In this paper we present an analysis of a large dataset of lightning and
polarimetric weather radar data collected in the course of a lightning
measurement campaign that took place in the summer of 2017 in the area
surrounding Säntis, in the northeastern part of Switzerland.
For this campaign and for the first time in the Alps, a lightning mapping
array (LMA) was deployed. The main objective of the campaign was to study the
atmospheric conditions leading to lightning production with a particular focus
on the lightning discharges generated due to the presence of the 124 m
tall Säntis telecommunications tower. In this paper we relate LMA very high frequency
(VHF)
sources data with co-located radar data in order to characterise the main
features (location, timing, polarimetric signatures, etc.) of both the
flash origin and its propagation path. We provide this type of analysis
first for all of the data and then we separate the datasets into intra-cloud
and cloud-to-ground flashes (and within this category positive and negative
flashes) and also upward lightning. We show that polarimetric weather radar
data can be helpful in determining regions where lightning is more likely to
occur but that lightning climatology and/or knowledge of the orography and
man-made structures is also relevant.
Introduction
The first lightning mapping arrays (LMAs) were introduced in South Africa by
and .
They have gradually experienced significant improvements both in terms of
software and hardware and in the understanding of their limitations
e.g., and they
have become a fundamental tool in the lightning research community. Networks
have been deployed or are currently operational in various locations in the
USA and Europe, either on a permanent basis e.g.
or in the context of specific measurement campaigns
e.g..
By coupling LMA data with information obtained from polarimetric weather radar,
one can obtain valuable information about the type of precipitating system
that produced the lightning activity and the sort of environment where the
flashes propagate. In particular, polarimetric weather radars can inform us of
the dominant hydrometeor type in the region where the flash propagates.
Numerous studies using both LMA and polarimetric weather radar data have been
presented in the past, although most of them were discussing data from
individual storms or types of storms. For example, in the context of the
Thunderstorm Electrification and Lightning Experiment (TELEX) measurement
campaign in US planes, , several case
studies were published about, for example, observations of a multicell storm
, a small mesoscale convective system
or of the presence of a lightning ring in a
supercell storm . Within the context of
another measurement campaign in the US planes, the Severe Thunderstorm
Electrification and Precipitation Study (STEPS)
, observations were presented about storms
with normal and inverted polarity . More
recently, and
examined lightning-producing snow storms.
Some well-known polarimetric signatures of electrification processes, have
been discussed in the literature over the course of the years. For example, it
is widely reported that strong electric fields may align ice particles,
resulting in negative values of the differential reflectivity
Zdr and specific differential phase
Kdpe.g..
Other authors have observed that the presence of a
Zdr column is an indicator of a strong updraft
, which has been repeatedly reported to
favour lightning activity . Hence, the
presence of a Zdr column would be an indirect
indicator of possible lightning activity. There is also considerable evidence
that the presence of large quantities of graupel (retrievable with
polarimetric weather radars) in an environment with supercooled water leads
to the production of lightning through non-inductive charging
e.g..
Other studies presented relevant features of lightning activity extracted
from large datasets of LMA data, but they did not provide a direct connection
with the precipitation regime as observed by polarimetric radars. For
example, examined the spatio-temporal characteristics
of 29 000 flashes in the northeast of the Iberian Peninsula.
used a large dataset obtained by the São
Paolo LMA to construct a climatology of the diurnal variability of lightning
activity in the area. did use a large
dataset of storms data from four different LMA networks in the USA and the 3-D
mosaic of reflectivity from the WSR88D network to determine the environmental
characteristics affecting the electrical behaviour of storms. The authors
essentially focused on the vertical profile of reflectivity of the convective
storms. Another notable study from
establishes relationships between the vertical profiles of polarimetric data
obtained from an X-band Doppler polarimetric weather radar and the flash
density.
This paper reports on a measurement campaign that took place in the area
around Säntis, in the northeastern part of Switzerland, during
the summer of 2017. Within this campaign, and for the first time in the Alps,
a lightning mapping array (LMA) was deployed. The main objective of the
campaign was to study the atmospheric conditions leading to lightning
discharges generated due to the presence of the 124 m tall Säntis
telecommunications tower . In the course of the
campaign, a sufficient amount of data was collected to allow a more general
analysis of the atmospheric conditions leading to lightning generation and
propagation. In this respect, LMAs offer a unique dataset since they provide
3-D information of the discharge path, including channels within the cloud,
with acceptable temporal and spatial precision.
