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Concurrent satellite and ground-based lightning observations from the Optical Lightning Imaging Sensor (ISS-LIS), the low-frequency network Meteorage and the SAETTA Lightning Mapping Array (LMA) in the northwestern Mediterranean region

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The new space-based Lightning Imager (LI) onboard the Meteosat Third Generation (MTG) geostationary satellite will improve the observation of lightning over Europe, the Mediterranean Sea, Africa and the Atlantic Ocean from 2021 onwards. In preparation for the use of the upcoming MTG-LI data, we compare observations by the Lightning Imaging Sensor (LIS) on the International Space Station (ISS), which applies an optical technique similar to MTG-LI, to concurrent records of the low-frequency (LF) ground-based network Meteorage. Data were analyzed over the northwestern Mediterranean Sea from 1 March 2017 to 20 March 2018. Flashes are detected by ISS-LIS using illuminated pixels, also called events, within a given (2.0 ms) frame and during successive frames. Meteorage describes flashes as a suite of intra-cloud and cloud-to-cloud (IC) pulses and/or cloud-to-ground (CG) strokes. Both events as well as pulses and strokes are grouped to flashes using a novel in-house algorithm. In our study, ISS-LIS detects about 57 % of the flashes detected by Meteorage. The flash detection efficiency (DE) of Meteorage relative to ISS-LIS exceeds 80 %. Coincident matched flashes detected by the two instruments show a good spatial and temporal agreement. Both peak and mean distances between matches are smaller than the ISS-LIS pixel resolution (about 5.0 km). The timing offset for matched ISS-LIS and Meteorage flashes is usually shorter than the ISS-LIS integration time frame (2.0 ms). The closest events and the pulses and strokes of matched flashes achieve sub-millisecond offsets. Further analysis of flash characteristics reveals that longer-lasting and more spatially extended flashes are more likely detected by both ISS-LIS and Meteorage than shorter-duration and smaller-extent flashes. The ISS-LIS relative DE is lower for daytime versus nighttime as well as for CG versus IC flashes. A second ground-based network, the very high-frequency (VHF) SAETTA Lightning Mapping Array (LMA), further enhances and validates the lightning pairing between ISS-LIS and Meteorage. It also provides altitude information on the lightning discharges and adds a detailed lightning mapping to the comparison for verification and better understanding of the processes. Both ISS-LIS and Meteorage flash detections feature a high degree of correlation with the SAETTA observations (without altitude information). In addition, Meteorage flashes with ISS-LIS match tend to be associated with discharges that occur at significantly higher altitudes than unmatched flashes. Hence, ISS-LIS flash detection suffers from degradation, with low-level flashes resulting in lower DE.
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Atmos. Meas. Tech., 13, 853–875, 2020
https://doi.org/10.5194/amt-13-853-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Concurrent satellite and ground-based lightning observations from
the Optical Lightning Imaging Sensor (ISS-LIS), the low-frequency
network Meteorage and the SAETTA Lightning Mapping Array
(LMA) in the northwestern Mediterranean region
Felix Erdmann1,2, Eric Defer1, Olivier Caumont2, Richard J. Blakeslee3, Stéphane Pédeboy4, and Sylvain Coquillat1
1Laboratoire d’Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
2CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
3NASA George C. Marshall Space Flight Center/NSSTC, Huntsville, AL, USA
4Météorage, Pau, 2 avenue du Président Pierre Angot – CS 8011 64053 Pau CEDEX 9, France
Correspondence: Felix Erdmann (erdmann.professional@gmx.de)
Received: 12 April 2019 – Discussion started: 4 July 2019
Revised: 25 November 2019 – Accepted: 5 December 2019 – Published: 20 February 2020
Abstract. The new space-based Lightning Imager (LI) on-
board the Meteosat Third Generation (MTG) geostationary
satellite will improve the observation of lightning over Eu-
rope, the Mediterranean Sea, Africa and the Atlantic Ocean
from 2021 onwards. In preparation for the use of the upcom-
ing MTG-LI data, we compare observations by the Light-
ning Imaging Sensor (LIS) on the International Space Sta-
tion (ISS), which applies an optical technique similar to
MTG-LI, to concurrent records of the low-frequency (LF)
ground-based network Meteorage. Data were analyzed over
the northwestern Mediterranean Sea from 1 March 2017 to
20 March 2018. Flashes are detected by ISS-LIS using illu-
minated pixels, also called events, within a given (2.0 ms)
frame and during successive frames. Meteorage describes
flashes as a suite of intra-cloud and cloud-to-cloud (IC)
pulses and/or cloud-to-ground (CG) strokes. Both events as
well as pulses and strokes are grouped to flashes using a
novel in-house algorithm.
In our study, ISS-LIS detects about 57% of the flashes
detected by Meteorage. The flash detection efficiency (DE)
of Meteorage relative to ISS-LIS exceeds 80%. Coincident
matched flashes detected by the two instruments show a good
spatial and temporal agreement. Both peak and mean dis-
tances between matches are smaller than the ISS-LIS pixel
resolution (about 5.0 km). The timing offset for matched
ISS-LIS and Meteorage flashes is usually shorter than the
ISS-LIS integration time frame (2.0 ms). The closest events
and the pulses and strokes of matched flashes achieve sub-
millisecond offsets. Further analysis of flash characteris-
tics reveals that longer-lasting and more spatially extended
flashes are more likely detected by both ISS-LIS and Mete-
orage than shorter-duration and smaller-extent flashes. The
ISS-LIS relative DE is lower for daytime versus nighttime as
well as for CG versus IC flashes.
A second ground-based network, the very high-frequency
(VHF) SAETTA Lightning Mapping Array (LMA), further
enhances and validates the lightning pairing between ISS-
LIS and Meteorage. It also provides altitude information
on the lightning discharges and adds a detailed lightning
mapping to the comparison for verification and better un-
derstanding of the processes. Both ISS-LIS and Meteorage
flash detections feature a high degree of correlation with the
SAETTA observations (without altitude information). In ad-
dition, Meteorage flashes with ISS-LIS match tend to be as-
sociated with discharges that occur at significantly higher al-
titudes than unmatched flashes. Hence, ISS-LIS flash detec-
tion suffers from degradation, with low-level flashes result-
ing in lower DE.
Published by Copernicus Publications on behalf of the European Geosciences Union.
854 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
1 Introduction
Lightning defines electrical discharges within the atmo-
sphere. The discharges can happen within a cloud, between
clouds (IC), or between a cloud and the ground (CG). The to-
tal lightning activity (IC+CG) is of interest for, e.g., numer-
ical weather prediction (NWP) as lightning serves as tracer
for deep convection. The total lightning flash rate is asso-
ciated with storm intensity features. For example, Deierling
and Petersen (2008) found a strong correlation between the
updraft volume above the 5C level in clouds and total
lightning activity. Deierling et al. (2008) show a fairly sta-
ble relationship and strong correlation between the precipi-
tation ice mass flux, the non-precipitation ice mass flux and
their product on the one hand and the total lightning flash rate
on the other. Graupel and small hail ice mass correlate espe-
cially well with the mean total lightning rate in their study.
Among others, Mattos et al. (2017) investigated the life cy-
cle of thunderstorms and processes leading to the different
discharge types. They found in their analysis of 46 isolated
thunderstorms that in 98 % of their cases, the first CG flash is
preceded by IC lightning by approximately 6 min on average.
At this time, lightning observations in Europe are mainly
made with ground-based sensors. To maximize the impact of
lightning data on assimilation in NWP systems, total light-
ning should be observed continuously over large areas. In a
few years, the new Lightning Imager (LI) onboard the Me-
teosat Third Generation (MTG) satellite (Stuhlmann et al.,
2005) will provide continuous lightning observation over Eu-
rope, the Mediterranean Sea, Africa, the Atlantic Ocean and
parts of Brazil. The satellite sensor will be able to detect to-
tal lightning including CG and IC flashes when launched in
the 2021 time frame. The Lightning Imaging Sensor (LIS) on
the International Space Station (ISS) (Blakeslee and Koshak,
2016) creates a unique opportunity to provide proxy data to
help prepare research and operational applications for the
MTG-LI data. It overpasses, among others, wide parts of Eu-
rope, including the entire Mediterranean region. ISS-LIS is
in principle similar to the planned MTG-LI so that ISS-LIS
data can to some extent mimic the upcoming MTG-LI data.
In addition, a comparison between European ground-based
lightning observation networks and ISS-LIS should improve
the understanding of ground- and space-based lightning ob-
servations. All instruments and networks are hereafter simply
referred to as lightning locating systems (LLSs).
These comparisons focus on the spatial and temporal coin-
cidence of flashes reported by the various systems, resulting
in measures of detection efficiency (DE) as a function of the
flash parameters. This study uses the term relative DE. It is
defined as the ratio of the number of matched flashes to the
number of flashes in the other (reference) LLS, expressed as
a percentage.
An LIS was previously operational on the Tropical Rain-
fall Measurement Mission (TRMM) satellite (e.g., Christian
et al., 1999; Cecil et al., 2005). Several LLSs comparisons
exist for regions covered by TRMM-LIS. The focus of the
following (not exhaustive) literature review is on observa-
tional analyses rather than laboratory experiments; e.g., Boc-
cippio et al. (2002). Ground-based LLSs observe different
frequency ranges of the lightning radio signal. They are clas-
sified as, e.g., very low-frequency (VLF) and low-frequency
(LF) LLSs as well as very high-frequency (VHF) LLSs (e.g.,
Fig. 2; Cummins and Murphy, 2009). A summary of de-
tection characteristics, (dis)advantages and the range of the
various ground-based LLSs is provided in Nag et al. (2015).
VLF–LF systems detect lightning at middle to long ranges.
Their DE is somewhat limited. It varies for different net-
works and flash types (CG flash DE is usually higher than
IC flash DE for VLF–LF LLSs) but increases in general with
lower baseline distance.
Thompson et al. (2014) aimed to explore suitable proxy
data for the Geostationary Lightning Mapper (GLM) (Good-
man et al., 2013). They report a pulse and stroke DE max-
imum for two long-range LLSs, the World Wide Lightning
Location Network (WWLLN) and the Earth Networks To-
tal Lightning Location Network (ENTLN), of 18.9 % and
63.3 %, respectively, relative to 18-month records of TRMM-
LIS groups (a combination of adjacent illuminated pixels in
the optical image that occur in the same 2 ms time frame).
The maxima were found over the Pacific Ocean for WWLLN
and near North America for ENTLN (within the analyzed re-
gion with the highest sensor density) in 2010 and 2011. They
did not study how many WWLLN and ENTLN pulses and/or
strokes had coincident TRMM-LIS groups.
Rudlosky et al. (2017) analyzed the performance of the
Global Lightning Dataset 360 (GLD360) relative to TRMM-
LIS from 2012 to 2014 in different regions. GLD360 was
able to detect 63.6 % of the TRMM-LIS flashes in North
America in 2014, the maximum DE reported in their study.
The performance steadily increased from 2012 to 2014. The
relative DE of GLD360 increased with the TRMM-LIS flash
duration, flash extent and group number. The mean (median)
location offset of the nearest GLD360 stroke to the matched
TRMM-LIS flashes was 8.7 km (7.0 km). Rudlosky et al.
(2017) applied the assumption that TRMM-LIS would de-
tect all flashes within its field of view but did not study the
reverse problem, i.e., the relative DE of TRMM-LIS to the
GLD360 flashes or strokes.
Defer et al. (2005) used both the UK Met Office
long-range VLF arrival time difference (ATD) system and
TRMM-LIS to study the lightning activity in the eastern
Mediterranean Sea for 20 d during winter 2008–2009. For
their investigation of the flash scale, they developed and em-
ployed their own algorithm for TRMM-LIS flashes. The flash
density analysis exhibits a general agreement between ATD
and TRMM-LIS. The relatively small dataset, and the fact
that ATD detected mostly CG lightning, limited the ability to
gain overall statistics.
Bitzer et al. (2016) tested a Bayesian approach on the DE
of TRMM-LIS and ENTLN by implementing the conditional
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 855
DEs of the two LLSs relative to each other. They found a
relative conditional group-to-pulse DE of 52 % (27 %) for
TRMM-LIS to ENTLN (ENTLN to TRMM-LIS near North
America in 2013). They also addressed peak timing differ-
ences and distances for the collocated discharges (again LIS
groups, ENTLN pulses; see Sect. 3.2 for details). Bitzer et al.
further tested the effect of assimilating one dataset into the
other on the detected number of discharges; i.e., 23.6 % of
discharges could be added to the total number of observed
flashes after combining the datasets.
While the previous papers focused on the DE, Höller and
Betz (2010) analyzed TRMM-LIS and a VLF–LF lightning
location network (LINET) in order to generate random proxy
optical data from a given set of LINET data using model dis-
tribution functions. The outcomes are of specific interest for
proxy data for the MTG-LI. Besides the relative DEs (ap-
proximately 50 % for both LLSs), they investigated the dis-
tribution functions and correlations between the TRMM-LIS
group and the LINET pulse and stroke number per flash, flash
extent, and duration as well as between LINET pulse and
stroke amplitude and TRMM-LIS group radiance. Although
the Pearson correlation coefficients remained low, the ap-
proach can be further refined for high-fidelity MTG-LI proxy
data.
VHF LLSs are sensitive to lightning channel formation
and leader processes, which occur multiple times during a
single flash. Hence, VHF LLSs typically feature high DE
performances and three-dimensional (3-D) mapping of light-
ning channel propagation and spatial extent (Thomas et al.,
2004). VHF LLSs depend on direct line-of-sight detection,
and thus the range suffers from the Earth’s curvature and ter-
rain shading effects.
Thomas et al. (2000) presented a case study of a storm in
Oklahoma, USA, at local nighttime. The storm was observed
by both the local VHF lightning mapping array (LMA) and
TRMM-LIS; 108 of the 128 LMA lightning discharges were
detected by TRMM-LIS, and the LMA detected all TRMM-
LIS flashes. The lightning missed by TRMM-LIS was mainly
confined to low-altitude discharges, i.e., below 7.0km. Opti-
cal signals of lightning discharges that propagated via scat-
tering to the upper part of the cloud were easily detected by
TRMM-LIS.
Blakeslee et al. (2013) studied the São Paulo LMA (SP
LMA) dataset and its capability to serve as GLM proxy data.
TRMM-LIS events were in good agreement with the concur-
rent SP LMA, ENTLN and LINET observations regarding
latitude, longitude and timing. The records showed as ex-
pected more VHF (SP LMA) sources than VLF pulses and
strokes (ENTLN and LINET) per flash.
