IEC 62858:2019
(Main)Lightning density based on lightning location systems - General principles
Lightning density based on lightning location systems - General principles
IEC 62858:2019 introduces and discusses all necessary measures to make reliable and homogeneous the values of ground flash density, NG and ground strike point density, NSG, obtained from lightning location systems (LLSs) in various countries. Only parameters that are relevant to risk assessment are considered. This second edition cancels and replaces the first edition published in 2015. This edition constitutes a technical revision. This edition includes the following significant technical changes with respect to the previous edition:
- Two informative annexes are introduced dealing with the determination of lightning density for risk calculation (Annex A) and ground strike point calculation methods (Annex B).
Densité de foudroiement basée sur des systèmes de localisation de la foudre - Principes généraux
L'IEC 62858:2019 décrit et étudie l'ensemble des mesures nécessaires pour rendre fiables et homogènes les valeurs de la densité de foudroiement au sol, NSG, et de la densité de points d'impact au sol, NSG, obtenues par des systèmes de localisation de la foudre (LLS) dans différents pays. Seuls les paramètres essentiels à l'évaluation du risque sont pris en compte. Cette deuxième édition annule et remplace la première édition parue en 2015. Cette édition constitue une révision technique. Cette édition inclut les modifications techniques majeures suivantes par rapport à l'édition précédente:
- Introduction de deux annexes informatives, traitant de la détermination de la densité de foudroiement pour le calcul du risque (Annexe A) et des méthodes de calcul concernant les points d'impact au sol (Annexe B).
General Information
Relations
Overview
IEC 62858:2019 - Lightning density based on lightning location systems - General principles - defines how to derive reliable, homogeneous lightning density values from Lightning Location Systems (LLSs). The standard focuses on the two primary inputs used for lightning risk assessment: ground flash density (NG) and ground strike-point density (NSG), and specifies general principles, performance requirements and validation approaches so that data from different countries and networks are comparable and fit for risk analysis.
This second edition (2019) is a technical revision of the 2015 edition and introduces two informative annexes:
- Annex A: Determination of lightning density for risk calculation.
- Annex B: Ground strike point (GSP) explanations and calculation methods.
Key topics and technical requirements
The standard addresses practical LLS characteristics and data-processing topics relevant to obtaining NG and NSG for risk assessment:
- Performance thresholds
- Flash detection efficiency (DE): annual average DE for cloud-to-ground (CG) flashes should be ≥ 80% in the region used for NG computation.
- Location accuracy (LA): median location accuracy for CG strokes should be better than 500 m.
- Classification accuracy: CG/IC classification accuracy should be ≥ 85% to avoid bias, especially for single-stroke flashes.
- A target NG error of ±20% or less is considered acceptable for lightning risk assessment.
- Data quality and processing
- Stroke-to-flash grouping, minimum observation periods, observation area, grid cell size, and edge-effect correction are specified to make densities homogeneous and comparable.
- Guidance on uptime, sensor baseline distance and sensor sensitivity as factors that affect DE and LA.
- Recommendation to avoid reporting NG with more than two decimal places.
- Validation methods
- Network self-referencing (statistical analysis of sensor timing error, confidence ellipses, reporting sensors).
- Ground-truth comparisons using independent techniques.
- Annex guidance
- Annex A links NG/NSG derivation directly to risk calculation workflows (e.g., IEC 62305).
- Annex B clarifies Ground Strike Point (GSP) concepts and calculation methods.
Applications and who uses this standard
IEC 62858:2019 is applicable to organizations and professionals who rely on accurate lightning density data:
- LLS owners, operators and data providers (network design, performance monitoring).
- Lightning protection engineers and consultants performing risk assessments (IEC 62305 compliance).
- Utilities, wind and solar asset owners, telecom and power network planners using NG/NSG for design and mitigation.
- Insurers, meteorological agencies and researchers using homogeneous lightning climatologies and loss modelling.
Related standards
- IEC 62305-1 - Protection against lightning - General principles
- IEC 62305-2 - Protection against lightning - Risk management
Keywords: IEC 62858:2019, lightning density, lightning location systems (LLS), ground flash density NG, ground strike-point density NSG, flash detection efficiency, location accuracy, lightning risk assessment.
Frequently Asked Questions
IEC 62858:2019 is a standard published by the International Electrotechnical Commission (IEC). Its full title is "Lightning density based on lightning location systems - General principles". This standard covers: IEC 62858:2019 introduces and discusses all necessary measures to make reliable and homogeneous the values of ground flash density, NG and ground strike point density, NSG, obtained from lightning location systems (LLSs) in various countries. Only parameters that are relevant to risk assessment are considered. This second edition cancels and replaces the first edition published in 2015. This edition constitutes a technical revision. This edition includes the following significant technical changes with respect to the previous edition: - Two informative annexes are introduced dealing with the determination of lightning density for risk calculation (Annex A) and ground strike point calculation methods (Annex B).
IEC 62858:2019 introduces and discusses all necessary measures to make reliable and homogeneous the values of ground flash density, NG and ground strike point density, NSG, obtained from lightning location systems (LLSs) in various countries. Only parameters that are relevant to risk assessment are considered. This second edition cancels and replaces the first edition published in 2015. This edition constitutes a technical revision. This edition includes the following significant technical changes with respect to the previous edition: - Two informative annexes are introduced dealing with the determination of lightning density for risk calculation (Annex A) and ground strike point calculation methods (Annex B).
IEC 62858:2019 is classified under the following ICS (International Classification for Standards) categories: 29.020 - Electrical engineering in general; 91.120.40 - Lightning protection. The ICS classification helps identify the subject area and facilitates finding related standards.
IEC 62858:2019 has the following relationships with other standards: It is inter standard links to IEC 62858:2015. Understanding these relationships helps ensure you are using the most current and applicable version of the standard.
You can purchase IEC 62858:2019 directly from iTeh Standards. The document is available in PDF format and is delivered instantly after payment. Add the standard to your cart and complete the secure checkout process. iTeh Standards is an authorized distributor of IEC standards.
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Lightning density based on lightning location systems – General principles
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IEC 62858 ®
Edition 2.0 2019-10
REDLINE VERSION
INTERNATIONAL
STANDARD
colour
inside
Lightning density based on lightning location systems – General principles
INTERNATIONAL
ELECTROTECHNICAL
COMMISSION
ICS 29.020; 91.120.40 ISBN 978-2-8322-7497-2
– 2 – IEC 62858:2019 RLV © IEC 2019
CONTENTS
FOREWORD . 3
INTRODUCTION . 5
1 Scope . 6
2 Normative references . 6
3 Terms, definitions, abbreviated terms and symbols . 6
3.1 Terms and definitions . 6
3.2 Abbreviated terms and symbol . 8
4 General requirements . 8
4.1 General . 8
4.2 Stroke-to-flash grouping . 9
4.3 Minimum observation periods . 9
4.4 Observation area . 9
4.5 Grid cell size . 10
4.6 Edge effect correction . 10
5 Validation of lightning location system performance characteristics . 10
Annex A (informative) Determination of lightning density for risk calculation . 12
Annex B (informative) Ground strike points (GSPs) explanations and calculation
methods . 13
Bibliography . 14
Figure A.1 – High resolution full climatology (HRFC) N data. 12
t
INTERNATIONAL ELECTROTECHNICAL COMMISSION
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LIGHTNING DENSITY BASED ON LIGHTNING LOCATION SYSTEMS –
GENERAL PRINCIPLES
FOREWORD
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– 4 – IEC 62858:2019 RLV © IEC 2019
International Standard IEC 62858 has been prepared by IEC technical committee 81:
Lightning protection.
This second edition cancels and replaces the first edition published in 2015. This edition
constitutes a technical revision.
This edition includes the following significant technical changes with respect to the previous
edition:
Two informative annexes are introduced dealing with the determination of lightning density for
risk calculation (Annex A) and ground strike point calculation methods (Annex B).