In this study we use a relatively large dataset of LMA data (more than 12 000
flashes collected over 8 different days) and a nearby operational C-band
Doppler polarimetric weather radar to determine the most likely precipitation
conditions for both flash generation and flash propagation. The study makes
use of the basic polarimetric variables, as well as the derived hydrometeor
classification. Moreover, for the first time, we go one step further and
we apply a technique that allows us to obtain semi-quantitative information
on the composition of the precipitating system at sub-radar resolution volume
scale. We will provide a general analysis of all the LMA data collected and
then categorise them according to whether they produced
cloud-to-ground (CG) lightning or not (and according to the CG flash
polarity) as well as whether they produced upward lightning.
LMAs require direct line-of-sight to operate and, therefore, as a general
rule, they do not provide information from the lowest layer of the
atmosphere. Hence, they are not capable of directly sensing CG flashes.
Indirect information of flashes reaching the ground can be obtained by
observing the presence of stepped leaders, i.e. sets of very high frequency (VHF) sources
propagating downwards. Dart leaders, on the other hand, are poorly traced
because they propagate more directly to the ground. Networks of low-frequency
sensors, such as the EUCLID network in Europe, on the other hand, offer a
high probability of detection of CG lightning data with good location
accuracy. Their detection capability of intra-cloud (IC) lightning,
however, is much more limited. It is, therefore, clear that the data offered by
both sensors are largely complementary. In this paper we have used data from
both networks to distinguish those flashes detected by the LMA that have
produced lightning strokes to the ground according to the EUCLID network from
those that have not. Moreover, since the EUCLID network provides information
about the polarity of the lightning stroke, we can further distinguish the
LMA flashes causing positive CG strokes and those causing negative CG
strokes.
Upward lightning is a source of continuous interest in the research
community. This type of lightning is generally associated with the existence
of tall structures and with the global expansion of wind farms its
incidence is likely to increase in the future . However, a
significant number of this type of flashes is not detected by conventional
lightning detection systems since they might contain only an initial
continuous current with neither superimposed pulses nor return strokes
e.g..
Moreover, another significant portion is actually detected but misclassified
as IC . In this study, we have collected all
flashes detected by the LMA with the first VHF source located in the liquid
or mixed-phase regions of the precipitating system, according to the
radar-based hydrometeor classification. Although detectability issues may not
be ruled out, especially in such complex orography, the flashes thus
collected are more likely to correspond to genuine upward lightning, and hence
they deserve a separate analysis of their propagation conditions.
Summarising, the main goals of this study are as follows:
To determine whether and which polarimetric signatures can inform us of the
likelihood of lightning activity;
To find out whether polarimetric signatures can be used to distinguish
between precipitating conditions producing mostly IC lightning activity from
those producing CG activity;
To study, from a statistical perspective, the environmental conditions leading to upward lightning.
The paper is organised as follows: Sect. 2 provides an overview of the
Säntis measurement campaign, the instrumentation used and the data-processing methods. Section 3 contains a detailed data analysis. Firstly, the
data availability and coverage is discussed, followed by a general overview
of all the data analysed, and finally the data are classified into different
categories: intra-cloud, cloud-to-ground (positive or negative), and flashes
with an origin in the mixed-phase or liquid-phase layers. General conclusions and
recommendations are discussed in Sect. 4.
The Säntis Measurement Campaign
The Säntis measurement campaign was a joint venture between the
Electromagnetic Compatibility Laboratory (EMC LAB) of the Swiss Federal
Institute of Technology in Lausanne (EPFL), the Institute for Information and
Communication Technologies of the University of Applied Sciences of Western
Switzerland (HEIG-VD), the Lightning Research Group (LRG) of the Technical
University of Catalonia, the Meteorological Service of Catalonia (Meteo.cat)
and the Radar Satellite and Nowcasting Division of the Federal Office of
Meteorology and Climatology (MeteoSwiss). The campaign took place in the summer
of 2017. The main objective of the campaign was to study the atmospheric
conditions leading to lightning production in the vicinity of the Säntis
telecommunications tower, with a particular focus on the upward lightning
discharges generated by the tower itself. The 124 m tall
telecommunications tower is situated on top of Säntis
(47.2429∘ N, 9.3393∘ E, 2502 ma.m.s.l.), in St. Gallen in the northeast of Switzerland. The main instruments
of the campaign were in situ measurements on the tower, a lightning mapping
array (LMA) network and a polarimetric Doppler weather radar. The area
covered by the campaign and the location of the instrumentation can be seen
in Fig. . In the following, a brief description of the
instrumentation used during the campaign is provided.