Due to the TRMM satellite orbit, the comparisons of
TRMM-LIS and ground-based LLSs records are restricted
to tropical and subtropical regions between about 38N and
38S. As a result of its higher-inclination orbit, ISS-LIS now
allows for the observation of extratropical thunderstorms to
extend to 55N and 55S. The higher-latitude storms might
show different behaviors to their tropical and subtropical
counterparts due to modified cloud vertical extent and forc-
ing like the general wind field, average temperature and tem-
perature gradients. Our study concentrates on the characteris-
tics of lightning flashes over the northwestern (NW) Mediter-
ranean Sea and should contribute to a better understanding
of both European storms and European LLSs. This allows
for the first time an intercomparison of LIS and European
LLSs. Three LLSs operating in different spectral regions
(near-IR, VLF–LF, VHF) are compared: the satellite-based
ISS-LIS operational since March 2017, the French Meteor-
age VLF–LF LLS and the VHF SAETTA LMA on Corsica.
The relative DE of ISS-LIS to Meteorage (and reverse) is
analyzed, while SAETTA is used to verify and understand
the results. Indeed, the spatially and temporally high reso-
lution of SAETTA’s measurements capture the structure and
the life cycle of each lightning flash and gather additional in-
formation, i.e., discharge altitude, to more thoroughly assess
ISS-LIS and Meteorage strengths and weaknesses. Besides
the commonly investigated relative DEs, distances and tim-
ing offsets, this work also examines specific characteristics
of matched ISS-LIS and Meteorage flashes. It aims to pro-
vide the basis for mimicking optical satellite-based lightning
data from a VLF–LF LLS.
In Sect. 2, ISS-LIS, Meteorage and SAETTA are in-
troduced as are the data processing, developed algorithms
and the investigation methodology. Results are presented
in Sect. 3. A brief summary and a discussion are given in
Sect. 4.
2 Instrumentation and methodology
This paper aims to identify the individual lightning detec-
tion characteristics by the satellite-based ISS-LIS, the VLF–
LF Meteorage and the VHF SAETTA LLSs. ISS-LIS, in-
stalled on the International Space Station in 2017, has been
acquiring data since 1 March 2017. Our intercomparison
of the LLSs covers the period from 1 March 2017 until
20 March 2018. The region was limited to 40.5 to 44.0N
and 7.0 to 11.0E around the island of Corsica in the NW
Mediterranean Sea. Figure 1 shows the domain with accu-
mulated data of one overpass (a), an infrared (IR) satellite
picture (b), and the example of one flash recorded by ISS-
LIS, Meteorage and SAETTA (c). The three instruments are
introduced within this section. In total, the ISS-LIS field of
view (FOV) intersected the region of interest 851 times dur-
ing the study period, with 26 of the overpasses exhibiting
lightning activity. In this work, all times are given in Coor-
dinated Universal Time (UTC). Altitudes are defined above
sea level (a.s.l.). Distances are calculated using Vincenty’s
formulae (Vincenty, 1975) based on the WGS 84 reference
ellipsoid, which is more accurate on Earth than, for exam-
ple, great circle distances (assumes the Earth as an oblate
sphere rather than a sphere). The term detection efficiency
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856 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
(DE) means in the following the DE for flashes, not the event
or pulse–stroke DE.
2.1 ISS-LIS
The ISS operates in low Earth orbit (LEO) and overpasses
one region on the surface up to three times a day (up to two
times in the tropics). Lightning observation of a specific point
lasts up to 90 s per overpass due to the ISS orbit characteris-
tics and the LIS FOV of approximately 655 ×655 km2. The
optical lightning detection is performed at a wavelength of
777.4 nm at the atomic oxygen line. ISS-LIS observes both
IC and CG discharges but cannot distinguish the lightning
type. ISS-LIS captures an image of the Earth every 2 ms,
referred to as a frame. The LIS focal plane consists of a
128 ×128 pixel charge-coupled device (CCD) that is read
out every 2 ms. The pixel FOV ranges between 4.5km (nadir)
and 6.2 km at the edges (Dennis Buechler, personal commu-
nication 2019). Blakeslee and Koshak (2016) apply a four-
step filtering approach, involving a spatial, spectral, tempo-
ral and background subtraction filter, to identify pixels with
lightning activity. This is required to detect the lightning dur-
ing daytime when the sunlight reflected off the cloud tops
otherwise overwhelms and masks the lightning signal (i.e., it
is daytime lightning detection that drives the design of space-
based lightning detectors such as LIS and the new MTG-
LI). An illuminated pixel that breaks a predefined threshold
in a given 2 ms frame is identified as an event. Events de-
fine the smallest units of the optical signals in the ISS-LIS
dataset. Their latitude and longitude correspond to the pixel
center. A group is the next unit of ISS-LIS data. An ISS-
LIS group contains one or more events occurring within the
same time frame and in adjacent pixels of the ISS-LIS im-
age (Christian et al., 2000). Next, groups are organized into
flashes so that a flash can consist of one or multiple groups.
A weighted Euclidean distance (WED) employs spatial and
temporal clustering with 330 ms and 5.5 km, respectively, to
merge groups in flashes (Mach et al., 2007). The locations
of groups and flashes are defined by the radiance-weighted
average positions of their events and groups, respectively.
Finally, an area contains all flashes with distances of less
than 16.5 km to each other. The National Aeronautics and
Space Administration (NASA) provides the ISS-LIS at dif-
ferent post-processing levels. In the latest available version,
P0.2, the quality control is already close to its (expected) fi-
nal stage, but the data may contain some undetected minor
errors (Blakeslee et al., 2017). The main difference will con-
cern the detection efficiency. The fully validated flash den-
sity should not differ more than 5.0 % to 10.0% from version
P0.2 (Richard J. Blakeslee, personal communication, 2018).
LIS data comprise 2 ms scientific data, e.g., the time, latitude,
longitude and optical amplitude count of events and instru-
ment, platform or external errors to verify the data quality,
and housekeeping data. The available ISS-LIS P0.2 version
data do not yet include the (background-)calibrated radiance.
The strength of the optical signal is defined by the raw am-
plitude count. It depends somewhat on the background value,
but in general the radiance increases with the raw count
(Dennis E. Buechler, NASA MSFC, personal communica-
tion, 2019). The housekeeping data, received every second,
contain among others LIS viewtime with information about
the FOV at a certain time. It is provided on a 0.5×0.5grid.
ISS-LIS viewtime is fundamental for the intercomparison to
continuous observations at the ground.
The original ISS-LIS data contain times in International
Atomic Time with reference to the 1 January 1993 format
(TAI93). For intercomparison of the LLSs, times are con-
verted to UTC while taking the missing leap seconds into ac-
count. The ISS-LIS times include a time-of-flight (TOF) cor-
rection accounting for the time photons need to travel from
the optical source at cloud top to the satellite.
2.2 Meteorage
The Meteorage LF LLS uses Vaisala LS7002 sensors
(Vaisala, 2013) at a frequency between 1 and 350 kHz. It in-
cludes 21 ground sensors across France and contributes to the
European Cooperation for Lightning Detection (EUCLID).
EUCLID comprises lightning sensors all over Europe and
helps to improve the performance of national LLSs (Schulz
et al., 2016). The LS7002 sensors measure the signals re-
lated to CG strokes as well as IC pulses and thus the total
lightning. Vaisala has a CG DE of 95 % and a DE for IC
of 50 %. Pédeboy et al. (2018a) stated that indeed 97 % of
the CG flashes and 56 % of the IC flashes were detected by
Meteorage (68.3 % overall DE relative to LMA flashes). The
theoretical median location accuracy is approximately 250 m
and improves inside the network to about 150 m. Pédeboy
et al. (2018a) found a reduced median location accuracy for
IC flashes of 1.64 km. Time synchronization applies a GPS
receiver with an accuracy of 50ns to UTC. The lightning lo-
cation needs at least two sensors (each provides a time and
an angle of arrival) by applying combined magnetic direction
finding and time-of-arrival techniques. Lightning can be de-
tected at a distance up to 1500 km from a sensor. In practice,
the use of ionospheric reflection is avoided, hence limiting
the sensor range to about 625 km. It ensures that the ground
plane wave front of the signal is measured rather than a re-
flected wave of the lightning-related signal. Our study makes
use of Meteorage lightning pulse and stroke data. For each
pulse and stroke, the occurrence time, latitude, longitude, the
amplitude with polarity and the type (IC/CG) are provided.
Meteorage observes lightning continuously within its range.
In the intercomparison with ISS-LIS, data are disregarded if
observation space or time do not fit the corresponding ISS-
LIS viewtimes.
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 857
Figure 1. Observations of ISS-LIS events (as pixel centers), Meteorage pulses and strokes, and SAETTA VHF sources (as indicated) during
one ISS overpass over Corsica on 10 September 2017 (a). The ISS-LIS viewtime is presented as grayscale in the background. Numbers in
parentheses give the number of SAETTA VHF sources, ISS-LIS events, and Meteorage pulses and strokes, respectively. Panel (b) shows the
infrared (IR 10.8 µm) satellite image of the same day at 01:15:00UTC (data visualization provided by the AERIS/ICARE Data and Services
Center). One flash over Corsica detected by the three LLSs during the same ISS overpass is shown in (c) as a map and (d) as time series of
latitude, longitude, signal strength amplitude (dBW for SAETTA, kA for Meteorage and amplitude count for ISS-LIS) and altitude (LIS and
Meteorage set to 15 km).
2.3 SAETTA (Suivi de l’Activité Electrique
Tridimensionnelle Totale de l’Atmosphère)
The LMA technology was developed by New Mexico Tech
(Rison et al., 1999). The SAETTA LMA operates in the
60–66 MHz VHF band, with an 80 µs analysis window (Co-
quillat et al., 2014), and consists of 12 LMA stations dis-
tributed over the island of Corsica. The distance between the
network’s northernmost and southernmost (westernmost and
easternmost) stations is approximately 180 km (70 km). The
station altitude ranges from 3.8 to 1950.2 m a.s.l. SAETTA
maps the total lightning activity. A minimum of six stations
is needed to capture a lightning source in 3-D. Redundant
information from more stations improves the location accu-
racy and consequently decreases the chance of mislocation
and possible noise (e.g., single VHF sources in Fig. 1c). As
a drawback, fewer VHF sources and flashes are detected si-
multaneously by more than six stations. Aiming at a high
flash DE, coincident signals at six stations are sufficient for
the LMA data in this study.
SAETTA data include the time, latitude, longitude, alti-
tude and amplitude of each lightning source. Lightning loca-
tion reaches up to a radius of 350 km from the center of the
network. The VHF LLS depends on the direct line of sight
to a lightning discharge. The altitude of the lowest detectable
VHF source increases with the distance to the LMA due to
Earth curvature. For example, sources at 100km (200 km)
of distance to a station at sea level must be at least 0.8 km
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858 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
(3.1 km) in altitude to be visible to that station. Equation (6)
of Koshak et al. (2018) is applied here. Their study also in-
vestigates the effects of the LMA network geometry, mainly
on the altitude errors. For SAETTA, Coquillat et al. (2019a)
show that the displacement of two stations in 2016 markedly
reduced the radial error and increased the altitude error over
wide parts of the studied domain (Fig. 3 in Coquillat et al.,
2019a). Therefore, when different sets of at least six stations
are involved in the reconstruction of the VHF source position
one would expect a different geometry of the network, which
influences the location precision. In general the SAETTA lo-
cation uncertainty increases with the distance to the network
center. According to the theoretical model of Thomas et al.
(2004), the radial, azimuthal and altitude errors are, at best
for VHF sources at 10 km of altitude, 15, 8 and 40m, respec-
tively, within 50 km from the center of the network (Coquillat
et al., 2019a). These theoretical errors reach about 300, 20
and 400 m, respectively, at the borders of the present study
domain (Fig. 1a). SAETTA location errors are of the same
order of magnitude as those of Meteorage CG location, while
the LMA should capture lightning in more detail than the LF
LLS.
SAETTA data are employed for locations and times of co-
incident ISS-LIS or Meteorage observations. Therefore, they
are analyzed in space and time regarding the detected ISS-
LIS and Meteorage lightning activity. A combined space–
time filter identifies SAETTA sources within 0.2(both lat-
itude and longitude) and (simultaneously) 0.3 s of corre-
sponding ISS-LIS events and Meteorage pulses and strokes.
The filtering per (ISS-LIS or Meteorage) flash allows for ana-
lyzing the concurrent VHF measurements with, e.g., altitude
information. Furthermore, SAETTA data are not used to ex-
clude any ISS-LIS or Meteorage observations, and neither
ISS-LIS nor Meteorage data are confined to any SAETTA
data condition. They are, however, used to verify the applied
data processing approaches, i.e., grouping elements (events,
pulses and strokes) to flashes and the analysis of possible
false alarms within the lightning detection of ISS-LIS and
Meteorage. The maximum altitude of SAETTA sources is
bounded at 15.0 km a.s.l., and the maximum reduced χ2,
which defines a measure for the overall uncertainty of the
time-of-arrival-based system (Thomas et al., 2004), is set to
0.5.
This study uses SAETTA source altitudes to define flash
mean, minimum and maximum altitudes. The flash mean al-
titude is the true mean of all altitudes of sources coincident
with the (ISS-LIS or Meteorage) flash. The minimum altitude
is defined as the 10th percentile of the altitudes of concurrent
SAETTA sources rather than the true minimum. It is aimed at
reducing the influence of noise in the data. In the same man-
ner the flash maximum altitude equals the 90th percentile of
the concurrent SAETTA source altitudes instead of the true
distribution maximum.
2.4 Flash-grouping algorithm
The NASA LIS flash-clustering algorithm distinguishes
events, groups and flashes (Sect. 2.1). It makes use of a WED
with a maximum difference of 5.5 km in space and 330 ms in
time. The WED analyzes group centroids and not the events
in the group to determine if two groups are considered part
of the same flash. One flash cannot last longer than 2.0 s
(Christian et al., 2000). An analysis of the (P0.2) NASA LIS
flash-clustering algorithm revealed that it tends to separate
flashes when compared to concurrent SAETTA observations.