The text of this International Standard is based on the following documents:
FDIS Report on voting
81/627A/FDIS 81/634/RVD
Full information on the voting for the approval of this International Standard can be found in
the report on voting indicated in the above table.
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INTRODUCTION
International standards for lightning protection (e.g. IEC 62305-2) provide methods for the
evaluation of the lightning risk on buildings and structures.
The lightning ground flash density N , defined as the mean number of lightning flashes to
G
ground per square kilometre per year, and the ground strike point density N , defined as the
SG
mean number of ground strike points per square kilometre per year is are the primary input
parameters to perform such an evaluation (see Annex A).
In many areas of the world N is derived from data for risk evaluation are provided by
G
lightning location systems (LLSs), but no common rule exists defining requirements either for
their performance or for the elaboration of the measured data.
– 6 – IEC 62858:2019 RLV © IEC 2019
LIGHTNING DENSITY BASED ON LIGHTNING LOCATION SYSTEMS –
GENERAL PRINCIPLES
1 Scope
This document introduces and discusses all necessary measures to make reliable and
homogeneous the values of ground flash density, N and ground strike point density, N ,
G SG
obtained from lightning location systems (LLSs) in various countries. Only parameters that are
relevant to risk assessment are considered.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their
content constitutes requirements of this document. For dated references, only the edition
cited applies. For undated references, the latest edition of the referenced document (including
any amendments) applies.
IEC 62305-1, Protection against lightning – Part 1: General principles
IEC 62305-2, Protection against lightning – Part 2: Risk management
3 Terms, definitions, abbreviated terms and symbols
3.1 Terms and definitions
For the purposes of this document, the terms and definitions given in IEC 62305-1 and
IEC 62305-2 and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following
addresses:
• IEC Electropedia: available at http://www.electropedia.org/
• ISO Online browsing platform: available at http://www.iso.org/obp
3.1.1
cloud-to-ground lightning
CG
discharge that is comprised of one or more cloud-to-ground lightning strokes that propagate
from cloud to ground or vice versa and lead to a net transfer of charge between cloud and
ground
Note 1 to entry: This note applies to the French language only.
3.1.2
cloud lightning
IC
discharge occurring within or among thunderclouds (intracloud), or between thunderclouds
(intercloud), or between cloud and air, without a ground termination
Note 1 to entry: This note applies to the French language only.
3.1.3
first return stroke
first stroke to ground of a cloud-to-ground lightning discharge
Note 1 to entry: The stepped leader and attachment process precede the first return stroke.
3.1.4
subsequent stroke
subsequent stroke to ground that follows a previous (return) stroke in the same flash
Note 1 to entry: A subsequent stroke is preceded by a dart leader and may or may not have the same ground
strike-point as any previous (return) stroke in the same flash.
3.1.5
multiplicity
number of first and subsequent strokes in a cloud-to-ground lightning flash
3.1.1
ground flash density
N
G
-2 -1
mean number of cloud-to-ground flashes per unit area per unit time (flashes x km x year )
3.1.2
ground strike-point density
N
SG
mean of the number of strike-points to ground or to ground based objects per unit area per
-2 -1
unit time (strike-points x km x year )
3.1.3
lightning sensor
device that measures electromagnetic signals produced by lightning discharges
3.1.4
lightning location system
LLS
network of lightning sensors that work together to detect and geolocate lightning events within
the area of the system’s coverage
Note 1 to entry: This note applies to the French language only.
3.1.5
confidence ellipse
ellipse centred on the estimated ground strike-point, describing the degree of confidence of
the location estimation (e.g. 50 %, 90 %, 99 %) based on sensor measurement errors
Note 1 to entry: The confidence ellipse is described in terms of the lengths of the semi-major and semi-minor
axes as well as the bearing of the semi-major axis.
3.1.6
uptime
duration of fully functional operation of a lightning location system sensor, expressed as a
percentage of the total observation time
3.1.7
stroke detection efficiency
flash detection efficiency
percentage of strokes or flashes detected as a percentage of the total number of strokes or
flashes occurring in reality
3.1.8
median location accuracy
median value of the distances between real stroke locations and the stroke locations given by
the lightning location system
– 8 – IEC 62858:2019 RLV © IEC 2019
3.2 Abbreviated terms and symbols
CG cloud-to-ground lightning
DE flash detection efficiency
GSP ground strike point
IC cloud lightning intra-cloud and inter-cloud
LA location accuracy
LLS lightning location system
N ground flash density
G
N ground strike-point density
SG
4 General requirements
4.1 General
The performance characteristics of a lightning location system (LLS) determine the quality of
the lightning data available for calculating N [3, 15] [1] . A value of N with an error of ±20 %
G G
or less is deemed to be acceptable adequate for lightning risk assessment. Data from any
LLS that is able to detect CG lightning and accurately determine the point of strike of CG
strokes can be used for the purpose of N computation. The following LLS performance
G
characteristics are required for computation of N with adequate accuracy.
G
• Flash detection efficiency (DE): The value of the annual average flash detection efficiency
of an LLS for CG lightning shall be at least 80 % in the region over which N has to be
G
computed. This DE is usually obtained within the interior of the network. The interior of the
network is defined as the region within the boundary defined by the outermost adjacent
sensors of the network.
• Location accuracy (LA): The value of the median location accuracy of an LLS for CG
strokes shall be better than 500 m in all regions in the region over which N has to be
G
computed. This LA is usually obtained within the interior of the network.
• Classification accuracy: In a network with a flash DE meeting the criteria set for N
G
calculation, erroneously low or high values of N will be identified if when too many CG
G
strokes are misclassified as cloud pulses (or vice versa, this may lead to erroneously low
or high values of N ). This is especially true for single-stroke CG flashes. A classification
G. .
accuracy (CG flashes not misclassified as IC) of at least 85% is required.
It is not recommended to use N values having more than 2 decimals.
G
These performance characteristics of an LLS can be determined using a variety of methods
including network self-referencing (using statistical analysis of parameters such as standard
deviation of sensor timing error, semi-major axis length of the 50 % confidence ellipse, and
the number of reporting sensors, which may be known from the LLS manufacturer or available
from the LLS data) and comparison against ground-truth lightning data obtained using various
techniques. These methods are discussed in Clause 5. A performance evaluation based on
the methods described in Clause 5 and all the relevant basics of the network have to be
provided on request.
The flash DE, LA, and classification accuracy of an LLS depend on a few fundamental
characteristics of the network. LLS owners, operators, and data-providers should consider the
following factors while designing and maintaining their networks to ensure that the lightning
data are of adequate quality for N computation.
G
– Sensor baseline distance: The distance between adjacent sensors in an LLS or so called
sensor baseline distance is influenced by the area of desired coverage and the sensitivity
of individual sensors. Sensor baseline distance is one of the factors that determine the DE
___________
Numbers in square brackets refer to the Bibliography.
and LA of an LLS. The maximum sensor baseline distance of an LLS shall be such that
the DE and LA of the network meet the criteria for N calculation described above.
G
– Sensor sensitivity: The sensitivity of sensors in an LLS primarily determines the ability of
the network to detect lightning events of different peak currents. The sensitivity of sensors
in an LLS shall be such that lightning events with peak currents in the range of 5 kA to
300 kA are detected and reported by the LLS. Sensor sensitivity is determined by various
factors such as trigger threshold, electronic gain, sensor bandwidth, and background
electromagnetic noise.
– Sensor uptime: The uptime of different sensors in a network determines the DE and LA of
the network. The spatial and temporal variations of DE and LA are determined by the
location of sensors that are up and contributing to the network. Hence it is important to
guarantee that LLS sensors are up and running with no interruption.
4.2 Stroke-to-flash grouping
Return strokes detected by lightning location systems shall be grouped into flashes for N
G
calculation. Multiple ground strike-points are included in the same flash. This grouping is done
based on a spatio-temporal window.