Lightning measurementsLightning measurements at the Säntis tower
Since May 2010, EPFL and HEIG-VD operate instrumentation to detect and
characterise lightning strikes on the Säntis tower. Lightning currents at
the tower are measured using two sets of Rogowski coils and multi-gap B-dot
sensors located at two different heights along the tower (82 and 24 m) . The analogue outputs are relayed
to a digitising system by means of optical fiber links. A PXI platform
digitises and records the measured waveforms at a sampling rate of 50 Mega Samples s-1. The lightning current is recorded over a 2.4 s time
with a pre-trigger delay of 960 ms. The system is GPS equipped and
allows remote maintenance, monitoring and control via the internet.
(a) Approximate extent of the maximum area covered by the LMA
(orange polygon). The yellow area shows the region with more comprehensive
coverage. Radar positions are marked by red dots, while the position of the
LMA sensors is marked by yellow dots. The Säntis tower is marked by a green
dot. (b) Zoom over the best-covered area.
Since 15 July 2016, an EFM-100 field mill is installed 85 m from the
tower to measure the electrostatic field. The system can detect lightning
activity up to distances of about 40 km from the tower
. In addition to this, an electric field measuring
system comprised of a flat plate antenna and an analogue integrator with an
overall operating frequency band between 30 Hz and 2 MHz is
installed 14.7 km away from the Säntis tower
.
LRG owns and operates a 3-D LMA installed on a permanent basis at the lower
part of the Ebro Valley, in Catalonia . The
LMA network there consists of 12 VHF (60–66 MHz) sensors, some of
which are mobile. For this campaign, 6 sensors were moved temporarily to
locations in the area surrounding Säntis (see Table
and Fig. for the locations). The network was
operational from 29 June to 15 August 2017, although not all the sensors were
operating during the entire period. The selection of the locations was made
taking into consideration practical installation aspects such as
accessibility, security, and reliable access to AC power and communication, as
well as considerations of the magnitude of the local noise within the
frequency band and the distance to the Säntis tower. In the end, the sensors
were located in the vicinity of mobile phone base stations belonging to
Swisscom and Swisscom Broadcast, which in the cases of the Gonten, Schwägalp
and Säntis stations resulted in an increased noise level coming from the
on-site telecommunications equipment. The Säntis station had the added
challenge of being located indoors.
Each sensor measures the arrival times of the impulsive VHF radiation sources
with an accuracy of 50 ns using a PC-based digitiser card coupled to a
GPS receiver. The received signal is digitised and the peaks (within a 80 µs window) are time-tagged using the time derived from GPS
receivers, which provide a timing pulse once per second
. The timed data are stored on-site as well
as transmitted over wireless modems to a central site for real time analysis
and display. If at least four stations are able to measure the time of arrival
of the radiation from a particular impulsive event, the three-dimensional
position of the source region can be estimated since this is described by
four unknowns (the three position coordinates, x, y, z,
plus the exact time when the discharge occurred t). A redundancy in
the number of stations observing the event allows for better accuracy and
helps in filtering out noise spikes from other source types. After
post-processing, individual sources deemed to be part of the same flash are
clustered together and assigned a unique ID number
. If the data point is not identified as
belonging to any flash, it is assigned the ID number 0. A file with data from
all the sources is generated each day. In this campaign, in order to account
for the increased noisiness of the data and the poor visibility, a minimum of
10 detected VHF sources is required for a flash to be accepted.
Since the detection of the lightning strike requires direct line of sight of
the source, LMAs observe mainly IC activity, mostly from negative leaders
moving through regions of positive charge. However, weaker sources from
positive leaders moving through negative charge regions are often detected.
CG activity is often detected indirectly from stepped negative leaders or,
less often, from negative dart leaders and sometimes positive leaders as
well.
EUCLID lightning detection network
Operational detection of CG and IC activity is performed by the European
Cooperation for Lightning Detection Network (EUCLID)
. The network uses various Vaisala sensors that
detect low-frequency (1–350 kHz) electromagnetic signals and GPS
receivers providing the time. The raw data are sent to a centralised location
where they are processed and for each lightning strike the time of event,
latitude and longitude of the impact point, and the current intensity and
polarity are recorded. The EUCLID network has a high CG detection efficiency
(on the order of 95 %) but a reduced IC detection efficiency, typically on
the order of 50 %. The median accuracy is on the order of 100 m,
although it may be worse in mountainous areas
. The data available at MeteoSwiss is
provided by Météorage and has a time resolution of 0.1 s.