Similar results were observed by Defer et al. (2005). Conse-
quently, a new algorithm is developed to merge the ISS-LIS
events to flashes. It has the additional advantage of treating
both ISS-LIS events and Meteorage pulses and strokes. The
lightning elements sensed by each LLS, which are the small-
est available lightning signals (events as well as pulses and
strokes), are merged into flashes. More explicitly, an event
of ISS-LIS (pulse and/or stroke of Meteorage) should belong
to exactly one flash, and a flash is defined as a collection of
events (pulses and strokes). Flash characteristics are derived
from the underlying element characteristics; e.g., the posi-
tions of its elements are used instead of the mean flash loca-
tion. This study makes use of the elementary ISS-LIS event
data as provided by NASA prior to any data merging. It is ac-
cepted that ISS-LIS events do not have a direct representation
in the Meteorage-like data. Former studies have claimed that
LIS groups roughly correspond to the physical processes de-
tected by VLF–LF LLSs (e.g., Bitzer et al., 2016; Höller and
Betz, 2010). Nevertheless, those studies found significantly
more groups than pulses and strokes within the same region
and time period. Bitzer et al. (2016) found for the number
of TRMM-LIS groups to ENTLN pulses and strokes a fac-
tor of about 28.4 globally and even 3.7 in North America in
2013. Höller and Betz (2010) analyzed 6.7 groups per pulse
or stroke on average. Due to those results, LIS optical groups
emerge from both discharge processes measured by VLF–LF
sensors but also processes lacking significant VLF–LF radia-
tion. In addition, the detected lightning sources of the applied
VHF LLS comply more with the LIS events than the groups.
Using events rather than group centroids improves in partic-
ular the finding of the coincident LMA data. The analysis of
flash extents profits from the use of events in that the extent
of an ISS-LIS flash corresponds to the full illuminated area
rather than the ISS-LIS group centroid locations. The repre-
sentation of the flash extent (density) will influence the future
assimilation of lightning data in NWP models. A statistical
analysis of (ISS-LIS) events and LF strokes and pulses will
also be of interest for creating a proxy optical dataset, e.g.,
for MTG-LI, derived from LF data.
Our grouping algorithm analyzes the elements (events or
pulses and strokes) and groups them based on their relative
location and time of occurrence to each other. First, the spa-
tial and temporal constraints, dsmerge and dtmerge, for ele-
ments within one flash must be determined. Then, a com-
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 859
bined space–time test merges the elements into flashes. It
starts with the first available element (in the data of one LLS)
and identifies all elements (of the same LLS data) within the
range of the constraints. Thereby, an element can only belong
to the same flash if both the distance to any element of the
flash is less than dsmerge and the time difference (to the same
element) is shorter than dtmerge. All elements identified for a
flash (including the initial element) are classified as used. For
each used element within a flash, the test is repeated until no
unused element can be added to the flash. This step allows for
considering propagating flashes and the potentially increas-
ing extent and duration of a flash while adding new elements.
The algorithm continues until all elements are classified as
used. Our algorithm does not limit the duration of a flash.
The number of elements per flash also remains free to the
algorithm.
The algorithm verification includes a sensitivity study
for dsmerge and dtmerge (Fig. 2) as well as a comparison
to NASA’s algorithm and concurrent SAETTA observations
(Fig. 3).
Figure 2 gives the number of flashes analyzed from all ob-
servations of the approximately 1-year period by using dif-
ferent dsmerge (panels a and c) and dtmerge (b, d) for ISS-LIS
(a, b) and Meteorage (c, d). In general, as expected, smaller
dsmerge and dtmerge increase the flash numbers because fewer
individual elements are part of a given flash, and thus more
flashes exist for the same elements. LIS flash numbers range
from 236 to 4567 for the dsmerge (dtmerge) between 50.0 and
1.0 km (1.0 and 0.1s), respectively. For the same constraints,
Meteorage flash numbers vary from 340 to 1720 flashes.
The ISS-LIS flash number decreases rapidly for dsmerge
between 0 and 10 km (Fig. 2a). The rapid change depends
on the pixel size within the ISS-LIS image. Hence, it is ex-
pected that events of one flash are partitioned within the same
frame if the dsmerge becomes smaller than the ISS-LIS image
pixel size. ISS-LIS flash numbers remain constant for dsmerge
greater than 15 km for all tested dtmerge; 0.3 s balances the
need for consistency and the wish for a strict dtmerge (Fig. 2b).
The resulting flashes are verified against concurrent 3-D
SAETTA sources, which supported the choice of our con-
straints and the identification of resulting flashes. The spatial
constraint (dsmerge of 15 km) refers directly to event loca-
tions and not to group centroids (as for NASA’s algorithm).
The chosen time constraint for ISS-LIS flashes (dtmerge of
300 ms) is similar to the P0.2 NASA flash-clustering algo-
rithm (330 ms).
The same algorithm is applied to group the Meteorage
pulses and strokes into flashes. It needs, however, modified
constraints dsmerge and dtmerge since physical processes pro-
ducing Meteorage pulses and strokes do not always corre-
spond to ISS-LIS events and occur with significantly lower
counts. Meteorage pulses and strokes do not cover the full
structure and duration of a lightning flash. Figure 2b and d
are analyzed for Meteorage flash numbers as demonstrated
for ISS-LIS flash numbers in Fig. 2a and c. To find constant
Figure 2. Total flash number based on constant, equal time con-
straint dtmerge (line color) with varying distance dsmerge for ele-
ments of ISS-LIS (a) and Meteorage (c) flashes. Panels (b) and
(d) are with constant, equal distance dsmerge (line color) and vary-
ing dtmerge for ISS-LIS and Meteorage, respectively.
constraints suitable for various situations (e.g., vertical cloud
structures, severity of a storm, flash rate), resulting flashes
for different constraints are verified manually using SAETTA
observations. Ultimately, Meteorage pulses and strokes be-
long to the same flash if they are detected within 20 km and
0.4 s. Due to the limited number of pulses and strokes, Mete-
orage dsmerge and dtmerge are coarser than the ISS-LIS merg-
ing constraints. Our constraints (20 km, 0.4 s) are consistent
with Meteorage’s flash-grouping algorithm using a separa-
tion distance of less than 10 km for subsequent CG strokes
and 20 km if IC pulses are involved. The delay between sub-
sequent discharges of the same flash must be smaller than
0.5 s in Meteorage’s algorithm. Höller and Betz (2010) pro-
vided a clustering of LINET VLF–LF pulses and strokes to
flash scale with 10 km and 1.0 s in space and time, respec-
tively. Hence, their merging constraints for a flash are finer
in space but coarser in time.
The determination of dsmerge and dtmerge does not ensure
a perfect arrangement of the elements in flashes. The objec-
tive is to find constraints leading to statistical representations
of flashes in the ISS-LIS and Meteorage data. Therefore, all
identified flashes are double-checked against concurrent 3-
D SAETTA observations. Even if it is sometimes challeng-
ing to separate the flashes in the SAETTA data, the detailed
VHF mapping helps us to understand the processes leading to
the identification of the ISS-LIS and Meteorage flashes. The
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860 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
SAETTA data can also be used to find possible false alarms
in the ISS-LIS and Meteorage data.
Figure 3 demonstrates the behavior of NASA’s flash-
merging algorithm and our developed algorithm for one ex-
ample. It shows a short time period (6.5 s) during one ISS
overpass on 10 September 2017. In Fig. 3a, there is a map
of flash locations from the P0.2 NASA flash-merging al-
gorithm and our developed algorithm as well as concurrent
VHF SAETTA sources. The ISS-LIS events (not plotted) co-
incide generally well with the SAETTA observations in both
location and time. The mapped observations are presented
in latitude, longitude and altitude time series in Fig. 3b;
20 flashes from NASA’s algorithm are confronted with 11
flashes from our developed algorithm for the same ISS-LIS
events. NASA’s merging algorithm somehow splits some
flashes, e.g., the flash between 5.3 and 6.2 s where NASA’s
algorithm identifies five flashes. Our algorithm finds a single
flash for that period, and the concurrent SAETTA observa-
tions support this result.
Our developed algorithm was additionally tested versus
GLM flash-scale data. The GLM algorithm uses the dis-
tance between events and not (as ISS-LIS) between group
centroids in order to merge events and/or groups to flashes.
WED time and spacing for events and/or groups of one GLM
flash are 330 ms and 16.5 km, respectively (Goodman et al.,
2013). The GLM flash-scale data agree very well with the
flashes identified by our algorithm utilizing the underlying
GLM events.
2.5 Flash-matching algorithm
ISS-LIS and Meteorage detect lightning in a different way.
It was described how the different signals can be merged
into a common entity, namely a flash. The intercomparison
of LLSs uses the flash scale to find concurrent observations.
Individual flashes of both LLSs are sorted into one of the
four following categories: LIS detected by both (i.e., an ISS-
LIS flash has a coincident Meteorage flash), LIS-only (i.e.,
no coincident Meteorage observations), Meteorage detected
by both (i.e., a Meteorage flash with concurrent ISS-LIS
events) or Meteorage-only (i.e., ISS-LIS does not detect the
flash). Matching criteria in space (dsmatch) and time (dtmatch )
are specified. The criteria dsmatch and dtmatch do not address
the flash mean position and time, respectively, but the single
events or pulses and strokes within a flash. Two flashes ob-
served by different LLSs are defined as matched if at least
two elements (one per flash) meet both dsmatch and dtmatch. A
given flash of the reference LLS does not necessarily corre-
spond to exactly one matched flash. It is also possible that a
flash meets the matching criteria of more than one given flash
(and is collocated with more than one flash). Hence, the two
categories, which are LIS detected by both and Meteorage
detected by both, are expected to have different counts.
The criteria dsmatch and dtmatch are determined through a
sensitivity study of the relative DEs of ISS-LIS and Mete-
orage (Fig. 4). A spatial criterion lower than 10.0 km re-
duces the relative DE of both ISS-LIS and Meteorage rapidly
(Fig. 4a: ISS-LIS, c: Meteorage). In general, the ISS-LIS rel-
ative DE is more sensitive to both dsmatch and dtmatch than the
Meteorage relative DE. This result is triggered by the low
number of Meteorage pulses and strokes (compared to the
number of ISS-LIS events) effectively hampering the find-
ing of suitable elements, i.e., pulses and strokes, for a collo-
cation. The ISS-LIS relative DE decreases within the entire
range of investigated times dtmatch. The most sensitive be-
havior occurs for dtmatch up to 1.5 s (Fig. 4b). Meteorage ap-
pears to be sensitive to dtmatch only up to 0.5 s (Fig. 4d). De-
spite the differences in sensitivity to the criteria between ISS-
LIS and Meteorage, the aim is to use the same dsmatch and
dtmatch for both LLSs. Finally, dsmatch of 20km and dtmatch
of 1.0 s are chosen to balance the individual sensitivities of
the LLSs to the criteria. They allow for the identification
of matches if, for example, ISS-LIS detects primary IC dis-
charges of a flash and Meteorage only detects a CG stroke
occurring during the final stage of the same flash. Our cri-
teria are relatively coarse compared to some former studies
(Sect. 1). Höller and Betz (2010) applied the same dtmatch but
an even coarser dsmatch (i.e., 30 km) to match LINET VLF–
LF flashes and TRMM-LIS flashes. Further investigation of
the matched flashes, e.g., the distributions of the distances
and timing offsets, will demonstrate to what extent matches
rely on the fairly coarse criteria.
A detailed analysis of distances and timing offsets between
matched flashes refines the matching algorithm further: the
number of cases in which one flash is matched to multiple
flashes of the second LLS should be reduced. Therefore, the
refined algorithm initiates with finer matching criteria, i.e.,
1 % of both dsmatch and dtmatch. It searches for one element
detected by the second LLS that meets the finer criteria for
any element of the given flash. Only if no match is found does
the allowed distance and time difference increase by 1% of
dsmatch and dtmatch, respectively. The process repeats itera-
tively until either a match is found or the allowed distance
(timing offset) exceeds the original dsmatch (dtmatch). In the
latter case, the algorithm stops and the flash is labeled un-
matched (note: the refined analysis is performed for matched
flashes only; however, the algorithm can also treat the un-
matched flashes). One or more matches for the given flash
are still possible because of the discrete increments from one
iteration to the following. There might also be flashes within
an equal distance and equal time offset to the given flash.
3 Results
The different LLSs detect flashes in different ways and with
distinct characteristics. In this section, flash observations are
compared and analyzed. As an example, the ISS overpass
with the corresponding observations of ISS-LIS, Meteorage
and SAETTA in Fig. 1 comprises (almost) the entire study
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 861
Figure 3. The map (a) and time series (b) of SAETTA observations and the mean flash positions based on the NASA LIS algorithm and our
developed algorithm for one situation on 10 September 2017. The numbers in parentheses in the legend indicate the number of identified
flashes (both algorithms analyzed the same LIS events). Colors in (a) represent the elapsed time from the initial lightning activity. Note: flash
altitudes in (b) are not known for ISS-LIS flashes but arbitrarily plotted at 15 km.
region. It lasted 169 s from FOV entering to leaving the re-
gion. The effective viewtime per 0.5×0.5grid box is in-
dicated in grayscale in Fig. 1a. Wide parts of the domain have
been seen for at least 60 s. Figure 1b additionally shows an
IR satellite image indicating the cloud tops. The example of
a single flash observed by all three LLSs during this over-
pass is given in Fig. 1c. SAETTA captures the most detail of
the flash structure, and there are significantly more ISS-LIS
events than Meteorage pulses and strokes. All but the first
Meteorage signals indicate an IC pulse. Since the first stroke
is of type CG, the entire flash is characterized as a CG flash.
First, relative DEs of ISS-LIS and Meteorage are elu-
cidated. The comparisons of matched flash location and
timing differences are discussed, and finally characteristics
of flashes, with a special interest in differences between
matched and unmatched flashes, are analyzed.
3.1 Detection comparison
This DE analysis is realized on the flash scale. Flashes were
preliminarily identified by our in-house algorithm, which
merges ISS-LIS events as well as Meteorage pulses and
strokes according to their locations and times of occurrence.
Further investigations break the flash scale down into events
and pulses and strokes, e.g., for the flash characteristics.
The period of observation spans from 1 March 2017 to
20 March 2018. In total, 330 ISS-LIS flashes and 569 Mete-
orage flashes are identified by our algorithm.
Besides the DE, the probability of false alarm (POFA)
characterizes the quality of detection. Quantifying the POFA
requires knowledge about the truth, which is the real num-
ber of flashes. SAETTA could provide a reference value
to quantify the POFA; however, not all stations have oper-
ated continuously for the entire study period. Signals from
at least six stations are needed to reconstruct and locate a
discharge signal, and 31 of 330 (89 of 569) ISS-LIS (Mete-
orage) flashes were not detected by SAETTA. SAETTA’s de-
tection efficiency and accuracy also decrease with distance
to the network’s center. A vast majority of more than 90 %
of all flashes occurred outside a distance of 100 km from
SAETTA’s center. There was evidence of VHF activity for
the vast majority (95.0 %) of the flashes not reported by
SAETTA (missed flashes). In 59.2 % of the cases, at least one
and fewer than six stations recorded signals. SAETTA light-
ning was observed just outside our matching criteria (0.2 ,
0.3 s) for 28.3 % of the missed flashes. The result indicates
that the POFA is low for both ISS-LIS and Meteorage (al-
though it cannot be quantified).