A subsequent stroke is grouped with the first return stroke to form a flash if the following
criteria are met:
a) the stroke occurs less than or equal to 1 s after the first return stroke;
b) the location of the stroke is less than or equal to 10 km from the first return stroke;
c) the time interval for successive strokes is less than or equal to 500 ms.
The flash position is assumed to be the location of the first stroke.
Multiple ground strike -points shall be included in the same flash using the above criteria.
Currently a multiplication factor of 2, relating N to N shall be used [2].
G SG
Strokes can also be grouped into ground strike points to obtain N based on different
SG
algorithms described in Annex B.
4.3 Minimum observation periods
A sufficiently long sampling period is required to ensure that short time scale variations in
lightning parameters due to a variety of meteorological oscillations are accounted for.
Additionally large scale climatological variations limit the validity of historic data. Some
lightning detection networks have been recording lightning data for several decades and
during this time there have been measurable changes to the global meteorology climate.
A set of lightning data for at least 10 full calendar years is required, with the newest data used
not being older than five years. The data should be as continuous as possible, unless the data
does not fulfil the performance requirements in some particular years which have then to be
removed.
4.4 Observation area
The observation area is an area over which lightning data of quality as described above are
available.
Different networks and sensor technologies will have different sensitivities with which they
detect lightning. Network coverage falls off outside the boundaries of a network. In general,
lightning data within half the average sensor baseline distance (distance between adjacent
sensors in the network) from the boundary of the network should be of sufficient quality for N
G
calculation [11].
– 10 – IEC 62858:2019 RLV © IEC 2019
4.5 Grid cell size
Ground flash density (N ) values vary annually and regionally. Lightning data have to be
G
evaluated as a raster map, i.e. a gridded array of cells constrained by a geographic boundary:
the area of interest is divided into a regular grid (tessellation of the geographic area) and the
N calculation function is applied to all the flashes occurring within the grid. The resulting
G
value is then assumed to be the meaningful value within that area.
Grid size shall has to be chosen in such a way that the dimensions of each cell and the
number of years considered both comply with the minimum requirements obtained from
Formula (1), following Poisson distribution and the law of rare events, thus obtaining an
uncertainty of less than 20 % at 90 % confidence level [82].
NT××A ≥ 80 (1)
G obs cell
where:
-2 -1
N is the ground flash density, in km year ;
G
T is the observation period, in years;
obs
A is the area of each single cell, in km .
cell
The data used in this analysis shall conform to the requirements of both 4.2 and 4.3. The
minimum permissible cell dimension, irrespective of ground flash density and observation
period, shall not be less than double the median location accuracy.
4.6 Edge effect correction
As defined in 4.5 the size of the smallest cell that can be considered should be such that it
contains contain at least 80 flashes. In order to avoid edge effects for this cell the N value
G
shall be obtained by integrating over a finer sub-grid of 1 km x 1 km resolution.
5 Validation of lightning location system performance characteristics
The performance characteristics of an LLS determine the quality of the lightning data
available. These performance characteristics include:
– detection efficiency for IC and CG flashes and CG strokes;
– location accuracy;
– peak current estimation accuracy; and
– lightning classification accuracy.
As stated in Clause 4, for N and N the determination of CG flash DE, LA, and lightning
G SG,
classification accuracy is of primary importance. These performance characteristics can be
evaluated using a variety of techniques which are summarized below.
a) Network self-reference: In this technique, statistical analysis of parameters (e.g. [11])
such as standard deviation of sensor timing error, semi-major axis length of the 50 %
confidence ellipse, and the number of reporting sensors, is used to infer the LA and DE of
an LLS. Examples of such studies are found in [3], [4] and [75]. This method requires data
collected by the network after it has been properly calibrated. It can provide a good
estimate of the network’s performance in a cost-effective, practical manner.
b) Rocket-triggered lightning and tall object studies: This method uses data from rocket-
triggered lightning experiments or lightning strikes to tall objects (e.g. instrumented
towers) as ground-truth to evaluate the performance characteristics of an LLS within
whose coverage area the triggered lightning facility or the tall object is located. The LA,
DE, peak current estimation accuracy, and lightning classification accuracy of an LLS can
be measured using this method. Examples of studies using rocket-triggered lightning for
LLS performance evaluation include [6], [8], and [12], [13]. While these methods provide
the best ground-truth data for performance characteristics validation for CG lightning (and
are the only ways to directly validate peak current estimation accuracy of an LLS), they
may be very expensive, may not be practical for all regions (as there are only a few
triggered lightning facilities and instrumented towers across the world), and are a valid
indicator of LLS performance only for the region where the rocket-triggered lightning
facility or tall object is located (especially in cases where the performance of the LLS is
expected to vary significantly from region to region). Examples of studies using rocket-
triggered lightning or lightning to tall structures for LLS performance evaluation include
[6], [7], and [8]. These methods provide the best ground-truth data for performance
characteristics validation for CG lightning. In addition, these methods are the only ways to
directly validate peak current estimation accuracy of an LLS. However, they may be very
expensive and may not be practical for all regions. There are only a few triggered lightning
facilities and instrumented towers across the world. The results obtained from these
methods are valid indicators of LLS performance only for the region where the rocket-
triggered lightning facility or instrumented tower is located. Additionally, rocket-triggered
lightning provides data for return strokes similar to only subsequent strokes in natural
lightning. No data for first strokes in natural lightning can be obtained using this
technique. This is also often the case for lightning strikes to tall objects depending upon
the height of the object, local terrain, storm type, and other factors. Since first strokes in
natural lightning are expected to have, on average, peak fields and currents that are a
factor of two larger than those for subsequent strokes (e.g. [9]), CG flash and stroke DE
estimated for an LLS using these methods may be somewhat of an underestimate.
c) Video camera studies: Lightning data obtained using video cameras can be used as
ground-truth to evaluate the performance characteristics of an LLS within whose coverage
area the lightning discharges occur. The LA, DE, and lightning classification accuracy of
an LLS can generally be estimated using this method. Examples of studies using video
cameras for LLS performance evaluation include [18] and [149]. In this method, data
collection can be time consuming and challenging because the exact locations of lightning
discharges to be captured on video cannot be predicted. Additional instrumentation such
as antennas measuring the electric field from lightning discharges is often required for this
technique.
d) Inter-comparison among networks: The performance of one LLS that is being tested can
be compared against another LLS that may be used as reference, as long as the
reference LLS is extremely well calibrated and its performance has been characterized
independently. This method allows inferences to be made about the detection efficiency
and location accuracy of the test LLS relative to the reference LLS. If the reference
network provides VHF lightning mapping, inference about the test network’s IC detection
efficiency capability can be made, for example on plausibility of IC pulses or IC-CG
discrimination. Examples of such studies include [10]. One limitation of this technique is
that the test and reference networks have to overlap substantially and the results are only
valid for the overlapping region. Further, if the performance of the reference network is
unknown or if the reference network is not well calibrated, any inferences about the test
network’s performance are invalid.
While one or a combination of the above techniques can be used to evaluate the performance
characteristics of an LLS, it is important to understand the strengths and weaknesses of the
methods used, in order to obtain reliable estimates of LLS performance characteristics.
– 12 – IEC 62858:2019 RLV © IEC 2019
Annex A
(informative)
Determination of lightning density for risk calculation
The lightning ground flash density N is the number of lightning flashes per square kilometre
G
per year. In many areas of the world this value can be derived from data provided by local
lightning location systems (LLSs) according to this document.
Historically N was determined from thunderstorm days or with the data of lightning flash
G
counters. Because nowadays more accurate methods to determine N exist, the usage of
G
thunderstorm days or data from lightning flash counters is no longer recommended.
In areas without ground-based lightning location systems, the recommended estimate of
ground flash density [11] is:
NN0,25× (A.1)
Gt
N being the total (CG + IC) density of optical recorded flashes per km per year, obtained
t
through the NASA website (https://lightning.nsstc.nasa.gov/data/data_lis-otd-
climatology.html). Figure A.1 gives an overview of total densities N all over the world.
t
SOURCE: https://ghrc.nsstc.nasa.gov/pub/lis/climatology/LIS-OTD/HRFC/browse/HRFC_COM_FR_V2.3.2015.png
reproduced with the permission from the authors.
