zenon Nieckarz ◽  
Andrzej Kulak ◽  
Stanislaw Zieba ◽  
Anna Odzimek
Keyword(s):  
Dipole Moment ◽  
Detection System ◽  
Direction Finding ◽  
Time Of Arrival ◽  
Lightning Detection ◽  
Cloud To Ground Lightning

Localised Single-Station Lightning Detection by Using TOA Method

2013 ◽  
Vol 64 (4) ◽  
Author(s):  
Behnam Salimi ◽  
Zulkurnain Abdul-Malek ◽  
Kamyar Mehranzamir ◽  
Saeed Vahabi Mashak ◽  
Hadi Nabipour Afrouzi
Keyword(s):  
Radiation Source ◽  
Detection System ◽  
Linear Equations ◽  
Lightning Strike ◽  
Time Of Arrival ◽  
Lightning Detection ◽  
Single Station ◽  
Mathematical Equations ◽  
Non Linear Equations

Lightning is an electrical discharge during storms that can be monitored continuously from certain distances. It can be either within clouds (intra cloud), or between clouds and the ground (cloud-ground). There are various techniques used nowadays to locate lightning, and to determine various parameters produced from lightning. Each technique provides its own claimed performances. This paper attempts to provide instantaneous detection of lightning strike lightning location using the Time of Arrival (TOA) method of a single detection station (comprises of four antennas). It also models the whole detection system using suitable mathematical equations so as to give some understanding on the differences between the measured and calculated (theoretical) results. The measurement system is based on the application of mathematical and geometrical formulas. Several parameters such as the distance from the radiation source to the station and the lightning path are significant in influencing the accuracy of the results (elevation and azimuth angles). The role of each parameter is examined in detail using Matlab. This study solved the resultant non-linear equations by Newton-Raphson techniques. Methods to determine the radiation source which include the exact coordinate of a given radiation source in 3-dimensions were also developed. Further clarifications on the cause of errors in the single-station TOA method and techniques to reduce the errors are given.

scholarly journals A source location algorithm of lightning detection networks in China

2010 ◽  
Vol 28 (10) ◽  
pp. 1981-1991 ◽  
Author(s):  
Z. X. Hu ◽  
W. G. Zhao ◽  
H. P. Zhu
Keyword(s):  
Geodesic Distance ◽  
Spherical Surface ◽  
Onset Time ◽  
Initial Position ◽  
Accurate Solution ◽  
Electric Power System ◽  
Time Of Arrival ◽  
Oblate Spheroidal ◽  
Lightning Detection ◽  
Cloud To Ground Lightning

Abstract. Fast and accurate retrieval of lightning sources is crucial to the early warning and quick repairs of lightning disaster. An algorithm for computing the location and onset time of cloud-to-ground lightning using the time-of-arrival (TOA) and azimuth-of-arrival (AOA) data is introduced in this paper. The algorithm can iteratively calculate the least-squares solution of a lightning source on an oblate spheroidal Earth. It contains a set of unique formulas to compute the geodesic distance and azimuth and an explicit method to compute the initial position using TOA data of only three sensors. Since the method accounts for the effects of the oblateness of the Earth, it would provide a more accurate solution than algorithms based on planar or spherical surface models. Numerical simulations are presented to test this algorithm and evaluate the performance of a lightning detection network in the Hubei province of China. Since 1990s, the proposed algorithm has been used in many regional lightning detection networks installed by the electric power system in China. It is expected that the proposed algorithm be used in more lightning detection networks and other location systems.