Only three (12) of the ISS-LIS (Meteorage) flashes missed
by SAETTA are located within 100 km of SAETTA’s cen-
ter. Due to the low total flash number within this close do-
main to SAETTA, a statistical analysis is ambiguous; 13 of
the 15 missed flashes near SAETTA were missed due to sta-
tion downtimes or filter criteria (spatial, temporal, reduced
χ2; Sect. 2.3). Pédeboy et al. (2018b) reported Meteorage
flashes missed by SAETTA with (absolute) peak currents
exceeding 100 kA; 2 of the 12 missed Meteorage flashes
close to SAETTA exhibit an (absolute) current above 100kA.
SAETTA data can, in fact, not provide the desired true flash
numbers, mainly due to station downtimes, and the POFA of
Meteorage and ISS-LIS cannot be calculated.
A total of 60.7 % (54) of the Meteorage flashes with-
out concurrent SAETTA sources contain one pulse or stroke
only. Those flashes with only one pulse or stroke (or one
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862 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
Figure 4. Relative detection efficiency based on constant, equal
time criterion dtmatch (line color) with varying distance dsmatch for
ISS-LIS (a) and Meteorage (c). Panels (b) and (d) are with constant,
equal distance dsmatch (line color) and varying dtmatch for ISS-LIS
and Meteorage, respectively.
event in the case of ISS-LIS) are referred to as single-element
flashes. Missing SAETTA observations for a single-element
flash might be indicative of a locating and timing problem of
the ISS-LIS event or Meteorage pulse and/or stroke (possible
false alarm). The DE analysis distinguishes results for the
complete dataset and excluded single-element flashes; 316
ISS-LIS and 367 Meteorage flashes remain after excluding
the single-element flashes. Thus, the ISS-LIS (Meteorage)
flash number is reduced by 14 (202) flashes compared to the
overall count. ISS-LIS single-element flashes are rare, while
there is a significant amount of Meteorage single-element
flashes. The result is related to the differences in optical and
LF lightning detection. The entire dataset contains 16 881
ISS-LIS events and 2144 Meteorage pulses and strokes (487
CG, 1657 IC); 15 578 events (92 %) are distributed over the
ISS-LIS flashes with a match. For Meteorage, 1439 pulses
and strokes (271 CG, 1168 IC) constitute the flashes with
matches (67 %). Hence, 55.6 % (70.5 %) of the CG strokes
(IC pulses) belong to flashes with coincident ground–space
detection. Despite coarser dsmerge and dtmerge for a Mete-
orage flash than an ISS-LIS flash, Meteorage observed 239
flashes more than ISS-LIS within similar regions and time
frames.
Figure 5a presents a histogram of the total flash detection
counts within the four categories introduced in section 2.5.
The number of single-element flashes is marked. Addition-
ally, Fig. 5 includes a map of the locations of the flashes
within each category. Figure 5b maps the flashes as a 2-D
histogram on a 0.1×0.1grid. Flashes are detected all over
the study domain for both ISS-LIS and Meteorage without
any apparent pattern, even if the number of flashes is not suf-
ficient to be statistically representative.
Table 1 summarizes all relative DEs. Daytime covers the
time from 05:00 to 17:00 UTC. Nighttime flashes are defined
between 17:00 and 05:00 UTC.
ISS-LIS was able to detect 326 of the 569 recorded Mete-
orage flashes from 1 March 2017 to 20 March 2018, a relative
DE of 57.3 %. If the notable number of Meteorage single-
element flashes is neglected, ISS-LIS detected 229 of the re-
maining 367 Meteorage flashes (62.4 %). ISS-LIS shows a
low relative DE of less than 54% for daytime flashes; 58.7 %
of the Meteorage nighttime flashes are detected by ISS-LIS.
In particular, the nighttime relative DE cannot reach the lit-
erature expectations of over 90 % for LIS (Boccippio et al.,
2002). The ISS-LIS relative DE significantly depends on the
Meteorage flash type. A flash with at least one CG stroke,
referred to as a CG flash, is detected in only 53.5 % of the
cases, while a pure IC flash is detected with 59.3 % relative
DE. ISS-LIS could detect 68.8 % of the occurring Meteorage
IC flashes with at least two pulses. If flashes with at least two
pulses and/or strokes are considered, the relative DE of IC
flashes surpasses that of CG flashes by almost 14 % and in-
creases compared to the total IC flash relative DE by 9.5 %.
Hence, CG flashes and single-pulse IC flashes especially de-
crease the total DE of ISS-LIS. All relative DEs use dsmatch
of 20 km and dtmatch of 1.0 s. Finer criteria would further de-
crease the relative DE of ISS-LIS (higher sensitivity to the
criteria than Meteorage; Fig. 4a).
Out of the total 330 ISS-LIS flashes, Meteorage detected
275 (83.3 %). The DE of Meteorage relative to ISS-LIS
flashes with at least two events equals 83.9 % (265 of 316
flashes). The relative DE of the VLF–LF Meteorage LLS
appears to be significantly higher than in former studies
(Sect. 1) using LF LLSs and TRMM-LIS. It is assumed that
the ISS-LIS detection efficiency is similar to that of TRMM-
LIS in general (Richard J. Blakeslee, personal communica-
tion, 2019), and thus Meteorage provides a high-quality LF
LLS. Moreover, the Meteorage detection efficiency in partic-
ular appears to be quite resistant to changes in dsmatch and
dtmatch. For example, halving both criteria (10 km in space,
0.5 s in time) results in a relative detection efficiency of about
78 %. More details about the sensitivity to the matching cri-
teria can be found in Sect. 2.5.
Meteorage detected 80.0 % of the 100 ISS-LIS daytime
flashes. Its relative DE reaches 84.8 % for 230 ISS-LIS night-
time flashes. The relative DE depends on the performance of
the LLS itself but also the performance and locating accuracy
relative to the reference LLS. As ISS-LIS detects flashes op-
tically, the influence of different lighting on ISS-LIS daytime
and nighttime accuracy is investigated as part of the follow-
ing section.
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 863
Figure 5. Flash category histogram (a) and spatial distribution (b) while matching ISS-LIS and Meteorage flashes for the available ISS
overpasses from March 2017 to March 2018. Categories show the number of Meteorage flashes seen by ISS-LIS: both (Meteorage flashes),
the number of ISS-LIS flashes also detected by Meteorage (both LIS flashes), and flashes detected either by Meteorage (Meteorage-only) or
ISS-LIS (LIS-only). The numbers of single-element flashes (event for ISS-LIS, pulse or stroke for Meteorage) are marked for each category
as indicated.
Table 1. Relative detection efficiencies (DEs) of Meteorage and ISS-LIS. The values in parentheses give the relative DEs for flashes with at
least two elements. The flash numbers (100 %) to calculate the DEs are indicated. Note: ISS-LIS (Meteorage) DE uses Meteorage (ISS-LIS)
flash numbers.
Overall Daytime Nighttime IC flash CG flash
ISS-LIS DE (%) 57.3 (62.4) 53.9 (60.8) 58.7 (63.0) 59.3 (68.8) 53.5 (55.4)
Meteorage flash number 569 (367) 167 (102) 402 (265) 369 (192) 200 (175)
Meteorage DE (%) 83.3 (83.9) 80.0 (80.2) 84.8 (85.5)
ISS-LIS flash number 330 (316) 100 (96) 230 (220)
3.2 Distances and timing offsets between collocated
flashes
In this section, the matched ISS-LIS and Meteorage flashes
are studied regarding their relative location and time of oc-
currence. For each element of a flash detected by one LLS
the closest (in time or in space, not a combined filter here)
element of the matched flash(es) accounts for the statistic.
One element can be closest to multiple elements of the sec-
ond LLS. The entirety of elements of flashes with matches
is analyzed statistically. Figure 6 presents the results for dis-
tances (a) and timing offsets (b) between events as well as
pulses and strokes.
Figure 6a shows histograms of the distance between a
given ISS-LIS event (Meteorage pulse and/or stroke) and the
closest pulse and/or stroke (event) of a matched flash. The
distribution given an ISS-LIS event peaks primarily between
2.50 and 3.00 km and secondarily at about 4.50 km, with a
median (mean) of 4.74 km (5.68 km). The distribution given
a Meteorage pulse or stroke has a broad maximum from 0.75
to 2.75 km, with a median (mean) of 2.31 km (3.60km). The
Meteorage pulse–stroke distance distribution features a more
pronounced (if wider) peak for less distance than the distri-
bution given an ISS-LIS event. This is due to the calcula-
tion method and the numbers of available events as well as
pulses and strokes. The higher number of (and smaller dis-
tance between) ISS-LIS events allows in general for finding
a closer event to a given Meteorage pulse or stroke than vice
versa. The cumulative distribution functions (CDFs) within
the plotted interval (Fig. 6aii) show that the distance distri-
bution given an ISS-LIS event has a larger tail than the dis-
tribution given a Meteorage pulse or stroke. The 60th per-
centile is found at approximately 5.5 and 2.6 km for a given
ISS-LIS event and Meteorage pulse or stroke, respectively.
Both Meteorage IC pulses and CG strokes exhibit similar
distributions to the overall Meteorage pulses and/or strokes
(also in the CDFs; Fig. 6aii), with the peak between 0.75
and 2.75 km. The median (mean) distance for IC pulses and
CG strokes and their match equals 2.36 km (3.63 km) and
2.22 km (3.51km), respectively. Hence, CG strokes feature a
slightly lower distance to matched events than IC pulses.
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864 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
Distances are calculated between the closest ISS-LIS
events (not groups or flashes as in former studies) and LF
pulses and/or strokes. Events provide a finer resolution of
the lightning discharge than groups, while group centroids
use radiance-weighted event locations and are interpolated to
sub-pixel locations. Bitzer et al. (2016), who used TRMM-
LIS groups and ENTLN pulses, found for both conditional
distributions median (mean) differences in location between
7.0 and 7.2 km (7.6 and 7.9 km) in North America. Those
values are in accordance with the distances observed by Rud-
losky et al. (2017) between TRMM-LIS flashes and GLD360
strokes. Zhang et al. (2019) thoroughly investigated TRMM-
LIS performance and found additional latitudinal location
offset resulting from TRMM yaw maneuvers. Their analysis
suggests a correction for TRMM-LIS group locations that
improves the TRMM-LIS group distance to NLDN pulses
and/or strokes for the summers of 2012 and 2013. The dis-
tance distribution peaks for 1–2 km after the correction (5–
6 km before the correction). The distribution peak distances
before the correction were similar to those reported by Bitzer
et al. (2016) and Rudlosky et al. (2017). Hence, it is as-
sumed that distances between TRMM-LIS groups and VLF–
LF LLS pulses and/or strokes are similar or slightly smaller
than distances comparing ISS-LIS events and Meteorage LF
pulses and/or strokes in this work. It should be mentioned
that the TRMM-LIS pixel size is slightly smaller than that
of ISS-LIS, i.e., 4.3 km (3.7 km) nadir after (before) TRMM
boost versus 4.5 km nadir.
The optical ISS-LIS sensor might be affected by different
lighting. Therefore, the accuracy of ISS-LIS flashes relative
to ground-based LLSs is explicitly investigated during day
and night (not shown as a figure). Daytime flash distances are
concentrated mainly between 2.0 and 5.0 km, and the distri-
bution peaks at about 3.5 km. The ISS-LIS nighttime flash
distribution peaks at about 5.5 km of distance to matched
Meteorage flashes. Given an ISS-LIS flash, the CDF distri-
bution also rises faster for daytime than for nighttime flash
distances. Hence, distances between coincident flashes are in
fact smaller during daytime than during nighttime. The com-
parison of ISS-LIS flashes to SAETTA reveals a small differ-
ence of up to 0.05latitude and longitude during both day-
and nighttime. ISS-LIS flashes tend to occur slightly south
and west of the corresponding SAETTA observations. The
small location difference, considering dsmatch of 20 km and
ISS-LIS spatial resolution of 4.5 km (nadir), does not signifi-
cantly influence our results. In particular, ISS-LIS maintains
its locating accuracy during daytime and during nighttime.
The timing offset subtracts the time of the matched el-
ement from the time of the given element. It yields pos-
itive and negative values according to which element oc-
curred first, with a positive value indicating that the given
element occurred later than its match. Again, the two condi-
tions, which are given an ISS-LIS event and given a Mete-
orage pulse or stroke, are applied. The resulting distribution
(Fig. 6b) peaks between 0.5 and 0.5 ms for a given ISS-LIS
event and between 1.0 and 1.0 ms for a given Meteorage
pulse or stroke. The distribution tails, with an absolute timing
offset longer than 10 ms and up to 1.0 s, are not plotted. They
are larger for a given ISS-LIS event than for a given Meteor-
age pulse or stroke. It is observed that Meteorage pulses and
strokes often do not cover the entire duration of a flash. ISS-
LIS events reflect the actual flash duration (reference to con-
current SAETTA sources) better than the Meteorage pulses
and strokes. Hence, given an ISS-LIS event and looking for
a matched Meteorage pulse or stroke, the number of avail-
able pulses and/or strokes is often limited. Several events
can have the same closest pulse or stroke even if the events
occurred in different time frames. It increases the probabil-
ity of larger timing offsets, especially for a given ISS-LIS
event compared to a given Meteorage pulse or stroke. The
CDFs (Fig. 6bii) reveal that about 20 % (5 %) of the ISS-
LIS events (Meteorage pulses and/or strokes) shown here ex-
hibit timing offsets of more than 2.5 ms. About 20 % (10 %)
of ISS-LIS events (Meteorage pulses and/or strokes) have
values lower than 2.5 ms. In the overall distribution (not
shown), time offsets exceed 10.0ms for 43 % (22 %) of ISS-
LIS events (Meteorage pulses and/or strokes). Negative time
offsets exceed 10.0 ms for 25 % (22 %) of ISS-LIS events
(Meteorage pulses and/or strokes). The distribution given an
ISS-LIS event is slightly skewed towards positive time off-
sets (given that the ISS-LIS event occurred later than its best
match stroke or pulse). The overall median (mean) values
yield 2.36 ms (54.60 ms) and 0.00 ms (2.70 ms) given an
ISS-LIS event and Meteorage pulse or stroke, respectively.