Polarimetric weather radar data
MeteoSwiss owns and operates a network of five C-band Doppler polarimetric
weather radars. The network was recently renewed within the project Rad4Alp,
which was concluded in 2016 . The five systems have
identical specifications and modes of operation. The scanning strategy
consists of 20 horizontal scans with elevations ranging from
-0.2 to 40∘ repeated every 5 min. The
elevations are inter-leaved, every 2.5 min a half-volume of 10
elevations from top to bottom is concluded. A very short pulse of 0.5 µs is used to obtain data with a range resolution of 83.3 m
with angular resolution of 1∘. In-phase and quadrature components of a signal (IQ) data are processed on-site
using standard techniques e.g. to obtain the
basic polarimetric moments, i.e. reflectivity (horizontal
Zh and vertical Zv),
differential reflectivity (Zdr), co-polar
correlation coefficient (ρhv) and raw co-polar
differential phase (ψdp), as well as Doppler
moments. These basic moments are transmitted to a central server. The
operational data processing involves a clutter detection using a
sophisticated decision tree filter (DT-filter) and a reduction of the
resolution to 500 m by averaging six consecutive gates (only the
clutter-free ones). From the low-resolution polarimetric moments all
subsequent products are generated. For the measurement campaign, data from
the Albis radar (47.2843∘ N 8.5120∘ E, 938 ma.m.s.l.),
situated 63 km west of the Säntis tower (see Fig. ) were used.
Basic radar data processing
A specific non-operational processing was applied to radar data obtained in
real time during the campaign. The processing was performed using the
Python-based open-source software Pyrad/Py-ART
. The first step was calculating the
signal-to-noise ratio (SNR) of the horizontal channel using the
estimated receiver noise from a high elevation angle (40 or
35∘). The SNR, together with the ratio between
the horizontal and vertical channel receiver noise were used to minimise the
effect of noise on ρhv. Clutter identification was performed using a
simple DT-filter based on the textures of Zh,
Zdr, ρhv, and
ψdp and the value of
ρhv. Range gates identified as
clutter-contaminated were removed from the analysis.
ψdp was processed by first filtering out range
gates with an SNR below 10 dB to reduce the influence of phase
noise and then applying a double window moving median filter. The length of
the windows was 1000 and 3000 m, respectively. The short window was
applied in regions of high reflectivity (above 40 dBZ) while the long
window was used elsewhere. The filtered differential phase
(ϕdp) was used to compute the specific
attenuation Ah using the ZPHI algorithm
.
Ah was estimated up to the freezing level height
as determined by the temperature provided by the closest available run of the
Numerical Weather Prediction (NWP) model COSMO-1 (see
http://www.cosmo-model.org/, last access: 21 May 2019). From Ah, the
specific differential attenuation Adp was derived.
By integrating Ah (Adp)
attenuation, the path integrated (differential) attenuation was obtained and
this quantity was added to the (differential) reflectivity in order to
correct for the precipitation-induced attenuation. In parallel to the
attenuation correction, the specific differential phase
(Kdp) was derived from
ϕdp using the method described in
.
Kdp, Zh,
Zdr, ρhv and the
temperature from the COSMO model were inputs of the semi-supervised
hydrometeor classification described by . The
hydrometeor classification provides the following outputs: aggregates (AG),
ice crystals (CR), light rain (LR), rimed particles (RP), rain (RN),
vertically oriented ice crystals (VI), wet snow (WS), melting hail (MH), ice
hail and high density graupel (IH), and no classification (no valid radar data, NC). An example of the output can be found in Fig. 11 of the aforementioned paper.
It must be mentioned here that the category vertically oriented ice crystals
is often misclassified. It is highly dependent on the
Zdr value, with the assumption of
Zdr being negative when the particles are
vertically oriented. Unfortunately, at the C-band large values of
Adp are not uncommon. Although
Adp is corrected for, insufficient correction
typically results in negative Zdr values at the
far end of the ray. Therefore, the vertically oriented ice crystals category
may contain a large proportion of regularly oriented ice crystals situated at
range gates far away from the radar.
In addition to the dominant hydrometeor class, the MeteoSwiss hydrometeor
classification algorithm also provides an estimation of the entropy
. Such a quantity provides information about whether
there is a clearly dominant hydrometeor type within the radar resolution volume (entropy 0) or if it is a heterogeneous mixture without any dominant
hydrometeor type (entropy 1). Moreover, using the technique described in , we are able to extract
semi-quantitative information of the proportion of each hydrometeor type
contained in the resolution volume.