Figure A.1 – High resolution full climatology (HRFC) N data
t
NOTE In most areas of the world, an indication of lightning activity can be obtained from observations of lightning
optical transients. Satellite-based sensors respond to all types of lightning with relatively uniform coverage. With
sufficient averaging, optical transient density data provide better estimates of ground flash density than thunder
observations, which have a wide range of relations between ground flash density and thunderstorm hours or
thunderstorm days. There are also regional variations in the ratio of ground flashes (CG) to total flashes (CG + IC).
Often flashes exhibit multiple ground strike-points. Modern LLSs may provide N directly
SG
according to one of the methods described in Annex B. In case of availability of N from
SG
LLSs, using this data is recommended if the overall N results were independently validated.
SG
=
Annex B
(informative)
Ground strike points (GSPs) explanations and calculation methods
About half of negative cloud-to-ground lightning flashes exhibit several ground strike points.
This happens when a given dart leader partly follows the preceding return stroke channel,
ending by creating its own path to the ground. Every ground strike point represents a threat
and should be accounted for in the lightning risk calculation.
Based on high resolution lightning location data it becomes possible to identify almost all the
different attachment points in a cloud-to-ground lightning flash.
There are different algorithms available to determine ground strike points for LLS data with
advantages and disadvantages:
• Cummins [12] employed discriminant analysis to create a “vote count” based on several
parameters, including location difference and other parameters that can help identify new
ground strike points, for example rise time. This method has the potential to identify new
ground strike points when the location uncertainty is larger than the separation distance.
The “vote” approach weakens the location difference analysis when the locations are well-
known. This method is highly dependent on the quality of the rise-time parameter but
some LLS technologies may not provide the rise time and peak-to-zero time information
at all.
• Pédeboy [13], [14], [15] implemented a reliable clustering algorithm based on the k-means
method. This algorithm does not employ a complete statistical treatment of the error
geometry embodied in the error ellipses (it is just scaled by the size of the confidence
ellipse) and has no mechanism to distinguish between individual ground strike points when
the location uncertainty is larger than the separation distance of the ground strike points.
• Campos [16], [17] does a rigorous statistical job of evaluating the location uncertainty by
using the geometry of the error ellipse in the full latitude/longitude space, while embracing
the strengths of the k-means approach developed by Pédeboy. This method has the same
potential weakness as the approach from Pédeboy, in that it has no mechanism to “refine”
the classification when the location uncertainty is larger than the separation distance.
After applying one of these algorithms to LLS data, the ground strike point density can be
determined spatially according to the same rules as the ground flash density.
– 14 – IEC 62858:2019 RLV © IEC 2019
Bibliography
[1] BIAGI, C.J., CUMMINS, K.L., KEHOE, K.E. and KRIDER, E:P. (2007), National
Lightning Detection Network (NLDN) Performance in Southern Arizona, Texas, and
Oklahoma in 2003–2004, J. Geophys. Res., 112, D05208, doi:10.1029/2006JD007341.
[2] BOUQUEGNEAU, C., KERN, A. and ROUSSEAU, A. (2012), Flash Density applied to
th
Lightning Protection Standards, Ground’2012 & 5 LPE, Bonito, Brazil, 26-30
November.
[3] CIGRE Report 376, April 2009, Working Group C4.404: Cloud-to-ground Lightning
Parameters derived from Lightning Location Systems – The Effects of System
Performance
[4] CUMMINS, K.L., MURPHY, M.J., CRAMER, J.A., SCHEFTIC, W., DEMETRIADES, N.
and NAG, A. (2010), Location accuracy improvements using propagation corrections: a
st
case study of the U.S. National Lightning Detection Network, 21 Intl. Lightning
Detection Conf., Orlando, FL, U.S., 19-20 April.
[5] DIENDORFER, G. (2008): Some Comments on the Achievable Accuracy of Local
Ground Flash Density Values, International Conference on Lightning Protection (ICLP).
[6] JERAULD, J., RAKOV, V.A., UMAN, M.A., RAMBO, K.J., JORDAN, D.M., CUMMINS,
K.L. and CRAMER, J.A. (2005), An Evaluation of the Performance Characteristics of
the U.S. National Lightning Detection Network in Florida using Rocket-triggered
lightning, J. Geophys. Res., 110, D19106, doi:10.1029/2005JD005924.
[7] NACCARATO, K.P., PINTO Jr., O. and MURPHY, M.J. (2008), Performance Analysis
rd
of the BrasilDAT network, 2008 Intl. Conf. on Grounding and Earthing / 3 Intl. Conf.
on Lightning Physics and Effects, Florianopolis, Brazil, 16-20 November, pp. 329-338.
[8] NAG, A., MALLICK, S., RAKOV, V.A., HOWARD, J.S., BIAGI, C.J., HILL, J.D., UMAN,
M.A., JORDAN, D.M., RAMBO, K.J., JERAULD, J.E., DeCARLO, B.A., CUMMINS, K.L.
and CRAMER, J.A. (2011): Evaluation of U.S. National Lightning Detection Network
Performance Characteristics using Rocket-triggered Lightning Data acquired in 2004-
2009, J. Geophys. Res., vol. 116, D02123, doi:10.1029/2010JD014929.
[9] NAG, A., RAKOV, V.A., SCHULZ, W., SABA, M.M.F., THOTTAPPILLIL, R., BIAGI,
C.J., OLIVEIRA FILHO, A., KAFRI, A., THEETHAYI, N. and GOTSCHL, T. (2008), First
versus Subsequent Return-stroke Current and Field Peaks in Negative Cloud-to-
ground Lightning Discharges, J. Geophys. Res., 113, D19112,
doi:10.1029/2007JD009729.
[10] POELMAN, D.R., SCHULZ, W. and VERGEINER, C. (2013): Performance
Characteristics of Distinct Lightning Detection Networks covering Belgium, J. Atmos.
Ocean. Tech., vol. 30, pp. 942-951.
[11] SCHULZ, W. (1997), Performance Evaluation of Lightning Location Systems. Ph.D.
Thesis, Technical University of Vienna.
[12] SCHULZ, W., VERGEINER, C., PICHLER, H., DIENDORFER, G., PACKET, S. et al.
(2012), Validation of the Austrian Lightning Location System ALDIS for Negative
Flashes. CIGRE Symposium.
[13] SCHULZ, W., PICHLER, H., DIENDORFER, G., VERGEINER, C., PACK, S. (2013):
Validation of Detection of Positive Flashes by the Austrian Lightning Location System
th
(ALDIS), 12 Intl. Symposium on Lightning Protection (XII SIPDA), Belo Horizonte,
Brazil, 7-11 October, paper 2.2.
[14] SCHULZ, W., PEDEBOY, S., VERGEINER, C., DEFER, E. and RISON, W. (2014):
Validation of the EUCLID LLS during HyMeX SOP1, International Lightning Detection
Conference, Tucson.
[15] SCHULZ, W., PEDEBOY, S., SCHULZ, W. (2014): Validation of the ground strike-point
identification algorithm based on ground truth data, International Lightning Detection
Conference, Tucson.
[1] CIGRE Report 376, “Cloud-to-Ground Lightning Parameters Derived from Lightning
Location Systems – The Effects of System Performance,” CIGRE Report 376, 2009
[2] G. Diendorfer, “Some Comments on the Achievable Accuracy of Local Ground Flash
Density Values,” in 29th International Conference on Lightning Protection (ICLP),
2008, no. June, p. 1–6
[3] W. Schulz, “Performance Evaluation of Lightning Location Systems,” PhD Thesis,
Technical University of Vienna, 1997
[4] K. L. Cummins, M. J. Murphy, J. A. Cramer, W. D. Scheftic, N. W. S. Demetriades, and
A. Nag, “Location accuracy improvements using propagation corrections: a case study
of the U.S. National Lightning Detection Network,” in 21st International Lightning
Detection Conference and 3rd International Lightning Meteorology Conference
(ILDC/ILMC), 2010
[5] K. P. Naccarato, O. J. Pinto, and M. J. Murphy, “Performance Analysis of the
BrasilDAT network,” in International Conference on Grounding and Earthing and 3rd
International Conference on Lightning Physics and Effects (GROUND/LPE), 2008
[6] J. E. Jerauld et al., “An evaluation of the performance characteristics of the U.S.