The mean for a given ISS-LIS event is an artifact of the
skewed distribution (also in the tails). Considering the ISS-
LIS integration frame time of 2.0 ms, the remaining average
statistics are close to the temporal accuracy of ISS-LIS. Both
conditional distributions given ISS-LIS and given Meteor-
age show an overall similar shape (Fig. 6b). The matched
element, considering both the ISS-LIS and Meteorage dis-
tributions, occurs with similar probability earlier or later (or
simultaneously) than the element itself, and the distribution
peak is centered at zero time offset. This is an interesting
finding since, e.g., Höller and Betz (2010) and Bitzer et al.
(2016) found that TRMM-LIS detected lightning on average
1 to 2 ms later than the ground-based LLSs. This is not the
case for ISS-LIS in our study (and again one must consider
the ISS-LIS integration time frame of 2.0 ms), although the
order of magnitude of the time offsets agrees well with our
results. Timing differences can in fact be directly compared
to those studies as the closest event provides the same time
as the closest group (groups merge several events within the
same time frame and in adjacent pixels of ISS-LIS).
The distribution given an IC pulse is also symmetric
around zero and shows a maximum between 1.0 and
1.0 ms (Fig. 6b). Its median (mean) is 0.00 ms (4.29 ms).
For CG strokes, however, the distribution peaks between
1.0 ms and 0.0 ms. The negative distribution peak and me-
dian (mean) of 0.07 ms (4.32 ms) indicate that ISS-LIS
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 865
Figure 6. Best match distance (a) and time offset (b) between a given Meteorage pulse or stroke (LIS event) and the closest ISS-LIS event
(Meteorage pulse or stroke). Histogram (i) and cumulative distribution function (ii) with bins of 0.25km (a) and 0.5 ms (b). Analyzed pulses
and strokes (events) belong to flashes with matches (spatial and temporal filters), while the pulses and/or strokes (events) of unmatched
flashes are not considered. For Meteorage, the discharge types (CG, IC) are distinguished. Only elements with absolute timing offsets of less
than 10 ms are included in the plotted time offset distribution. A positive time indicates that the given element occurred later than the best
match.
detected CG lightning slightly later than Meteorage. It might
account for the time the light of the CG lightning needs to
propagate towards the higher parts of the cloud and to be-
come visible from space.
3.3 Characteristics of detected flashes
The previous sections dealt with the relative DEs, location
and times of coincident ISS-LIS and Meteorage records.
In this section the unmatched flashes (42.7 % Meteorage,
16.7 % ISS-LIS) are also considered to investigate the fol-
lowing flash characteristics: the number of elements (events,
pulses and strokes) per flash, flash extent, flash duration,
flash mean absolute (pulse–stroke) amplitudes and indi-
vidual pulse–stroke amplitudes, flash mean (event) ampli-
tude count, flash maximum (event) amplitude count, and
the flash mean, minimum and maximum altitudes based on
SAETTA observations. They are separated per matched and
unmatched flash, per daytime (05:00 to 17:00 UTC) and
nighttime (17:00 to 05:00 UTC), and per flash type (IC, CG).
The ISS-LIS flash IC or CG attribute depends on the type
of the matched Meteorage flash. There is no flash type asso-
ciated with ISS-LIS-only flashes. As explained in Sect. 2.4,
ISS-LIS events are analyzed. The statistical results obtained
would be similar using groups instead of events, except for
the flash extent and maximum amplitude count per flash. It
should be noted that the number of daytime CG flashes is
particularly limited (24 ISS-LIS and 42 Meteorage, meaning
< 10%). Flash extents add the north–south and the east–west
distance of a flash. The north–south distance uses the maxi-
mum and minimum latitude of the flash elements. The east–
west distance of a flash is defined as the distance between the
longitudinal maximum and minimum of the elements at the
mean latitude (as that distance also depends on the latitude).
Flash durations, or the times from the first to the last element
of a flash, are only limited by the viewing time of ISS-LIS.
Theoretically, one flash could last for up to 90s. Meteorage
flash durations are not limited.
Statistics for ISS-LIS flash characteristics are summarized
in Table 2. It contains the overall average and the aver-
ages, minima and maxima observed for matched and un-
matched ISS-LIS flashes. ISS-LIS flashes have on average
51.2 events. Matched ISS-LIS flashes had more than twice
as many events as the unmatched flashes (56.6 versus 23.7).
The detailed event number distributions for matched and un-
matched ISS-LIS flashes are shown in Fig. 7a and b, re-
spectively. They include the histogram (i) and the CDF (ii).
Daytime and nighttime flashes are distinguished for the flash
types (only for matched flashes). The histogram bars add
the numbers of the different categories for the correspond-
ing bin. All following figures make use of the same layout.
ISS-LIS nighttime flashes have about two times more events
than daytime flashes. The background subtraction threshold
for the optical signal is usually greater during daytime than
during nighttime, and the sensor acquisition is less sensitive
during the day (minimum event amplitude count of 10.0 and
9.0 during daytime and nighttime, respectively). This influ-
ences the number of events per flash, with a relative reduction
of event numbers on bright backgrounds (daytime) compared
to dark backgrounds (nighttime). For example, 16.3 % (2394
of 14 710) of nighttime events observed in this study have an
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866 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
amplitude count of 9.0 (value less than the daytime thresh-
old). Additionally, ISS-LIS CG flashes comprise on average
approximately 11 % more events than IC flashes.
In accordance with the difference in event numbers, the
matched ISS-LIS flashes feature a larger extent and longer
duration than the unmatched ISS-LIS flashes (Table 2). ISS-
LIS flash extents range from 0 km (single events) to about
92 km, as shown in the distributions in Fig. 8. Peterson et al.
(2017), who studied the evolution and structure of extreme
flashes observed by TRMM-LIS, found an LIS flash with a
maximum event separation of 162 km. This size likely results
from an elongation due to scattering of optically bright dis-
charges.
This work found coincident Meteorage flashes for all but
four ISS-LIS flashes with extents exceeding 40 km. ISS-LIS
nighttime flashes are on average 13.2 km larger than day-
time flashes (and comprise more events). The result is likely
caused by the higher background subtraction threshold dur-
ing the day than during the night. It could also result from
an optical elongation of nighttime flashes. Large flashes with
the maximum event separations in Peterson et al. (2017) also
occurred at nighttime, but the groups of these flashes were
not separated by a significant fraction of the event separa-
tion. Fundamentally different cloud structures or types dur-
ing day and night might also influence the results. We would
need additional information, e.g., measuring infrared bright-
ness temperatures for the cloud tops, to verify this hypothe-
sis. Referring to the flash types, the mean extent of ISS-LIS
CG flashes is 6.1 km longer than for ISS-LIS IC flashes; how-
ever, the longest ISS-LIS flash is a nighttime IC flash.
One observed ISS-LIS flash lasted about 1.7 s (a CG night-
time flash), the longest duration found in this study. Peterson
et al. (2017) found spurious flash durations up to 28 s in con-
vective clouds, which result from high flash rates and slow
storm motion. One large propagating flash lasted 5.04 s in
their study. Figure 9 presents the duration distributions for
the matched (a) and unmatched (b) ISS-LIS flashes. Matched
ISS-LIS flashes last on average almost twice as long as ISS-
LIS-only flashes, i.e., 0.35 s versus 0.20 s (also Table 2).
About 10 % (25%) of the matched (unmatched) flashes were
recorded during a single LIS frame. Long-lasting flashes (du-
ration longer than 0.5 s) were detected by both LLSs with
high probability (92.6 %). ISS-LIS nighttime flashes last sta-
tistically 0.1 s longer than the daytime flashes. The result is
in accordance with the ISS-LIS higher relative DE and more
detected events at nighttime than during the day.
The averages, minima and maxima of Meteorage flash
characteristics are summarized in Table 3. Meteorage flashes
contain on average 3.8 (but up to 54) strokes and/or pulses.
The distributions of pulse and stroke numbers per matched
and unmatched flash are presented in Fig. 10a and b, includ-
ing the stacked histogram (i) and the CDFs (ii) as explained
for Fig. 7. Meteorage flashes seen by ISS-LIS are com-
posed of 4.4 pulses and/or strokes on average. Meteorage-
only flashes contain 2.9 pulses and/or strokes on average;
29.8 % of Meteorage flashes with a coincident ISS-LIS flash
have only one pulse or stroke (10 CG, 87 IC). Single-element
flashes constitute about 43.2 % of the unmatched Meteorage
flashes (15 CG, 90 IC). As for ISS-LIS flashes, Meteorage
flashes with a match not only contain more pulses and/or
strokes, but also extend and last longer than the unmatched
flashes (Table 3). The flash extent distributions in Fig. 11a
and b show a mean (maximum) of 12.1 km (147.5 km) and
6.9 km (109.2 km) for matched and unmatched flashes, re-
spectively. ISS-LIS detected all IC Meteorage flashes with
extents above 32 km. The longest flashes are categorized
as CG nighttime. In general, Meteorage CG flashes extend
further than IC flashes. The mean extent equals 18.2 km
(11.6 km) and 9.2 km (3.9 km) for matched (unmatched) CG
and IC flashes, respectively. This is particularly small for
unmatched IC flashes (as ISS-LIS can detect the longer IC
flashes).
Meteorage flash durations support the findings, with
matched flashes lasting on average (maximal) 0.22 s (2.3 s)
and unmatched flashes lasting on average (maximal) 0.11 s
(1.0 s). Figure 12a and b provide the duration distributions
for Meteorage flashes. Distributions of both matched (a) and
unmatched (b) flashes are sharply peaked for flashes shorter
than 0.05 s (first bin; including single-element flashes, max-
imum of 13 pulses and/or strokes per flash). The CDF
(Fig. 12aii and bii) illustrates that Meteorage CG flashes
(mean 0.28 s) last statistically longer than Meteorage IC
flashes (mean 0.11 s).
To conclude, matched flashes contain more elements, are
more extended and last longer than unmatched flashes for
both ISS-LIS and Meteorage records. Meteorage flashes ap-
pear to be on average both smaller in extent and shorter in
duration than ISS-LIS flashes. The finding is in accordance
with the different expectations for optical (LIS) and LF (Me-
teorage) signals.
Seven (two ISS-LIS, five Meteorage) exceptionally long
flashes (extent > 90 km or duration >1.5s) are analyzed using
concurrent SAETTA observations. The VHF sources high-
light the fact that there can be concurrent flashes that either
merge and form one flash or propagate at different height lev-
els. ISS-LIS and Meteorage detect both types as continuous
flashes as the LLSs capture the flashes two-dimensionally.
They can, in particular, not distinguish the different altitudes
for the latter.
Then, the VHF SAETTA LLS is used to determine the al-
titude range of each ISS-LIS and Meteorage flash. The flash
mean altitude, the flash minimum altitude and the flash max-
imum altitude (as defined in Sect. 2.3) constitute three ad-
ditional flash characteristics. Since not every ISS-LIS and
Meteorage flash was detected by SAETTA, flash numbers
are reduced compared to the ones discussed in Sect. 3.1 to
256 ISS-LIS flashes with a match, 43 ISS-LIS-only flashes,
292 Meteorage flashes with a match and 188 Meteorage-only
flashes. ISS-LIS mean event amplitude count and Meteorage
mean pulse–stroke amplitude distributions are examined for
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 867
Table 2. Overall average and the average, minimum and maximum values of ISS-LIS flash characteristics for matched and unmatched flashes.
The minimum (maximum) altitude represents the 10th (90th) percentile of concurrent SAETTA sources. Amplitude count is recorded per
event.
Average Average Average Minimum Minimum Maximum Maximum
matched unmatched matched unmatched matched unmatched
Number of events 51.2 56.6 23.7 1 1 518 116
Extent (km) 27.9 29.5 19.8 0.0 0.0 92.3 57.8
Duration (s) 0.32 0.35 0.20 0.0 0.0 1.69 0.89
Mean altitude (km) 8.2 8.2 8.2 2.9 3.6 10.9 11.6
Minimum altitude (km) 6.3 6.2 6.7 1.9 2.2 9.6 10.5
Maximum altitude (km) 9.9 10.0 9.6 2.9 4.6 12.8 12.9
Mean amplitude count 17.9 18.2 16.0 9.0 9.0 40.2 32.5
Maximum amplitude count 50.6 53.3 36.9 9.0 9.0 127.0 88.0
Figure 7. LIS event numbers of ISS-LIS flashes with a coincident Meteorage flash (a) and unmatched ISS-LIS flashes (b). Daytime, nighttime
and flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use the same colors. The CDF
additionally shows a black curve for all data. The histogram bin width is constant at five events. Note: the CG–IC attribute for an ISS-LIS
flash needs the matched Meteorage flash and does not exist for ISS-LIS-only flashes. The mean value is plotted as a dashed line. The total
number of flashes is indicated above the histogram.
the analyzed altitude levels of flashes. The lowest altitude of
detectable VHF sources increases with distance to the LMA
network, mainly due to Earth’s curvature and also due to
shading by the relief, especially in the south of the domain
(Coquillat et al., 2019a). Hence, flash minimum (and mean)
altitudes might suffer from undetected VHF sources at low
altitudes.
Figure 13 presents the mean altitude of matched (a)
and unmatched (b) ISS-LIS flashes as histograms (i) and
CDFs (ii). The distributions of the flash mean amplitude
counts in each altitude bin are included as a blue box plot
(with the mean marked as a diamond; outliers not plotted).
The distribution of mean altitudes for unmatched ISS-LIS
flashes fits that of the matched ISS-LIS flashes (although the
number of unmatched flashes is low). The mean flash alti-
tudes average about 8.2 km (Table 2).
The overall ISS-LIS flash mean altitude distribution,
which is dominated by 83.3 % flashes with a match, peaks
at about 9.5 km, as shown in the histogram in Fig. 13ai. The
daytime distribution has a second mode near 5.0 km of al-
titude. ISS-LIS flashes reach on average altitudes of 9.9 km
and were observed up to almost 13 km of altitude (Table 2)
(a noteworthy high value considering the tropopause at 10 to
12 km of altitude).
Differences between matched and unmatched ISS-LIS
minimum flash altitudes are approximately 0.5 km, with
matched flashes showing lower minima (distributions not
shown). The difference is significant as it exceeds the pre-
dicted SAETTA altitude error (about 0.2 km over wide parts
of the domain); 89.7 % of the 126 ISS-LIS flashes with min-
ima less than (or equal to) 6.0 km of altitude have a coin-
cident Meteorage flash. ISS-LIS flashes with minima above
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868 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
Figure 8. Flash extents of ISS-LIS flashes with a coincident Meteorage flash (a) and unmatched ISS-LIS flashes (b). Daytime, nighttime and
flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use the same colors. The CDF additionally
shows a black curve for all data. The histogram bin width is constant at 2.5 km. Note: the CG–IC attribute for an ISS-LIS flash needs the
matched Meteorage flash and does not exist for ISS-LIS-only flashes. The mean value is plotted as a dashed line. The total number of flashes
is indicated above the histogram.