System of Warning about Dangerous Atmospheric Phenomena in the North Caucasus for Objects of Economic Activity

2018 ◽  
Vol 931 ◽  
pp. 1019-1024
Author(s):  
Vitaliy A. Shapovalov
Keyword(s):  
Land Reclamation ◽  
Detection System ◽  
Radar Data ◽  
Automated System ◽  
Insurance Companies ◽  
North Caucasus ◽  
Weather Radars ◽  
The North ◽  
Lightning Detection ◽  
Atmospheric Phenomena

This paper presents the developed program-mathematical software for receiving, archiving, analysis and display of radar, lightning and satellite data on clouds and precipitation, interfacing of meteorological information. The program of processing of meteorological information "GIMET-2010" is established on a network of weather radars DMRL-C of the Russian Federation. An automated system combining radar and lightning detection system information applies to the command posts of the uniformed services on the fight against hail and centers of severe storm warning. Following items are provided: a receiving and transmitting to consumers the operational radar data on the actual weather; the detection, identification, and warning of hazardous weather phenomena for airports and populated areas; measurement of the intensity and amount of precipitation for agriculture, hydrological forecasts and land reclamation; obtaining precipitation map for agriculture and insurance companies.

scholarly journals An analysis of manual and autoanalysis for submicrosecond parameters in the typical first lightning return stroke

2021 ◽  
Vol 23 (3) ◽  
pp. 1451
Author(s):  
Muhammad Akmal Bahari ◽  
Zikri Abadi Baharudin ◽  
Tole Sutikno ◽  
Ahmad Idil Abdul Rahman ◽  
Mohd Ariff Mat Hanafiah ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Detection System ◽  
Programming Technique ◽  
Return Stroke ◽  
Zero Crossing ◽  
Manual Analysis ◽  
Lightning Detection ◽  
Crossing Time ◽  
Rising Time ◽  
Initial Peak

The mechanism on how lightning detection system (LDS) operated never been exposed by manufacturer since it was confidential. This scenario motivated the authors to explore the issue above by using MATLAB to develop autoanalysis software based on the feature extraction. This extraction is intended for recognizing the parameters in the first return stroke, and compare the measurement between the autoanalysis software and the manual analysis. This paper is a modification based on a previous work regarding autoanalysis of zero-crossing time and initial peak of return stroke using features extraction programming technique. Further, the parameter on rising time of initial peak is added in this autoanalysis programming technique. Finally, the manual analysis using WaveStudio (LeCroy product) of those two lightning parameters is compared with autoanalysis software. This study found that the autoanalysis produce similar result with the manual analysis, hence proved the reliability of this software.

scholarly journals A Climatology of Thunderstorms across Europe from a Synthesis of Multiple Data Sources

2019 ◽  
Vol 32 (6) ◽  
pp. 1813-1837 ◽  
Author(s):  
Mateusz Taszarek ◽  
John Allen ◽  
Tomáš Púčik ◽  
Pieter Groenemeijer ◽  
Bartosz Czernecki ◽  
...  
Keyword(s):  
Central Europe ◽  
Detection System ◽  
Thunderstorm Activity ◽  
Severe Weather ◽  
Data Sources ◽  
Annual Number ◽  
Central Mediterranean ◽  
Severe Thunderstorm ◽  
Lightning Detection ◽  
The Alps

Abstract The climatology of (severe) thunderstorm days is investigated on a pan-European scale for the period of 1979–2017. For this purpose, sounding measurements, surface observations, lightning data from ZEUS (a European-wide lightning detection system) and European Cooperation for Lightning Detection (EUCLID), ERA-Interim, and severe weather reports are compared and their respective strengths and weaknesses are discussed. The research focuses on the annual cycles in thunderstorm activity and their spatial variability. According to all datasets thunderstorms are the most frequent in the central Mediterranean, the Alps, the Balkan Peninsula, and the Carpathians. Proxies for severe thunderstorm environments show similar patterns, but severe weather reports instead have their highest frequency over central Europe. Annual peak thunderstorm activity is in July and August over northern, eastern, and central Europe, contrasting with peaks in May and June over western and southeastern Europe. The Mediterranean, driven by the warm waters, has predominant activity in the fall (western part) and winter (eastern part) while the nearby Iberian Peninsula and eastern Turkey have peaks in April and May. Trend analysis of the mean annual number of days with thunderstorms since 1979 indicates an increase over the Alps and central, southeastern, and eastern Europe with a decrease over the southwest. Multiannual changes refer also to changes in the pattern of the annual cycle. Comparison of different data sources revealed that although lightning data provide the most objective sampling of thunderstorm activity, short operating periods and areas devoid of sensors limit their utility. In contrast, reanalysis complements these disadvantages to provide a longer climatology, but is prone to errors related to modeling thunderstorm occurrence and the numerical simulation itself.