National Lightning Detection Network in Florida using rocket-triggered lightning,” J.
Geophys. Res. Atmos., vol. 110, no. D19, p. D19106, 2005
[7] A. Nag et al., “Evaluation of U.S. National Lightning Detection Network performance
characteristics using rocket-triggered lightning data acquired in 2004–2009,” J.
Geophys. Res. Atmos., vol. 116, no. D2, p. D02123, 2011
[8] W. Schulz, G. Diendorfer, S. Pedeboy, and D. R. Poelman, “The European lightning
location system EUCLID – Part 1: Performance analysis and validation,” Nat. Hazards
Earth Syst. Sci., vol. 16, no. 2, p. 595–605, 2016
[9] W. Schulz, S. Pédeboy, C. Vergeiner, E. Defer, and W. Rison, “Validation of the
EUCLID LLS during HyMeX SOP1,” in International Lightning Detection Conference
and International Lightning Meteorology Conference (ILDC/ILMC), 2014
[10] D. R. Poelman, W. Schulz, and C. Vergeiner, “Performance Characteristics of Distinct
Lightning Detection Networks Covering Belgium,” J. Atmos. Ocean. Technol., vol. 30,
no. 5, p. 942–951, 2013
[11] W. A. Chisholm, “Estimates of Lightning Ground Flash Density using Optical Transient
Density,” in IEEE PES Transmission and Distribution Conference and Exposition (IEEE
Cat. No.03CH37495), 2003, vol. 3, p. 1068–1071
– 16 – IEC 62858:2019 RLV © IEC 2019
[12] K. L. Cummins, “Analysis of Multiple Ground Contacts in Cloud-to-ground Flashes
Using LLS Data: The Impact of Complex Terrain,” in International Lightning Detection
Conference and International Lightning Meteorology Conference (ILDC/ILMC), 2012
[13] S. Pédeboy, “Identification of the multiple ground contacts flashes with lightning
location systems,” in 22nd International Lightning Detection Conference and 4th
International Lightning Meteorology Conference (ILDC/ILMC), 2012
[14] S. Pédeboy and W. Schulz, “Validation of a ground strike point identification algorithm
based on ground truth data,” in International Lightning Detection Conference and
International Lightning Meteorology Conference (ILDC/ILMC), 2014
[15] W. Schulz, S. Pedeboy, and M. M. F. Saba, “LLS Detection Efficiency of Ground Strike
Points,” in Lightning Protection (ICLP), 2014 International Conference on, 2014, no. 2,
p. 381–384
[16] L. Z. S. Campos, K. L. Cummins, and O. J. Pinto, “An algorithm for identifying ground
strike points from return stroke data provided by Lightning Location Systems,” in Asia-
Pacific Conference on Lightning (APL), 2015, p. 475–478
[17] L. Z. S. Campos, “On the mechanisms that lead to multiple ground contacts in
lightning,” PhD Thesis, INPE, Brazil, 2016
___________
IEC 62858 ®
Edition 2.0 2019-10
INTERNATIONAL
STANDARD
NORME
INTERNATIONALE
colour
inside
Lightning density based on lightning location systems – General principles
Densité de foudroiement basée sur des systèmes de localisation
de la foudre (LLS) – Principes généraux
– 2 – IEC 62858:2019 © IEC 2019
CONTENTS
FOREWORD . 3
INTRODUCTION . 5
1 Scope . 6
2 Normative references . 6
3 Terms, definitions, abbreviated terms and symbols . 6
3.1 Terms and definitions . 6
3.2 Abbreviated terms and symbols . 7
4 General requirements . 7
4.1 General . 7
4.2 Stroke-to-flash grouping . 8
4.3 Minimum observation periods . 9
4.4 Observation area . 9
4.5 Grid cell size . 9
4.6 Edge effect correction .
...
IEC 62858 ®
Edition 2.0 2019-10
INTERNATIONAL
STANDARD
NORME
INTERNATIONALE
colour
inside
Lightning density based on lightning location systems – General principles
Densité de foudroiement basée sur des systèmes de localisation
de la foudre (LLS) – Principes généraux
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IEC 62858 ®
Edition 2.0 2019-10
INTERNATIONAL
STANDARD
NORME
INTERNATIONALE
colour
inside
Lightning density based on lightning location systems – General principles
Densité de foudroiement basée sur des systèmes de localisation
de la foudre (LLS) – Principes généraux
INTERNATIONAL
ELECTROTECHNICAL
COMMISSION
COMMISSION
ELECTROTECHNIQUE
INTERNATIONALE
ICS 29.020; 91.120.40 ISBN 978-2-8322-7457-6
– 2 – IEC 62858:2019 © IEC 2019
CONTENTS
FOREWORD . 3
INTRODUCTION . 5
1 Scope . 6
2 Normative references . 6
3 Terms, definitions, abbreviated terms and symbols . 6
3.1 Terms and definitions . 6
3.2 Abbreviated terms and symbols . 7
4 General requirements . 7
4.1 General . 7
4.2 Stroke-to-flash grouping . 8
4.3 Minimum observation periods . 9
4.4 Observation area . 9
4.5 Grid cell size . 9
4.6 Edge effect correction . 9
5 Validation of lightning location system performance characteristics . 10
Annex A (informative) Determination of lightning density for risk calculation . 12
Annex B (informative) Ground strike points (GSPs) explanations and calculation
methods . 13
Bibliography . 14
Figure A.1 – High resolution full climatology (HRFC) N data. 12
t
INTERNATIONAL ELECTROTECHNICAL COMMISSION
____________
LIGHTNING DENSITY BASED ON LIGHTNING LOCATION SYSTEMS –
GENERAL PRINCIPLES
FOREWORD
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International Standard IEC 62858 has been prepared by IEC technical committee 81:
Lightning protection.
This second edition cancels and replaces the first edition published in 2015. This edition
constitutes a technical revision.
This edition includes the following significant technical changes with respect to the previous
edition:
Two informative annexes are introduced dealing with the determination of lightning density for
risk calculation (Annex A) and ground strike point calculation methods (Annex B).
– 4 – IEC 62858:2019 © IEC 2019
The text of this International Standard is based on the following documents:
FDIS Report on voting
81/627A/FDIS 81/634/RVD
Full information on the voting for the approval of this International Standard can be found in
the report on voting indicated in the above table.
This document has been drafted in accordance with the ISO/IEC Directives, Part 2.
The committee has decided that the contents of this document will remain unchanged until the
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the specific document. At this date, the document will be
• reconfirmed,
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• replaced by a revised edition, or
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IMPORTANT – The 'colour inside' logo on the cover page of this publication indicates
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colour printer.
INTRODUCTION
International standards for lightning protection (e.g. IEC 62305-2) provide methods for the
evaluation of the lightning risk on buildings and structures.
The lightning ground flash density N , defined as the mean number of flashes per square
G
kilometre per year, and the ground strike point density N , defined as the mean number of
SG
ground strike points per square kilometre per year are the primary input parameters to
perform such an evaluation (see Annex A).
In many areas of the world data for risk evaluation are provided by lightning location systems
(LLSs), but no common rule exists defining requirements either for their performance or for
the elaboration of the measured data.