Figure 9. Flash duration of ISS-LIS flashes with a coincident Meteorage flash (a) and unmatched ISS-LIS flashes (b). Daytime, nighttime and
flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use the same colors. The CDF additionally
shows a black curve for all data. The histogram bin width is constant at 0.05 s. Note: the CG–IC attribute for an ISS-LIS flash needs the
matched Meteorage flash and does not exist for ISS-LIS-only flashes. The mean value is plotted as a dashed line. The total number of flashes
is indicated above the histogram.
6.0 km (173) are detected by Meteorage in 82.7 % of the
cases. Overall, Meteorage better detected low-altitude ISS-
LIS flashes than ISS-LIS flashes restricted to middle and high
levels.
The amplitude count of ISS-LIS flashes increases in gen-
eral with the mean altitude (Fig. 13ai and bi). The high-
est observed flash mean altitudes occur mainly for pure IC
flashes and show statistically high-amplitude counts. They
likely originate within high-reaching convective clouds like
cumulus congestus and cumulonimbus. Similar results re-
garding the amplitude count distributions were identified for
the ISS-LIS flash maximum altitude distributions and max-
imum event amplitude count per flash at different altitudes
(not shown). Matched and unmatched ISS-LIS flashes fea-
ture almost similar mean amplitude counts (Table 2). The
overall brightest event (127.0) occurred during nighttime for
a matched flash. The strongest optical signal during the day
(105.0) is also recorded within a matched flash. Accordingly,
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 869
Table 3. Overall average and the average, minimum and maximum values of Meteorage flash characteristics for matched and unmatched
flashes. The minimum (maximum) altitude represents the 10th (90th) percentile of concurrent SAETTA sources. The maximum pulse–stroke
amplitude is the maximum current observed for the flash (negative or positive).
Average Average Average Minimum Minimum Maximum Maximum
matched unmatched matched unmatched matched unmatched
Number of pulses and/or strokes 3.8 4.4 2.9 1 1 54 26
Extent (km) 9.9 12.1 6.8 0.0 0.0 147.5 109.2
Duration (s) 0.17 0.22 0.11 0.0 0.0 2.32 0.98
Mean altitude (km) 7.6 8.1 6.7 2.7 2.1 11.2 11.0
Minimum altitude (km) 5.7 6.1 5.1 1.7 1.6 10.3 9.4
Maximum altitude (km) 9.2 9.8 8.2 3.2 2.1 12.8 12.9
Mean absolute amplitude (kA) 9.5 8.0 11.6 1.3 1.1 98.1 102.9
Maximum pulse–stroke amplitude (kA) 4.82.28.2149.0144.0 150.0 128.5
Figure 10. Pulse–stroke number of Meteorage flashes with a coincident ISS-LIS flash (a) and unmatched Meteorage flashes (b). Daytime,
nighttime and flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use the same colors. The CDF
additionally shows a black curve for all data. The histogram bin width is constant at two pulses and/or strokes. The mean value is plotted as
a dashed line. The total number of flashes is indicated above the histogram.
maximum event amplitude counts averaged over all flashes
of about 53.3 and 36.9 characterize matched and unmatched
flashes, respectively (Table 2). Flashes containing the opti-
cally brightest events have a higher chance of producing sig-
nificant LF signals and being detected by Meteorage than the
optically darker flashes.
The comparison of altitudes of Meteorage flashes with and
without ISS-LIS matches aims to study how ISS-LIS can de-
tect low-altitude flashes. The flash mean (absolute) ampli-
tude and maximum pulse–stroke amplitude per flash are ad-
ditionally analyzed for each altitude bin in the histograms.
The maximum amplitude per flash can either show a pos-
itive or negative current. Results are presented in Fig. 14
for the altitude maximum with the mean absolute amplitude
per flash. Mean flash altitudes average 8.1 km for Meteorage
flashes with a match (Table 3). They are on average 1.4 km
lower for the Meteorage-only flashes. The mean altitude of
matched flashes is similar to that of ISS-LIS matched flashes
(Fig. 13a). The unmatched flashes, however, differ by about
1.5 km of altitude (difference well above the SAETTA alti-
tude uncertainty). Meteorage flash maximum altitudes con-
firm this result (Fig. 14): flashes with a coincident ISS-LIS
flash reach on average 9.8 km of altitude. The Meteorage-
only flashes feature a maximum altitude of 8.2 km on aver-
age. The maximum altitude distribution peaks, as for the ISS-
LIS matched flashes, at about 11.0 km of altitude (Fig. 14).
For the Meteorage-only flashes, another mode exists between
6.5 and 7.0 km of altitude. The daytime distribution of un-
matched Meteorage flashes peaks at the lower altitudes. It is
indicative of the ISS-LIS reduced DE for low-altitude flashes
(during all times and even more pronounced in daytime than
during the night). Meteorage flashes with maxima exceeding
10.0 km (248) are detected by ISS-LIS in 75.4 % of the cases.
The ISS-LIS relative DE for Meteorage flashes with maxima
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870 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
Figure 11. Flash extent of Meteorage flashes with a coincident ISS-LIS flash (a) and unmatched Meteorage flashes (b). Daytime, nighttime
and flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use the same colors. The CDF
additionally shows a black curve for all data. The histogram bin width is constant at 2.5 km. The mean value is plotted as a dashed line. The
total number of flashes is indicated above the histogram.
Figure 12. Meteorage flash duration with a coincident ISS-LIS flash (a) and unmatched Meteorage flashes (b). Daytime, nighttime and flash
type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use the same colors. The CDF additionally shows
a black curve for all data. The histogram bin width is constant at 0.05 s. The mean value is plotted as a dashed line. The total number of
flashes is indicated above the histogram.
lower than (or equal to) 10.0 km (232) is only 45.3 %. This
trend still influences the flash mean and minimum altitudes
(Table 3). Hence, it is confirmed that ISS-LIS flash detection
declines from high- to low-altitude flashes. The result agrees
with the case study of Thomas et al. (2000), who found sig-
nificantly less skill of TRMM-LIS for (CG) discharges near
the cloud base than for lightning channels propagating to
near the top of the clouds.
Figure 15 shows the distribution of minimum flash alti-
tudes with the maximum (pulse–stroke) amplitude per flash
in each altitude bin. Low-altitude flashes (minimum alti-
tudes below 5.0 km) feature statistically higher flash mean
(not plotted) and maximum amplitudes than flashes occur-
ring above 5.0 km of altitude (Fig. 15). Those flashes are
mainly identified as CG flashes. The analysis of the flash
maximum amplitude shows that those low-altitude flashes
are dominated by negative maximum currents. The flashes
with minimum altitudes above 5.0 km exhibit statistically
more positive than negative maximum currents. Further in-
vestigation reveals that about 94% of the (absolute) currents
above 22.5 kA belong to CG strokes. The strongest currents
reach up to 150.0 kA (both negative and positive currents)
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F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 871
Figure 13. Flash mean altitude of ISS-LIS flashes (from concurrent SAETTA observations) with a coincident Meteorage flash (a) and un-
matched ISS-LIS flashes (b). Daytime, nighttime and flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding
CDF (ii) use the same colors. The CDF additionally shows a black curve for all data. The histogram bin width equals 0.5 km. Note: the
CG–IC attribute for an ISS-LIS flash needs the matched Meteorage flash and does not exist for ISS-LIS-only flashes. The mean value is
plotted as a dashed line. The total number of flashes is indicated above the histogram. The blue box plots (median as a line, mean as a
diamond, interquartile range – IQR – as a box, 1.5 IQR as whiskers; outliers not plotted) represent the distributions of the ISS-LIS mean
event amplitude count per flash for each altitude bin.
Figure 14. Flash maximum altitude of Meteorage flashes (from concurrent SAETTA observations) with (a) and without (b) a coincident
ISS-LIS flash. Daytime, nighttime and flash type, IC and CG, are indicated by the colors. The histogram (i) and corresponding CDF (ii) use
the same colors. The CDF additionally shows a black curve for all data. The histogram bin width equals 0.5 km. The mean value is plotted as
a dashed line. The total number of flashes is indicated above the histogram. The blue box plots (median as a line, mean as a diamond, IQR
as a box, 1.5 IQR as whiskers; outliers not plotted) represent the distributions of the Meteorage mean absolute amplitude per flash for each
altitude bin (scale fixed range from 0 to 30 kA).
and are related to CG strokes. The vast majority (90.6 %) of
the CG strokes have negative currents in this study. IC pulse
currents do not exceed 50 kA. About 90 % of pulses and/or
strokes with an amplitude below 10.0 kA are IC pulses. A
similar result is provided by Cummins and Murphy (2009).
They found that 90 % of positive LF currents with less than
10.0 kA belong to IC pulses. Negative currents are observed
for approximately 26 % of the IC pulses.
The Meteorage mean (maximum) flash absolute amplitude
equals 8.0 kA (13.2 kA) and 11.6 kA (18.1 kA) for matched
and unmatched flashes, respectively. The difference between
matched and unmatched flashes is attributed to some low-
to mid-level flashes producing strong currents and not be-
ing detected by ISS-LIS (compare panels a and b in Figs. 14
and 15). However, the overall distributions of absolute flash
www.atmos-meas-tech.net/13/853/2020/ Atmos. Meas. Tech., 13, 853–875, 2020
872 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
Figure 15. As Fig. 14 for the minimum altitude of Meteorage flashes with (a) and without (b) a match. Here, the blue box plots represent the
distributions of the Meteorage maximum (pulse–stroke) amplitude per flash (positive or negative currents) for each altitude bin.
amplitudes appear to be similar for matched and unmatched
Meteorage flashes.
Flashes observed in this study show a statistical relation-
ship between the polarity of the maximum (LF) current and
the altitude. The relationship was detailed for the flash min-
imum altitudes and also appears for the flash maximum alti-
tudes. In this study, flashes with maximum altitudes below
10.0 km exhibit mainly negative maximum currents. As it
was found that the ISS-LIS DE is 30 % higher for flashes
with maximum altitudes above 10.0 km than for flashes re-
stricted to lower levels, the polarity of the flash maximum
current might provide the first information on whether a flash
is detected by ISS-LIS. This finding is probably specific for
the storm types and flashes analyzed in this study (and re-
gion). The observed relationship between the polarity of the
maximum current of a flash and its altitude might change for
inverted-polarity storms or hybrid (IC+CG) flashes.
4 Conclusions
This study compares the results of the LF ground-based
Meteorage LLS, the satellite sensor ISS-LIS and the VHF
ground-based LMA SAETTA. The study domain is bounded
to a region near Corsica in the Mediterranean Sea where
SAETTA data are available. As ISS-LIS has been operating
since March 2017, the period is confined to about 1 year from
1 March 2017 to 20 March 2018.
A new algorithm is developed to group ISS-LIS events
as well as Meteorage pulses and strokes to flashes. The al-
gorithm is validated using concurrent SAETTA observations
and the results of the existing NASA LIS algorithm.
ISS-LIS detected in total 16 881 events distributed over
330 flashes during its overpasses of the study domain. Me-
teorage data are filtered for the times of ISS overpasses. It
contains 2144 pulses and/or strokes (487 CG, 1657 IC) in
569 flashes. ISS-LIS detected about 57.3 % of the Meteorage
flashes. Cloud-to-ground (CG) flashes and single-pulse intra-
cloud and cloud-to-cloud (IC) flashes especially decrease the
overall relative detection efficiency (DE) of ISS-LIS. A rela-
tive DE of 53.9 % was observed for flashes detected by Me-
teorage during daytime. LIS detected Meteorage IC flashes
with about a 6 % higher relative DE than CG flashes. The
LF Meteorage LLS was able to detect more than 80 % of all
occurring ISS-LIS flashes.
Distances and timing offsets between matched ISS-LIS
and Meteorage flashes are analyzed. A mode (median) dis-
tance (given a Meteorage flash) of about 1.8 km (2.3 km)
indicates a fairly accurate collocation of the flashes. Given
an ISS-LIS flash, the mode (median) distance equals about
3.0 km (4.7 km). The majority of distances between matched
flashes are within the ISS-LIS pixel resolution (4.5 km nadir,
6.2 km at the edge of the field of view). The absolute timing
offset distribution between a given Meteorage flash and the
matched ISS-LIS flash is sharply peaked for less than 1.0 ms.
Considering the ISS-LIS frame integration time of 2.0 ms,
this is a very satisfying result. An analysis of the closest el-
ements (events and pulses and/or strokes) reveals that, with
similar probability, ISS-LIS or Meteorage detected lightning
first, while the mode timing offsets remain within the LIS
frame integration time. For CG strokes, however, ISS-LIS
tended to detect the lightning activity later than Meteorage.
All offsets increase relatively from the distribution given a
Meteorage flash to the distribution given an ISS-LIS flash.
Atmos. Meas. Tech., 13, 853–875, 2020 www.atmos-meas-tech.net/13/853/2020/
F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations 873
This finding is likely caused by the significantly lower num-
ber of pulses and strokes than the number of events. Thus, it
is more likely to find an event close to a pulse or stroke than
vice versa.
For an enhanced understanding of the flash detection by
ISS-LIS and Meteorage, characteristics of the flashes are in-
vestigated. In accordance with, e.g., Rudlosky et al. (2017)
and Zhang et al. (2019), the probability of a match increases
with a larger flash extent and flash duration. A matched flash
extended on average almost twice as wide and lasted twice
as long as a flash not seen by both ISS-LIS and Meteorage.
In a similar manner, the matched flashes contained on av-
erage twice the number of elements as a flash observed by
only one of the LLSs. ISS-LIS is sensitive to optical signals,
while Meteorage detects LF signals of electrical discharges.
Nevertheless, ISS-LIS flashes with at least one very bright
event were more likely to be detected by Meteorage than
optically darker flashes. Using the 3-D lightning location
of concurrent SAETTA observations, ISS-LIS and Meteor-
age flash altitudes are compared. Altitude-related behaviors
are likely driven by the range of IC and CG flash altitudes.
Detailed results for the flash types are given in Sect. 3.3.
Matched flashes of both ISS-LIS and Meteorage feature sim-
ilar mean altitudes near 8.2 km on average. Unmatched Me-
teorage flashes occurred on average 1.4 km lower than Me-
teorage flashes seen by ISS-LIS. The maximum altitude of
a flash significantly influenced the detectability by ISS-LIS
(compare, e.g., Thomas et al., 2000). Meteorage flashes with
maxima exceeding 10.0 km of altitude were detected by ISS-
LIS in 75.4 % of the cases. The ISS-LIS relative DE for
Meteorage flashes with maxima lower than 10.0 km of alti-
tude is only 45.3 %. The Meteorage flash detection depended
slightly on the flash minimum altitude; 89.7 % of the ISS-LIS
flashes with minima less than 6.0 km of altitude had a coin-
cident Meteorage flash. ISS-LIS flashes with minima above
6.0 km of altitude had a coincident Meteorage flash in 82.7 %
of the cases.