At the end of the processing, high-resolution clutter-free volumes of
attenuation-corrected Zh and
Zdr, ρhv,
Kdp, the model air temperature, the dominant
hydrometeor type, the entropy, and the proportion of each hydrometeor type at
each range gate were obtained. These parameters were used in the subsequent
analysis.
Radar data along lightning trajectories
Within the radar data processing tool Pyrad, a lightning trajectory function
has been implemented. This function reads the daily produced LMA lightning
data and determines from them the time of the first and last VHF source
detection. It then loops over all the radar volumes within this time interval
and assigns to each VHF source the value of the polarimetric parameter in the
range gate closest (both in time and space) to the source location. For each
radar variable a file is generated containing the flash source time, the
flash number, the value at the flash position and the mean, minimum and maximum
of the cube formed by the neighbours.
Association of LMA flashes to EUCLID CG strokes
A two-step algorithm associates LMA flashes to corresponding EUCLID CG
strokes. The first step looks for EUCLID CG strokes occurring during the
propagation time of each LMA flash. A 0.1 s tolerance is added to the
start and the end of the LMA flash since this is the time resolution of the
EUCLID data available at MeteoSwiss. If EUCLID strokes have been found within
the LMA flash duration, a second step looks at whether these EUCLID strokes are
within the area covered by the LMA flash. The LMA flash area is defined as
the minimum oriented rectangle that contains all the VHF sources of the flash
projected to the ground. The minimum area of this rectangle is set to 25 km2,
which is considered a reasonable area to look for in case of
flashes with reduced horizontal extent. A scaling factor of 1.2 is applied to
each dimension of the rectangle if its area is larger than the minimum area
to account for the fact that the flash may still propagate horizontally below
the LMA detectable altitude. If EUCLID strokes are present within the LMA
flash area, the LMA flash data are saved in a separate file. This process can
be performed to associate LMA flashes to all, only positive or only negative CG EUCLID
strokes. A separate process gets the complementary data, i.e. LMA flashes
without associated CG EUCLID strokes, by comparing the file with all the
flash data with the resultant filtered data file.
Data analysisData availability and coverage
The LMA was installed in the Säntis area between 29 June and 15 August 2017.
On half of the days that the campaign lasted (24 out of 48) some lightning
activity was registered in the area covered by the LMA of the EUCLID network.
Of these, on 15 d lightning activity was registered within 2 km from the
Säntis tower. On 10 of these, direct strikes to the tower were also registered
by the in situ sensors. According to the operational MeteoSwiss
probability of hail (POH) algorithm, hail with a probability above 90 % was
present somewhere within the domain on 11 d. On 6 of these days hail was
detected within 20 km of the Säntis tower. Figure provides an
overview of the relevant events during the campaign. For our analysis, we
have focused on events that produced lightning in the immediate proximity of
the tower. Of these, 22, 24 and 25 July were excluded because fewer than five LMA
stations were operational. The data from 5, 8, 9 and 15 August were excluded as well
because, although enough stations were operating, for reasons still under
investigation the data quality was poor. Some characteristics of the events
with lightning in the vicinity of the Säntis tower can be seen in Table .
During the 8 d where LMA data were analysed, a total of
1 586 394 VHF sources, corresponding to 12 062 flashes, were detected (i.e. 132
VHF sources per flash). Almost half of them were detected on the first of
August alone.
Analysed days and some of their general characteristics.
Days examinedLMALMALMASäntisCG-CG+CGbipolar% +CGNon-solidflashessourcesCGorigin29 Jun 2017625041 721134442204.53130 Jun 201751155285 291030255016.71310 Jul 201751339171 7433322711634.44014 Jul 2017526320 89711082020.02018 Jul 20175635115 617324196125.02419 Jul 201752250202 343716454119972.62722 Jul 20174NANA0NANANANANANA24 Jul 20173NANA0NANANANANANA25 Jul 20173NANA0NANANANANANA30 Jul 20176960138 445016142012.5211 Aug 201765210610 33727655242985740.0655 Aug 20175NANA1NANANANANANA8 Aug 20175NANA1NANANANANANA9 Aug 20175NANA1NANANANANANA15 Aug 20175NANA1NANANANANANA
NA: not available
Overview of relevant events within the LMA reduced domain occurred
during the 2017 campaign. Hail probability is derived from the POH radar
product. Occurrence of relevant events is marked in green.