– 6 – IEC 62858:2019 © IEC 2019
LIGHTNING DENSITY BASED ON LIGHTNING LOCATION SYSTEMS –
GENERAL PRINCIPLES
1 Scope
This document introduces and discusses all necessary measures to make reliable and
homogeneous the values of ground flash density, N and ground strike point density, N ,
G SG
obtained from lightning location systems (LLSs) in various countries. Only parameters that are
relevant to risk assessment are considered.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their
content constitutes requirements of this document. For dated references, only the edition
cited applies. For undated references, the latest edition of the referenced document (including
any amendments) applies.
IEC 62305-1, Protection against lightning – Part 1: General principles
IEC 62305-2, Protection against lightning – Part 2: Risk management
3 Terms, definitions, abbreviated terms and symbols
3.1 Terms and definitions
For the purposes of this document, the terms and definitions given in IEC 62305-1 and
IEC 62305-2 and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following
addresses:
• IEC Electropedia: available at http://www.electropedia.org/
• ISO Online browsing platform: available at http://www.iso.org/obp
3.1.1
ground flash density
N
G
-2 -1
mean number of cloud-to-ground flashes per unit area per unit time (flashes x km x year )
3.1.2
ground strike-point density
N
SG
-2
mean of the number of strike-points to ground per unit area per unit time (strike-points x km
-1
x year )
3.1.3
lightning sensor
device that measures electromagnetic signals produced by lightning discharges
3.1.4
lightning location system
LLS
network of lightning sensors that work together to detect and geolocate lightning events within
the area of the system’s coverage
Note 1 to entry: This note applies to the French language only.
3.1.5
confidence ellipse
ellipse centred on the estimated ground strike-point, describing the degree of confidence of
the location estimation (e.g. 50 %, 90 %, 99 %) based on sensor measurement errors
Note 1 to entry: The confidence ellipse is described in terms of the lengths of the semi-major and semi-minor
axes as well as the bearing of the semi-major axis.
3.1.6
uptime
duration of fully functional operation of a lightning location system sensor, expressed as a
percentage of the total observation time
3.1.7
stroke detection efficiency
flash detection efficiency
percentage of strokes or flashes detected as a percentage of the total number of strokes or
flashes occurring in reality
3.1.8
median location accuracy
value of the distances between real stroke locations and the stroke locations given by the
lightning location system
3.2 Abbreviated terms and symbols
CG cloud-to-ground
DE detection efficiency
GSP ground strike point
IC intra-cloud and inter-cloud
LA location accuracy
LLS lightning location system
N ground flash density
G
N ground strike-point density
SG
4 General requirements
4.1 General
The performance characteristics of a lightning location system (LLS) determine the quality of
the lightning data available for calculating N [1] . A value of N with an error of ±20 % or
G G
less is deemed to be adequate for lightning risk assessment. Data from any LLS that is able
to detect CG lightning and accurately determine the point of strike of CG strokes can be used
for the purpose of N computation. The following LLS performance characteristics are
G
required for computation of N with adequate accuracy.
G
___________
Numbers in square brackets refer to the Bibliography.
– 8 – IEC 62858:2019 © IEC 2019
• Flash detection efficiency (DE): The value of the annual average flash detection efficiency
of an LLS for CG lightning shall be at least 80 % in the region over which N has to be
G
computed. This DE is usually obtained within the interior of the network. The interior of the
network is defined as the region within the boundary defined by the outermost adjacent
sensors of the network.
• Location accuracy (LA): The value of the median location accuracy of an LLS for CG
strokes shall be better than 500 m in the region over which N has to be computed. This
G
LA is usually obtained within the interior of the network.
• Classification accuracy: In a network with a flash DE meeting the criteria set for N
G
calculation, erroneously low or high values of N will be identified when too many CG
G
strokes are misclassified as cloud pulses (or vice versa). This is especially true for single-
.
stroke CG flashes. A classification accuracy (CG flashes not misclassified as IC) of at
least 85% is required.
These performance characteristics of an LLS can be determined using a variety of methods
including network self-referencing (using statistical analysis of parameters such as standard
deviation of sensor timing error, semi-major axis length of the 50 % confidence ellipse, and
the number of reporting sensors, which may be known from the LLS manufacturer or available
from the LLS data) and comparison against ground-truth lightning data obtained using various
techniques. These methods are discussed in Clause 5. A performance evaluation based on
the methods described in Clause 5 and all the relevant basics of the network have to be
provided on request.
The flash DE, LA, and classification accuracy of an LLS depend on a few fundamental
characteristics of the network. LLS owners, operators, and data-providers should consider the
following factors while designing and maintaining their networks to ensure that the lightning
data are of adequate quality for N computation.
G
– Sensor baseline distance: The distance between adjacent sensors in an LLS so called
sensor baseline distance is influenced by the area of desired coverage and the sensitivity
of individual sensors. Sensor baseline distance is one of the factors that determine the DE
and LA of an LLS. The maximum sensor baseline distance of an LLS shall be such that
the DE and LA of the network meet the criteria for N calculation described above.
G
– Sensor sensitivity: The sensitivity of sensors in an LLS primarily determines the ability of
the network to detect lightning events of different peak currents. The sensitivity of sensors
in an LLS shall be such that lightning events with peak currents in the range of 5 kA to
300 kA are detected and reported by the LLS. Sensor sensitivity is determined by various
factors such as trigger threshold, electronic gain, sensor bandwidth, and background
electromagnetic noise.
– Sensor uptime: The uptime of different sensors in a network determines the DE and LA of
the network. The spatial and temporal variations of DE and LA are determined by the
location of sensors that are up and contributing to the network. Hence it is important to
guarantee that LLS sensors are up and running with no interruption.
4.2 Stroke-to-flash grouping
Return strokes detected by lightning location systems shall be grouped into flashes for N
G
calculation. Multiple ground strike-points are included in the same flash. This grouping is done
based on a spatio-temporal window.
A subsequent stroke is grouped with the first return stroke to form a flash if the following
criteria are met:
a) the stroke occurs less than or equal to 1 s after the first return stroke;
b) the location of the stroke is less than or equal to 10 km from the first return stroke;
c) the time interval for successive strokes is less than or equal to 500 ms.
The flash position is assumed to be the location of the first stroke.
Strokes can also be grouped into ground strike points to obtain N based on different
SG
algorithms described in Annex B.
4.3 Minimum observation periods
A sufficiently long sampling period is required to ensure that short time scale variations in
lightning parameters due to a variety of meteorological oscillations are accounted for.
Additionally large scale climatological variations limit the validity of historic data. Some
lightning detection networks have been recording lightning data for several decades and
during this time there have been measurable changes to the climate.
A set of lightning data for at least 10 full calendar years is required, with the newest data used
not being older than five years. The data should be as continuous as possible, unless the data
does not fulfil the performance requirements in some particular years which have then to be
removed.
4.4 Observation area
The observation area is an area over which lightning data of quality as described above are
available.
Different networks and sensor technologies will have different sensitivities with which they
detect lightning. Network coverage falls off outside the boundaries of a network. In general,
lightning data within half the average sensor baseline distance (distance between adjacent
sensors in the network) from the boundary of the network should be of sufficient quality for N
G
calculation.
4.5 Grid cell size
Ground flash density (N ) values vary annually and regionally. Lightning data have to be
G
evaluated as a raster map, i.e. a gridded array of cells constrained by a geographic boundary:
the area of interest is divided into a regular grid (tessellation of the geographic area) and the
N calculation function is applied to all the flashes occurring within the grid. The resulting
G
value is then assumed to be the meaningful value within that area.
Grid size has to be chosen in such a way that the dimensions of each cell and the number of
years considered both comply with the minimum requirements obtained from Formula (1),
following Poisson distribution and the law of rare events, thus obtaining an uncertainty of less
than 20 % at 90 % confidence level [2].
NT××A ≥ 80 (1)
G obs cell
where:
-2 -1
N is the ground flash density, in km year ;
G
T is the observation period, in years;
obs
A is the area of each single cell, in km .
cell
The data used in this analysis shall conform to the requirements of both 4.2 and 4.3. The
minimum permissible cell dimension, irrespective of ground flash density and observation
period, shall not be less than double the median location accuracy.