Further investigation revealed that the optical brightness
of ISS-LIS flashes is somewhat correlated with the flash
altitude, with increasing (both mean and maximum event)
amplitude counts for increasing flash altitudes. Meteorage
amplitudes increased statistically with decreasing flash al-
titudes. The polarity and the current of the strongest pulse
or stroke within a Meteorage flash showed particular poten-
tial to gain qualitative flash altitude information. Flashes with
maximum currents of 10 kA or lower remained mainly be-
low 10.0 km of altitude. As stated earlier, the ISS-LIS relative
DE was 30 % higher for those flashes than for flashes with
maximum altitudes above 10.0 km. This finding will need
additional proof, but it can be useful for mimicking satellite
lightning products using LF LLSs.
This study analyzes satellite observed lightning over an ex-
tratropical region and compares the observations to ground-
based LLSs. Our results, including the statistics, use about
1 year of data within the limited region around Corsica is-
land. This results in a limited number of lightning cases. The
limited region enables the direct unique comparison of not
only ISS-LIS and LF Meteorage but also the VHF SAETTA
LLS. Hence, ISS-LIS and Meteorage flash detection is in-
vestigated in more detail, e.g., considering the concurrent
SAETTA lightning source altitudes. The coincidences be-
tween ISS-LIS and Meteorage flashes do not always have
a one-to-one correspondence. It is, in addition, an artifact of
the relatively coarse match constraints of 20.0 km in space
and 1.0 s in time. The constraints are validated and their influ-
ence on the results is seen in the matched distance and timing
offset distributions. It should be mentioned that the available
ISS-LIS data are the provisional P0.2 version for this work,
which represents close to but not quite the fully validated data
of ISS-LIS. Due to our limited number of cases, all ISS-LIS
data are treated in the same way independent of the position
within the ISS-LIS field of view (FOV). It is known that the
ISS-LIS pixel (event) resolution and the DE decrease near
the edge of the FOV. However, it was decided not to filter
or reduce the observed cases further in order to allow for a
statistical analysis. Our method can be applied to geostation-
ary satellite LLSs, i.e., GLM and the future MTG-LI, and the
comparison of their observations to ground-based LLSs. It
is planned to study GLM and NLDN lightning observations
in America using our methodology. The geostationary satel-
lite observes one region continuously, and thus there will be
many more cases for the statistics. The results might be com-
pared to our results of the comparison of ISS-LIS and Mete-
orage.
Data availability. ISS-LIS provisional science data are avail-
able via NASA and HyDRO Search at the following DOI:
https://doi.org/10.5067/LIS/ISSLIS/DATA204 (Blakeslee et al.,
2017). Fully validated ISS-LIS data are provided by NASA and Hy-
DRO Search. SAETTA data are available to members of HyMeX
on the HyMeX website and can be provided on demand. They
are also available on the AERIS/SEDOO/HyMeX database (https:
//www.aeris-data.fr/, Coquillat et al., 2019b). Meteorage data are
provided by and are the property of Meteorage as a company.
Author contributions. FEr, EDe and OCa designed the methodolo-
gies to merge and analyze the lightning data. FEr implemented the
methods and verified both the code and results. FEr created all the
plots. RJB, SPe and SCo provided the lightning data and some ex-
pertise on their quality. FEr wrote the paper. All authors contributed
to revisions of the paper.
Competing interests. The authors declare that they have no conflict
of interest.
Special issue statement. This article is part of the spe-
cial issue “Hydrological cycle in the Mediterranean
www.atmos-meas-tech.net/13/853/2020/ Atmos. Meas. Tech., 13, 853–875, 2020
874 F. Erdmann et al.: Concurrent ISS-LIS, Meteorage and SAETTA lightning observations
(ACP/AMT/GMD/HESS/NHESS/OS inter-journal SI)”. It is
not associated with a conference.
Acknowledgements. Felix Erdmann thanks the CNES and Météo-
France for funding his PhD. This work is a contribution to the
HyMeX program through the EXAEDRE project, grant ANR-16-
CE04-0005, funded by the French research foundation ANR and
the SOLID project, funded by CNES. Acknowledgements are also
addressed to the CORSiCA-SAETTA main sponsors (Collectivité
Territoriale de Corse through the Fonds Européen de Développe-
ment Régional of the European Operational Program 2007-2013
and the Contrat de Plan Etat Région, HyMeX/MISTRALS, Obser-
vatoire Midi-Pyrénées, Laboratoire d’Aérologie, CNES) and many
individuals and regional institutions in Corsica that host the 12 sta-
tions of the network or helped us to find sites. The authors also
want to thank the SAETTA team. EUMETSAT MSG/SEVIRI data
were provided by SATMOS (Météo-France/CMS). We thank the
AERIS/ICARE Data and Services Center for providing access to
and visualization for the data used in Fig. 1b.
Financial support. This research has been supported by the Centre
National d’Etudes Spatiales (grant no. SOLID).
Review statement. This paper was edited by Domenico Cimini and
reviewed by Kenneth Cummins and two anonymous referees.
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... It covers a storm scale resolution of 5-10 km at temporal resolution of 2 ms and a flash detection efficiency of 93 ± 4% at night and 73 ± 11% during day time. After the TRMM, an LIS was placed on the international space station (ISS) in Feb 2017 (Erdmann et al. 2020). On the space station, the LIS monitors total global lightning in both day and night and covers almost the entire globe (Liu et al. 2020). ...
... The ISS operates in low earth orbit (LEO) and traverses an area of the surface up to three times per day (two times in tropical regions). Lightning observation of a specific point lasts up to 90 s per overpass due to the ISS orbit characteristics and the LIS FOV of approximately 655 9 655 km 2 (Erdmann et al. 2020). ...
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This paper provides an overview on the spatiotemporal distribution and evolution mechanism of lightning. The predominant mechanism of ozone formation in the upper troposphere is lightning-induced precursors such as oxides of nitrogen (NOx), carbon monoxide (CO), and hydrocarbons (HC). Lightning-induced NOx (LNOx) is one of the major ordinary sources of NOx in the upper atmosphere, particularly in the tropical region, but it is still highly uncertain as to the exact quantity. Various ground measurements, satellite observations and modelling studies on the lightning and global NOx source rate have been extensively studied and compared to find the variability in estimated global lightning-induced NOx. Lightning can influence the climate via the production of nitrogen oxides (NO + NO2 = NOx) followed by the production of ozone, another efficient greenhouse gas. The global annual lightning NOx of 5 ± 3 Tg year−1 has been estimated by modelling studies with an ozone creation efficiency of 6.5 ± 4.7 times that of surface NOx sources. Understanding and quantifying the processes and production of lightning and LNOx is important for assessment of ozone concentrations and its associated impacts on the global climate.
... The TRMM satellite was a joint project between the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) (Kummerow et al., 1998) and LIS was an instrument onboard TRMM that detected lightning at storm-scale resolution (∼3-6 km). Although the detection efficiency of the LIS instrument can vary based on latitude and land/ocean differences (Erdmann et al., 2020), the TRMM LIS improved upon its predecessor, the OTD onboard Microlab-1 (later renamed Orbview-1), by detecting approximately 90% of all lightning in TRMM's swath (Cecil et al., 2014). TRMM orbited from the end of 1997 to early 2015. ...
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The objective of this study is to determine the relationship between lightning observed by the Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) and seven large‐scale environmental variables obtained from the 3‐hourly Modern‐Era Retrospective analysis for Research and Application version 2 (MERRA‐2) reanalysis in the tropics and subtropics. The large‐scale environmental variables used are: convective available potential energy (CAPE), normalized CAPE (nCAPE), lifting condensation level (LCL), column saturation fraction (r), 700‐hPa omega, low‐level wind shear (LS) from 900‐700 hPa and deep wind shear (DS) from 900‐300 hPa. All environmental variables show a significant shift towards larger values when lightning is present except for shear. DS decreases when lightning is present, while LS shows little mean change. However, strong geographical differences exist in the relationship between the environmental variables and lightning occurrence, particularly between land and ocean and the tropics and subtropics. Using a logistic regression, a lightning parameterization for global climate models (GCMs) is created using the above environmental variables as predictors while also adding geographic indicators (coast, slope and latitude) and terms representing interactions between the predictors. The logistic regression predicts lightning occurrence accurately up to 86% of the time and is further applied to MERRA‐2. While there are regions of overprediction and underprediction, the lightning parameterization performance shows promising potential for use in GCMs.
... A similar Lightning Imager (LI) will be on the Meteosat Third Generation satellite, planned for launch into a geostationary orbit in 2022 to cover the region of Africa, Europe as well northern South America and parts of the Atlantic and Indian Ocean (European Space Agency [ESA] Earth Observation Portal, 2020; European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], 2014). Since the GLM and the LI will be used operationally for the next two decades, it is of interest to understand their sensitivities to various lightning and cloud properties (e.g., Erdmann et al., 2020). ...
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Abstract We analyze a nighttime negative cloud‐to‐ground lightning flash in Colombia observed from the ground with a high‐speed camera at 5,000 images per second and from space by the Atmosphere‐Space Interactions Monitor (ASIM) on the International Space Station (ISS), the Lightning Imaging Sensor also on the ISS (ISS‐LIS), and the Geostationary Lightning Mapper (GLM) on GOES‐16. The space instruments measure the oxygen band at 777.4 nm, allowing for direct comparisons of measurements, and the ground‐based camera observes in a wide visible band. After conversion to energy emitted at the cloud top, we find a good linear correspondence of the optical energies measured by the three space instruments, except that GLM values were 3 times higher. We attribute this mainly to the difference in viewing angles between spacecraft and the cloud. Over the entirety of the ASIM observed flash, optical pulses were detected by GLM and LIS, only when the energy reported by ASIM was greater than 332 J and 949 J, respectively. Their detection rate corresponds to 14% and 2.5%, respectively, of the flash duration observed by ASIM. The temporal variation of the high‐speed camera luminosity matched well the features observed by ASIM around the time of the stroke but reached ~3.9 times higher peak intensity during the return stroke, attributed to its broader spectral sensitivity band and a viewing angle advantage.
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Widespread event of lightning occurred in two states of eastern India on June 25, 2020, killing 83 people in Bihar and 24 people in Uttar Pradesh (UP). Lightning event is studied using ground-based lightning observational data and Weather Research and Forecasting (WRF) model. A Specialized forecast system for lightning and thunderstorm is needed to minimize the loss of lives. The updraft and ice particle concentration play essential roles in the initialization of lightning inside the thundercloud. The charge generation and separation inside the clouds play an essential role in the severity of lightning. The Lightning Potential Index (LPI) measures the potential of charge generation and separation inside the clouds. It plays a significant role in determining lightning-prone zones. As the monsoon intensified over the Indo Gangetic Plains, lightning simulation is carried out using an ensemble of different WRF model configurations. The model has been integrated from 24th June 0000 UTC to 26th June 0600 UTC with an ensemble of 9 members. 8 members are simulated with a single domain (3 km resolution), and only the second member is simulated with a triple nested domain (9, 3, and 1 km resolution) over Bihar. The ensemble consists of 1 control +8 members with different configurations of the WRF model. LPI is calculated using the model-derived parameters. Furthermore, the model explicitly simulated lightning flash count using a lightning parameterization scheme. The results are analyzed using the Indian Institute of Tropical Meteorology (IITM) ground-based observation data. Every ensemble member's results are distinct from each other. This shows the sensitivity of every configuration. Member 2 (M2) is the triple nested member; it uses the same physics option as member 1 (M1). Moreover, M2 shows comparatively good results towards the observation. Simulated radar reflectivity is compared and analyzed using Indian National Satellite System (INSAT-3D) 3D Brightness Temperature (BT). To check the results of all ensemble members model skill score has been calculated. Ensemble probability is calculated to measure the spatial pattern and threat of lightning based on LPI, and it recorded the high lightning threat (90–100) % probability over northwest Bihar (Gopalganj), and it also recorded the heavy rainfall (300 mm). The skill scores of simulated lightning flash count in M2, M8, and M9 showed reasonably good POD values (0.6, 0.5, and 0.69, respectively).
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Coincident Geostationary Lightning Mapper (GLM) and National Lightning Detection Network (NLDN) observations are used to build a generator of realistic lightning optical signal in the perspective to simulate Lightning Imager (LI) signal from European NLDN-like observations. Characteristics of GLM and NLDN flashes are used to train different machine learning (ML) models, that predict simulated pseudo-GLM flash extent, flash duration, and event number per flash (targets) from several NLDN flash characteristics. Comparing statistics of observed GLM targets and simulated pseudo-GLM targets, the most suitable ML-based target generators are identified. The simulated targets are then further processed to obtain pseudo-GLM events and flashes. In the perspective of lightning data assimilation, Flash Extent Density (FED) is derived from both observed and simulated GLM data. The best generators simulate accumulated hourly FED sums with a bias of 2% to the observation, while cumulated absolute differences remain of about 22 %. A visual comparison reveals that hourly simulated FED features local maxima at the similar geolocations as the FED derived from GLM observations. However, the simulated FED often exceeds the observed FED in regions of convective cores and high flash rates. The accumulated hourly area with FED>0 flashes per 5 km×5 km pixel simulated by some pseudo-GLM generators differs by only 7% to 8% from the observed values. The recommended generator uses a linear Support Vector Regressor (linSVR) to create pseudo-GLM FED. It provides the best balance between target simulation, hourly FED sum, and hourly electrified area.
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The Atmosphere-Space Interactions Monitor (ASIM) on the International Space Station (ISS) provides optical radiances and images of lightning flashes in several spectral bands. This work presents a lightning flash simultaneously observed from space by ASIM, the Geostationary Lightning Mapper (GLM) and the Lightning Imaging Sensor on the International Space Station (ISS-LIS); and from ground by the Colombia Lightning Mapping Array (Colombia-LMA). Volumetric weather radar provides reflectivity data to help to interpret the effects of the cloud particles on the observed optical features. We found that surges in radiance in the band at 777.4 nm appear to be related mostly with lightning processes involving currents as well with branching of lightning leaders with new leader development. In cloud areas with reflectivity <18 dBZ above the lightning leader channels at altitudes >7 km, these have been imaged by ASIM and GLM. But in the region with reflectivity <23 dBZ, despite its lower cloud tops and similar altitudes of lightning channels, these have been almost undetectable. The calculated relative optical depths are consistent with the observed optical intensity at the cloud top. Despite the effects of the cloud particles and the altitude of the lightning channels on the attenuation of the luminosity, the luminosity of the lightning channels due to different processes is fundamental for the imaging of lightning from space.