Detecting Multiple Ground Contacts in Cloud-to-Ground Lightning Flashes

2009 ◽  
Vol 26 (11) ◽  
pp. 2392-2402 ◽  
Author(s):  
Christina A. Stall ◽  
Kenneth L. Cummins ◽  
E. Philip Krider ◽  
John A. Cramer
Keyword(s):  
Standard Deviation ◽  
Rise Time ◽  
Random Errors ◽  
Peak Current ◽  
Video Recordings ◽  
Lightning Detection ◽  
Cloud To Ground Lightning ◽  
The U.S ◽  
Good Agreement ◽  
Cg Lightning

Abstract Video recordings of cloud-to-ground (CG) lightning flashes have been analyzed in conjunction with correlated stroke reports from the U.S. National Lightning Detection Network (NLDN) to determine whether the NLDN is capable of identifying the different ground contacts in CG flashes. For 39 negative CG flashes that were recorded on video near Tucson, Arizona, the NLDN-based horizontal distances between the first stroke and the 62 subsequent strokes remaining in a preexisting channel had a mean and standard deviation of 0.9 ± 0.8 km and a median of 0.7 km. The horizontal distances between the first stroke and the 59 new ground contacts (NGCs) had a mean and standard deviation of 2.3 ± 1.7 km and a median of 2.1 km. These results are in good agreement with prior measurements of the random errors in NLDN positions in southern Arizona as well as video- and thunder-based measurements of the distances between all ground contacts in Florida. In cases where the distances between ground contacts are small and obscured by random errors in the NLDN locations, measurements of the stroke rise time, estimated peak current, and stroke order can be utilized to enhance the ability of the NLDN to identify strokes that produce new ground terminations.

Fusion of a FBG-based health monitoring system for wind turbines with a fiber-optic lightning detection system

2008 ◽  
Author(s):  
Sebastian G. M. Krämer ◽  
Benjamin Wiesent ◽  
Mathias S. Müller ◽  
Fernando Puente León ◽  
Yarú Méndez Hernández
Keyword(s):  
Monitoring System ◽  
Wind Turbines ◽  
Health Monitoring ◽  
Fiber Optic ◽  
Detection System ◽  
Health Monitoring System ◽  
Lightning Detection

scholarly journals Algorithm for Improved QPE over Complex Terrain Using Cloud-to-Ground Lightning Occurrences

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 85
Author(s):  
Carlos Minjarez-Sosa ◽  
Julio Waissman ◽  
Christopher Castro ◽  
David Adams
Keyword(s):  
Complex Terrain ◽  
Convective Precipitation ◽  
North American Monsoon ◽  
Monsoon Region ◽  
Convective Rainfall ◽  
The Third ◽  
The North ◽  
Lightning Detection ◽  
Cloud To Ground Lightning ◽  
Noise Test

Lightning and deep convective precipitation have long been studied as closely linked variables, the former being viewed as a proxy, or estimator, of the latter. However, to date, no single methodology or algorithm exists for estimating lightning-derived precipitation in a gridded form. This paper, the third in a series, details the specific algorithm where convective rainfall was estimated with cloud-to-ground lightning occurrences from the U.S. National Lightning Detection Network (NLDN), for the North American Monsoon region. Specifically, the authors present the methodology employed in their previous studies to get this estimation, noise test, spatial and temporal neighbors and the algorithm of the Kalman filter for dynamically derived precipitation from lightning.

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