4.6 Edge effect correction
As defined in 4.5 the size of the smallest cell that can be considered should contain at least
80 flashes. In order to avoid edge effects for this cell the N value shall be obtained by
G
integrating over a finer sub-grid of 1 km x 1 km resolution.
– 10 – IEC 62858:2019 © IEC 2019
5 Validation of lightning location system performance characteristics
The performance characteristics of an LLS determine the quality of the lightning data
available. These performance characteristics include:
– detection efficiency for IC and CG flashes and CG strokes;
– location accuracy;
– peak current estimation accuracy; and
– lightning classification accuracy.
As stated in Clause 4, for N and N the determination of DE, LA, and lightning
G SG,
classification accuracy is of primary importance. These performance characteristics can be
evaluated using a variety of techniques which are summarized below.
a) Network self-reference: In this technique, statistical analysis of parameters such as
standard deviation of sensor timing error, semi-major axis length of the 50 % confidence
ellipse, and the number of reporting sensors, is used to infer the LA and DE of an LLS.
Examples of such studies are found in [3], [4] and [5]. This method requires data collected
by the network after it has been properly calibrated. It can provide a good estimate of the
network’s performance in a cost-effective, practical manner.
b) Rocket-triggered lightning and tall object studies: This method uses data from rocket-
triggered lightning experiments or lightning strikes to tall objects (e.g. instrumented
towers) as ground-truth to evaluate the performance characteristics of an LLS within
whose coverage area the triggered lightning facility or the tall object is located. The LA,
DE, peak current estimation accuracy, and lightning classification accuracy of an LLS can
be measured using this method. Examples of studies using rocket-triggered lightning or
lightning to tall structures for LLS performance evaluation include [6], [7], and [8]. These
methods provide the best ground-truth data for performance characteristics validation for
CG lightning. In addition, these methods are the only ways to directly validate peak
current estimation accuracy of an LLS. However, they may be very expensive and may not
be practical for all regions. There are only a few triggered lightning facilities and
instrumented towers across the world. The results obtained from these methods are valid
indicators of LLS performance only for the region where the rocket-triggered lightning
facility or instrumented tower is located. Additionally, rocket-triggered lightning provides
data for return strokes similar to only subsequent strokes in natural lightning. No data for
first strokes in natural lightning can be obtained using this technique. This is also often the
case for lightning strikes to tall objects depending upon the height of the object, local
terrain, storm type, and other factors. Since first strokes in natural lightning are expected
to have, on average, peak fields and currents that are a factor of two larger than those for
subsequent strokes (e.g. [9]), CG flash and stroke DE estimated for an LLS using these
methods may be somewhat of an underestimate.
c) Video camera studies: Lightning data obtained using video cameras can be used as
ground-truth to evaluate the performance characteristics of an LLS within whose coverage
area the lightning discharges occur. The LA, DE, and lightning classification accuracy of
an LLS can generally be estimated using this method. Examples of studies using video
cameras for LLS performance evaluation include [8] and [9]. In this method, data
collection can be time consuming and challenging because the exact locations of lightning
discharges to be captured on video cannot be predicted. Additional instrumentation such
as antennas measuring the electric field from lightning discharges is often required for this
technique.
d) Inter-comparison among networks: The performance of one LLS that is being tested can
be compared against another LLS that may be used as reference, as long as the
reference LLS is extremely well calibrated and its performance has been characterized
independently. This method allows inferences to be made about the detection efficiency
and location accuracy of the test LLS relative to the reference LLS. If the reference
network provides VHF lightning mapping, inference about the test network’s IC detection
capability can be made, for example on plausibility of IC pulses or IC-CG discrimination.
Examples of such studies include [10]. One limitation of this technique is that the test and
reference networks have to overlap substantially and the results are only valid for the
overlapping region. Further, if the performance of the reference network is unknown or if
the reference network is not well calibrated, any inferences about the test network’s
performance are invalid.
While one or a combination of the above techniques can be used to evaluate the performance
characteristics of an LLS, it is important to understand the strengths and weaknesses of the
methods used, in order to obtain reliable estimates of LLS performance characteristics.
– 12 – IEC 62858:2019 © IEC 2019
Annex A
(informative)
Determination of lightning density for risk calculation
The lightning ground flash density N is the number of lightning flashes per square kilometre
G
per year. In many areas of the world this value can be derived from data provided by local
lightning location systems (LLSs) according to this document.
Historically N was determined from thunderstorm days or with the data of lightning flash
G
counters. Because nowadays more accurate methods to determine N exist, the usage of
G
thunderstorm days or data from lightning flash counters is no longer recommended.
In areas without ground-based lightning location systems, the recommended estimate of
ground flash density [11] is:
NN0,25× (A.1)
Gt
N being the total (CG + IC) density of optical recorded flashes per km per year, obtained
t
through the NASA website (https://lightning.nsstc.nasa.gov/data/data_lis-otd-
climatology.html). Figure A.1 gives an overview of total densities N all over the world.
t
SOURCE: https://ghrc.nsstc.nasa.gov/pub/lis/climatology/LIS-OTD/HRFC/browse/HRFC_COM_FR_V2.3.2015.png
reproduced with the permission from the authors.
Figure A.1 – High resolution full climatology (HRFC) N data
t
NOTE In most areas of the world, an indication of lightning activity can be obtained from observations of lightning
optical transients. Satellite-based sensors respond to all types of lightning with relatively uniform coverage. With
sufficient averaging, optical transient density data provide better estimates of ground flash density than thunder
observations, which have a wide range of relations between ground flash density and thunderstorm hours or
thunderstorm days. There are also regional variations in the ratio of ground flashes (CG) to total flashes (CG + IC).
Often flashes exhibit multiple ground strike-points. Modern LLSs may provide N directly
SG
from
according to one of the methods described in Annex B. In case of availability of N
SG
LLSs, using this data is recommended if the overall N results were independently validated.
SG
=
Annex B
(informative)
Ground strike points (GSPs) explanations and calculation methods
About half of negative cloud-to-ground lightning flashes exhibit several ground strike points.
This happens when a given dart leader partly follows the preceding return stroke channel,
ending by creating its own path to the ground. Every ground strike point represents a threat
and should be accounted for in the lightning risk calculation.
Based on high resolution lightning location data it becomes possible to identify almost all the
different attachment points in a cloud-to-ground lightning flash.
There are different algorithms available to determine ground strike points for LLS data with
advantages and disadvantages:
• Cummins [12] employed discriminant analysis to create a “vote count” based on several
parameters, including location difference and other parameters that can help identify new
ground strike points, for example rise time. This method has the potential to identify new
ground strike points when the location uncertainty is larger than the separation distance.
The “vote” approach weakens the location difference analysis when the locations are well-
known. This method is highly dependent on the quality of the rise-time parameter but
some LLS technologies may not provide the rise time and peak-to-zero time information
at all.
• Pédeboy [13], [14], [15] implemented a reliable clustering algorithm based on the k-means
method. This algorithm does not employ a complete statistical treatment of the error
geometry embodied in the error ellipses (it is just scaled by the size of the confidence
ellipse) and has no mechanism to distinguish between individual ground strike points when
the location uncertainty is larger than the separation distance of the ground strike points.
• Campos [16], [17] does a rigorous statistical job of evaluating the location uncertainty by
using the geometry of the error ellipse in the full latitude/longitude space, while embracing
the strengths of the k-means approach developed by Pédeboy. This method has the same
potential weakness as the approach from Pédeboy, in that it has no mechanism to “refine”
the classification when the location uncertainty is larger than the separation distance.
After applying one of these algorithms to LLS data, the ground strike point density can be
determined spatially according to the same rules as the ground flash density.