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During February 2019, two severe storms affected the island of Crete, located in south Greece. Both storms produced excessive rainfall, provoking severe damages, especially in the western part of Crete. The role of the prevailing synoptic patterns and the interaction of the flow with the high mountains of Crete were investigated. For this purpose, a variety of observational and numerical model data were exploited, including data from a dense rain gauge network, satellite imagery, and model analysis of various parameters describing the stability of the impinging flow. The first storm was a long-lasting event, with convective outbreaks embedded in a more stratiform rainfall pattern. The second storm was brief but mostly convection dominated. The analysis of the available data underlined the role of the low-level convergence upstream of the mountains during both storms, highlighting similarities and differences, as well as the role of the stability of the impinging flow. High soil moisture content was also evidenced as a key ingredient for the severe flooding that occurred during the second storm. This work complements similar studies on the role of Mediterranean islands and their topography on the spatial and temporal distribution of extreme rainfall.
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Deployed on the mountainous island of Corsica for thunderstorm monitoring purposes in the Mediterranean Basin, SAETTA is a network of 12 LMA (Lightning Mapping Array, designed by New Mexico Tech, USA) stations that allows the 3-D mapping of very high-frequency (VHF) radiation emitted by cloud discharges in the 60–66 MHz band. It works at high temporal (∼40 ns in each 80 µs time window) and spatial (tens of meters at best) resolution within a range of about 350 km. Originally deployed in May 2014, SAETTA was commissioned during the summer and autumn seasons and has now been permanently operational since April 2016 until at least the end of 2020. We first evaluate the performances of SAETTA through the radial, azimuthal, and altitude errors of VHF source localization with the theoretical model of Thomas et al. (2004). We also compute on a 240 km × 240 km domain the minimum altitude at which a VHF source can be detected by at least six stations by taking into account the masking effect of the relief. We then report the 3-year observations on the same domain in terms of number of lightning days per square kilometer (i.e., total number of days during which lightning has been detected in a given 1 km square pixel) and in terms of lightning days integrated across the domain. The lightning activity is first maximum in June because of daytime convection driven by solar energy input, but concentrates on a specific hot spot in July just above the intersection of the three main valleys. This hot spot is probably due to the low-level convergence of moist air fluxes from sea breezes channeled by the three valleys. Lightning activity increases again in September due to numerous small thunderstorms above the sea and to some high-precipitation events. Finally we report lightning observations of unusual high-altitude discharges associated with the mesoscale convective system of 8 June 2015. Most of them are small discharges on top of an intense convective core during convective surges. They are considered in the flash classification of Thomas et al. (2003) to be small–isolated and short–isolated flashes. The other high-altitude discharges, much less numerous, are long-range flashes that develop through the stratiform region and suddenly undergo upward propagations towards an uppermost thin layer of charge. This latter observation is apparently consistent with the recent conceptual model of Dye and Bansemer (2019) that explains such an upper-level layer of charge in the stratiform region by the development of a non-riming ice collisional charging in a mesoscale updraft.
Conference Paper
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We examined the initial conditions leading to negative cloud-to-ground (-CG) flashes with a return stroke larger than 100 kA (absolute value), so called-CG<-100kA flashes. The dataset is made of 88 flashes observed during summer 2017 over Corsica in France by a Lightning Locating System (Météorage), a Lightning Mapping Array (SAETTA) and BLESKA, a broadband HF magnetic field analyzer. We found that-CG<-100kA flashes exhibited in average a vertical extent of 2730m and initiated at an altitude of 3720m, these values being far below those we recorded for-CG>-100kA flashes, respectively 3600m and 5350m. In addition,-CG<-100kA flashes presented a short delay of about 2ms between the first preliminary breakdown pulse and the return stroke. We concluded that-CG<-100kA flashes are mainly related to low base and top thunderclouds which combined with the elevated terrain in Corsica might enhance the vertical electric field and the electrical charges motion resulting in large return strokes. Finally, we noted that all the analyzed strokes were followed by a period ranging from 7ms to 98ms during which no VHF activity was detected by SAETTA, likely to be related to the continuing current phase. INTRODUCTION Any downward CG flash usually starts with an initial breakdown which gives birth to a leader propagating toward the ground. The return stroke is the current wave that is produced when the leader and one of the resulting upward connecting leaders manage to connect creating a conductive path between the cloud and the ground. The return stroke then propagates upward from the ground as a current wave draining all the electrical charges deposited in the ionized channel to the charged regions in the thundercloud. Because the electrification process leads to the production of both positive and negative charges in the thundercloud, the current flowing in the return stroke can be of both polarities. Then, depending on the type of flash this sequence of leader/return stroke can occur several times during the same flash like for-CG flashes with multiple connections to the ground either along the same ionized channel or/and along new channels, whereas it generally happens only once in +CG flashes.
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In this paper we present a performance analysis of the European lightning location system EUCLID for cloud-to ground flashes/strokes in terms of location accuracy (LA), detection efficiency (DE) and peak current estimation. The performance analysis is based on ground truth data from direct lightning current measurements at the Gaisberg Tower (GBT) and data from E-field and video recordings. The E-field and video recordings were collected in three different regions in Europe, namely in Austria, Belgium and France. The analysis shows a significant improvement of the LA of the EUCLID network over the past 7 years. Currently, the median LA is in the range of 100 m in the center of the network and better than 500 m within the majority of the network. The observed DE in Austria and Belgium is similar, yet a slightly lower DE is determined in a particular region in France, due to malfunctioning of a relevant lightning location sensor during the time of observation. The overall accuracy of the lightning location system (LLS) peak current estimation for subsequent strokes is reasonable keeping in mind that the LLS-estimated peak currents are determined from the radiated electromagnetic fields, assuming a constant return stroke speed. The results presented in this paper can be used to estimate the performance of the EUCLID network related to cloud-to-ground flashes/strokes for regions with similar sensor baselines and sensor technology.
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The Lightning Imaging Sensor (LIS) that was on board the Tropical Rainfall Measuring Mission (TRMM) satellite captured optical emissions produced by lightning. In this work, we quantify and evaluate the LIS performance characteristics at both the pixel level of LIS events and contiguous clusters of events known as groups during a recent 2-yr period. Differences in the detection threshold among the four quadrants in the LIS pixel array produce small but meaningful differences in their optical characteristics. In particular, one LIS quadrant (Q1, X ≥ 64; Y ≥ 64) detects 15%–20% more lightning events than the others because of a lower detection threshold. Sensitivity decreases radially from the center of the LIS array to the edges because of sensor optics. The observed falloff behavior is larger on orbit than was measured during the prelaunch laboratory calibration and is likely linked to changes in cloud scattering pathlength with instrument viewing angle. Also, a two-season comparison with the U.S. National Lightning Detection Network (NLDN) has uncovered a 5–7-km north–south LIS location offset that changes sign because of periodic TRMM yaw maneuvers. LIS groups and flashes that had any temporally and spatially corresponding NLDN reports (i.e., NLDN reported the radio signals from the same group and/or from other groups in the same flash) tended to be spatially larger and last longer (only for flashes) than the overall population of groups/flashes.
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The problem of inferring the location and time of occurrence of a very high frequency (VHF) lightning source emission from Lightning Mapping Array (LMA) network time-of-arrival (TOA) measurements is closely examined in order to clarify the cause of retrieval errors and to determine how best to mitigate these errors. With regard to this inverse problem, the previous literature lacks a comprehensive discussion of the associated forward problem. Hence, the forward problem is analyzed in this study to better clarify why retrieval errors increase with increasing source horizontal range and/or decreasing source altitude. Further insight is obtained by performing carefully designed Monte Carlo inversion simulations that provide specific retrieval error plots, which in turn lead to clear recommendations for mitigating retrieval errors. Based on all of the numerical results, the following strategies are recommended formitigating retrieval errors (when possible, and without obstructing the line of sight): expand the horizontal extent of the LMA network, maximize the vertical sensor baseline by using mountainous terrain if available, and improve TOA measurement timing accuracy.Adding sensors to the network is relatively ineffective, unless of course the addition of sensors expands the horizontal extent and/or vertical baseline of the network. It is also shown how the standard retrieval method can be generalized by considering, in addition to the regular (unpolarized) point VHF source, the polarized transient very low frequency/low frequency (VLF/LF) electric point dipole source. Multiple observations (i.e., VHF arrival time and power, and VLF/LF arrival time and electric field amplitude) are simultaneously implemented into the new generalized mathematical framework, and the potential benefits are indicated.
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This study documents the composition, morphology, and motion of extreme optical lightning flashes observed by the Lightning Imaging Sensor (LIS). The furthest separation of LIS events (groups) in any flash is 135 km (89 km), the flash with the largest footprint had an illuminated area of 10,604 km2, and the most dendritic flash has 234 visible branches. The longest duration convective LIS flash lasted 28 s, and is over-grouped and not physical. The longest duration convective-to-stratiform propagating flash lasted 7.4 s while the longest duration entirely stratiform flash lasted 4.3 s. The longest series of nearly-consecutive groups in time lasted 242 ms. The most radiant recorded LIS group (i.e., “superbolt”) is 735x more radiant than the average group. Factors that impact these optical measures of flash morphology and evolution are discussed. While it is apparent that LIS can record the horizontal development of the lightning channel in some cases, radiative transfer within the cloud limits the flash extent and level of detail measured from orbit. These analyses nonetheless suggest that lightning imagers such as LIS and GLM can complement ground-based lightning locating systems for studying physical lightning phenomena across large geospatial domains.
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This study evaluates the performance of the operational and reprocessed Global Lightning Dataset 360 (GLD360) data relative to the Tropical Rainfall Measurement Mission (TRMM) Lightning Imaging Sensor (LIS) during 2012-14. The analysis compares ground- and space-based lightning observations to better characterize the pre- and post-upgrade GLD360. The reprocessed, post-upgrade data increases the fraction of LIS flashes detected by the GLD360 (i.e., relative Detection Efficiency; DE). The relative DE improves during each year in every region, and year over year improvement appears in both datasets. The reprocessed relative DE exceeds 40% throughout large portions of the study domain with relative maxima over the western Atlantic, eastern Pacific, and the Gulf of Mexico. The upgrade results in shorter distances between matched LIS and GLD360 locations, indicating improved location accuracy. On average, the matched LIS flashes last longer (18.6 ms) and are larger (379.3 km2) than the unmatched LIS fla...
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This work evaluates how clouds evolve to thunderstorms in terms of microphysical characteristics and produces the first intracloud (IC) and cloud-to-ground (CG) lightning flashes. Observations of 46 compact isolated thunderstorms during the 2011/2012 spring-summer in Southeast Brazil with the X-band polarimetric radar and two- and three-dimensional Lightning Location Systems demonstrated key parameters in a cloud's vertical structure that produce the initial electrification and lightning activity. The majority (98 %) of the first CG flashes were preceded (by approximately 6 min) by intracloud (IC) lightning. The most important aspect of the observations going into this paper, which came originally from the visual examination of a large number of thunderstorms, is that an initial positive differential reflectivity (ZDR) (associated with supercooled raindrops) evolved to reduced ZDR (and even negative values) in the cloud layer between 0° and to -15 °C before and during the time of the initial lightning, suggesting evolution from supercooled raindrops to frozen particles promoting the formation of the conical graupel. An enhanced negative specific differential phase (KDP) (down to -0.5 °km-1) in the glaciated layer (above -40 °C) was predominantly observed at the time of the first CG flash, indicating that ice crystals, such as plates and columns, were being vertically aligned by a strong electric field. These results demonstrate that the observations of ZDR evolution in the mixed layer and negative KDP in the upper levels of convective cores may provide useful information on thunderstorm vigor and lightning nowcasting.
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Historically, researchers explore the effectiveness of one lightning detection system with respect to another system; that is, the probability that system A detects a discharge given that system B detected the same discharge is estimated. Since no system detects all lightning, a more rigorous comparison should include the reverse process-that is, the probability that system B detects a discharge given that system A detected it. Further, the comparison should use the fundamental physical process detected by each system. Of particular interest is the comparison of ground-based radio frequency detectors with space-based optical detectors. Understanding these relationships is critical as the availability and use of lightning data, both ground based and space based, increases. As an example, this study uses Bayesian techniques to compare the effectiveness of the Earth Networks Total Lightning Network (ENTLN), a ground-based wideband network, and the Lightning Imaging Sensor (LIS), a space-based optical detector. This comparison is completed by matching LIS groups and ENTLN pulses, each of which correspond to stroke-type discharges. The comparison covers the period from 2009 to 2013 over several spatial domains. In 2013 LIS detected 52.0% of the discharges ENTLN reported within the LIS field of view globally and 53.2% near North America. Conversely, ENTLN detected 5.9% of the pulses detected by LIS globally and 26.9% near North America in 2013. Using these results in the Bayesian-based methodology outlined, the study finds that LIS detected 80.1% of discharges near North America in 2013, while ENTLN detected 40.1%.
Article
Lightning stroke data from both the World Wide Lightning Location Network (WWLLN) and the Earth Networks Total Lightning Network (ENTLN) were compared to lightning group data from the Lightning Imaging Sensor (LIS) from 1 January 2010 through 30 June 2011. The region of study, from 39 degrees S to 39 degrees N latitude, chosen based on the orbit of LIS, and 164 E east to 17 W longitude, chosen to approximate the possible Geostationary Lightning Mapper (GLM) longitude, was considered in its entirety and then divided into geographical subregions. Over this 18-month time period, WWLLN had an 11.0% entire region, 13.2% North American, 6.2% South American, 16.4% Atlantic Ocean, and 18.9% Pacific Ocean coincidence percent (CP) value. The ENTLN CP values were 28.5%, 63.3%, 2.2%, 3.0%, and 2.5%, respectively. During the 18 months, WWLLN CP values remained rather consistent but low and often higher over ocean than land; ENTLN CP values showed large spatial and temporal variability. With both networks, North America had less variability during summer months than winter months and higher CP values during winter months than summer months. The highest ENTLN CP values were found in the southeastern United States, especially in a semicircle that extended from central Oklahoma, through Texas, along the northern Gulf of Mexico, across southern Florida, and along the U.S. East Coast. There was no significant change in CP values over time; the lowest monthly North American ENTLN CP value was found in June 2011 at 48.1%, the last month analyzed. These findings are consistent with most ENTLN sensors being located in the United States.