– 14 – IEC 62858:2019 © IEC 2019
Bibliography
[1] CIGRE Report 376, “Cloud-to-Ground Lightning Parameters Derived from Lightning
Location Systems – The Effects of System Performance,” CIGRE Report 376, 2009
[2] G. Diendorfer, “Some Comments on the Achievable Accuracy of Local Ground Flash
Density Values,” in 29th International Conference on Lightning Protection (ICLP),
2008, no. June, p. 1–6
[3] W. Schulz, “Performance Evaluation of Lightning Location Systems,” PhD Thesis,
Technical University of Vienna, 1997
[4] K. L. Cummins, M. J. Murphy, J. A. Cramer, W. D. Scheftic, N. W. S. Demetriades, and
A. Nag, “Location accuracy improvements using propagation corrections: a case study
of the U.S. National Lightning Detection Network,” in 21st International Lightning
Detection Conference and 3rd International Lightning Meteorology Conference
(ILDC/ILMC), 2010
[5] K. P. Naccarato, O. J. Pinto, and M. J. Murphy, “Performance Analysis of the
BrasilDAT network,” in International Conference on Grounding and Earthing and 3rd
International Conference on Lightning Physics and Effects (GROUND/LPE), 2008
[6] J. E. Jerauld et al., “An evaluation of the performance characteristics of the U.S.
National Lightning Detection Network in Florida using rocket-triggered lightning,” J.
Geophys. Res. Atmos., vol. 110, no. D19, p. D19106, 2005
[7] A. Nag et al., “Evaluation of U.S. National Lightning Detection Network performance
characteristics using rocket-triggered lightning data acquired in 2004–2009,” J.
Geophys. Res. Atmos., vol. 116, no. D2, p. D02123, 2011
[8] W. Schulz, G. Diendorfer, S. Pedeboy, and D. R. Poelman, “The European lightning
location system EUCLID – Part 1: Performance analysis and validation,” Nat. Hazards
Earth Syst. Sci., vol. 16, no. 2, p. 595–605, 2016
[9] W. Schulz, S. Pédeboy, C. Vergeiner, E. Defer, and W. Rison, “Validation of the
EUCLID LLS during HyMeX SOP1,” in International Lightning Detection Conference
and International Lightning Meteorology Conference (ILDC/ILMC), 2014
[10] D. R. Poelman, W. Schulz, and C. Vergeiner, “Performance Characteristics of Distinct
Lightning Detection Networks Covering Belgium,” J. Atmos. Ocean. Technol., vol. 30,
no. 5, p. 942–951, 2013
[11] W. A. Chisholm, “Estimates of Lightning Ground Flash Density using Optical Transient
Density,” in IEEE PES Transmission and Distribution Conference and Exposition (IEEE
Cat. No.03CH37495), 2003, vol. 3, p. 1068–1071
[12] K. L. Cummins, “Analysis of Multiple Ground Contacts in Cloud-to-ground Flashes
Using LLS Data: The Impact of Complex Terrain,” in International Lightning Detection
Conference and International Lightning Meteorology Conference (ILDC/ILMC), 2012
[13] S. Pédeboy, “Identification of the multiple ground contacts flashes with lightning
location systems,” in 22nd International Lightning Detection Conference and 4th
International Lightning Meteorology Conference (ILDC/ILMC), 2012
[14] S. Pédeboy and W. Schulz, “Validation of a ground strike point identification algorithm
based on ground truth data,” in International Lightning Detection Conference and
International Lightning Meteorology Conference (ILDC/ILMC), 2014
[15] W. Schulz, S. Pedeboy, and M. M. F. Saba, “LLS Detection Efficiency of Ground Strike
Points,” in Lightning Protection (ICLP), 2014 International Conference on, 2014, no. 2,
p. 381–384
[16] L. Z. S. Campos, K. L. Cummins, and O. J. Pinto, “An algorithm for identifying ground
strike points from return stroke data provided by Lightning Location Systems,” in Asia-
Pacific Conference on Lightning (APL), 2015, p. 475–478
[17] L. Z. S. Campos, “On the mechanisms that lead to multiple ground contacts in
lightning,” PhD Thesis, INPE, Brazil, 2016
___________
– 2 – IEC 62858:2019 © IEC 2019
SOMMAIRE
AVANT-PROPOS . 3
INTRODUCTION . 5
1 Domaine d'application . 6
2 Références normatives . 6
3 Termes, définitions, termes abrégés et symboles . 6
3.1 Termes et définitions . 6
3.2 Termes abrégés et symboles . 7
4 Exigences générales . 8
4.1 Généralités . 8
4.2 Regroupement des arcs-en-retour en flashs CG . 9
4.3 Périodes d'observation minimales . 9
4.4 Zone d'observation . 9
4.5 Dimensions des cellules de la grille . 10
4.6 Correction de l'effet de bord . 10
5 Validation des caractéristiques de performance d'un système de localisation des
éclairs (LLS) . 10
Annexe A (informative) Détermination de la densité de foudroiement pour le calcul du
risque . 13
Annexe B (informative) Explications et méthodes de calcul concernant les points
d'impact au sol (GSP) . 14
Bibliographie . 15
Figure A.1 – Données N climatologiques haute résolution (HRFC) . 13
t
COMMISSION ÉLECTROTECHNIQUE INTERNATIONALE
____________
DENSITÉ DE FOUDROIEMENT BASÉE SUR DES SYSTÈMES DE
LOCALISATION DES ECLAIRS – PRINCIPES GÉNÉRAUX
AVANT-PROPOS
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기사 제목: IEC 62858:2019 - 번개 위치 시스템을 기반으로 한 번개 밀도 - 일반 원칙 기사 내용: IEC 62858:2019는 이전 판과 기술적 내용의 변경 사항을 보여주는 국제 표준과 그의 Redline 버전을 포함한 IEC 62858:2019 RLV로 제공됩니다. IEC 62858:2019는 다양한 국가에서 번개 위치 시스템 (LLSs)으로부터 얻은 지면 번개 밀도, NG와 지면 충격점 밀도, NSG의 신뢰성과 일관성을 확보하기 위한 필수 조치들에 대해 도입하고 논의합니다. 위험 평가와 관련된 관련 매개변수만 고려됩니다. 이 제2판은 2015년에 출판된 제1판을 취소하고 대체합니다. 이 번째 판은 기술 개정을 구성합니다. 이 번째 판에는 이전 판에 비해 다음과 같은 중요한 기술적 변경 사항이 포함되어 있습니다: - 위험 계산을 위한 번개 밀도 결정에 관련된 정보성 부록 두 개가 도입되었습니다(부록 A). - 지면 충격점 계산 방법에 관한 정보성 부록 또한 도입되었습니다(부록 B).
IEC 62858:2019 is a standard that focuses on lightning density based on lightning location systems (LLSs). It aims to establish consistent and reliable values of ground flash density and ground strike point density obtained from LLSs in different countries. This second edition of the standard replaces the previous edition from 2015 and includes two informative annexes, one discussing the determination of lightning density for risk calculation and the other addressing ground strike point calculation methods. The standard is available as IEC 62858:2019 RLV, which includes the International Standard and its Redline version, highlighting all changes compared to the previous edition.
記事のタイトル：IEC 62858:2019 - 雷位置システムに基づく雷密度-一般原則 記事の内容：IEC 62858:2019は、以前の版との技術的内容の変更点を示す国際規格とそのRedline版を含むIEC 62858:2019 RLVとして利用できます。 IEC 62858:2019では、異なる国々の雷位置システム（LLSs）から得られる地上フラッシュ密度および地上ストライクポイント密度の信頼性と均一性を確保するために必要な措置を導入し、議論しています。リスク評価に関連するパラメータのみを考慮しています。この第2版は、2015年に発行された第1版を取り消し、置き換えます。この版は技術的な改訂となっており、以下の重要な技術的変更点が先行版に比べて含まれています： - リスク計算のための雷密度の決定に関する情報の付録2つが導入されました（付録A）。 - 地上ストライクポイントの計算方法に関する情報の付録も導入されました（付録B）。
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