Position of detected VHF sources for the days examined. (a, c) All
VHF sources. (b, d) Only the first sources of each flash. (a, b) All
data. (c, d) Flashes with associated EUCLID CG strokes.
Figure a plots the position of all the LMA
detected VHF sources during the days analysed. Each cross in the plot is a
detected LMA VHF source. The data have been colour-coded by estimated altitude
with lowest altitude in dark blue. The lowest-altitude VHF sources are
plotted on top. As the plot shows, the data are distributed over a broad
surface oriented from southwest to northeast, which was the moving
direction of most of the convective cells during the period analysed. It is
also apparent that the coverage of the LMA network is uneven. There is a
section in the south, oriented from southwest to northeast, where the
minimum altitude at which data are detected is much higher due to blockage
from the Alps. Likewise, there is a gradual loss of detectability the further
one moves away from the centre of the network. Since the number of
operational sensors varied between five and six during the days examined and the
malfunctioning sensor was not always the same, the actual detectability
varies between days. Nevertheless, the area surrounding Säntis
appears to be reasonably well covered. Figure b plots the position of the first LMA detected VHF source of each flash
during the days analysed. It can be seen that they have an uneven
distribution with a band with high density of flashes to the south and a
second band with a lower flash density further north. However, this seems to
be associated more to the path of individual storms than to specific
detectability issues.
General data analysis
This section discusses the bluish areas of the histograms in Figs. – that provide a general overview of all the
data sources collected during the days analysed. It should be noticed that in
all the histograms presented in this paper, the values outside of the
histogram range are added to the bins at the extremes, e.g. the last bin in
the histograms in Fig. a include all the
values above 900 ms.
Distribution of the LMA flashes for all days analysed: (a) time of occurrence, (b) duration, (c) 2-D projection area over the
day for all days analysed. Bluish area: all data. Greenish area: flashes without
associated EUCLID CG strokes. Reddish area: flashes with associated EUCLID CG
strokes. Note that the values outside of the histogram range are added to the
bins at the extremes.
Concerning the distribution of the flashes over the day (see Fig. a), they are concentrated in the
afternoon. The first flashes are detected at 10:00 UTC and the last at
21:00 UTC,
with a clear peak at 16:00 UTC. Obviously, with so few events, the distribution
is highly dependent on the severity and time of occurrence of the individual
events but it seems probable that in the study area there is a diurnal cycle
with a peak at mid-afternoon during the summer months. Figure b shows the distribution of the
duration of the flashes. For our purposes we define the flash duration as the
time difference between the first and the last VHF source identified as
belonging to a single flash. As it can be seen it has an exponential
distribution. A total of 51 % of flashes have a duration of up to 200 ms. On the
other hand, 3 % of flashes have a duration of more than 900 ms. The
flash area (see Fig. bottom panel) also follows a
marked exponential distribution with more than half (58 %) covering
an area of less than 100 km2. There are few flashes though (0.4 %)
that cover an area of more than 1900 km2.
Figure shows histograms of the power of the VHF sources
detected by the LMA. In Fig. a, all sources are shown while in Fig. b only the first detected source for each flash (which we consider a
proxy for flash origin) is shown. The histogram exhibits a Gaussian-like
shape with median of 18.5 dBm. Detected sources had power ranging from
-16 to 46 dBm. The sources power at the origin also has a Gaussian-like
shape but has increased power. The median in this case is 20.5 dBm.
Histogram of VHF sources power for all days analysed. (a) All
sources. (b) Only the first sources of each flash. Bluish area: all data. Greenish area:
flashes without associated EUCLID CG strokes. Reddish area: flashes with
associated EUCLID CG strokes. Note that the values outside of the histogram
range are added to the bins at the extremes.
Number of VHF sources (flashes) detected and percentage of each
dominant hydrometeor type at the location of each flash
type.
Flash typeNumberRPIHAGCR (VI)WSMHRN (LR)NCAll all sources1 586 39454.626.911.71.7 (72)1.80.41.6 (23)1.4All at origin12 06254.229.59.32.0 (63)0.80.20.9 (34)3.1IC all sources1 299 82155.125.912.01.9 (70)1.80.31.5 (24)1.6IC at origin10 89254.928.49.52.0 (63)0.80.20.9 (38)3.3CG all sources279 19952.231.310.61.0 (86)1.90.52.1 (16)0.5CG at origin108547.241.47.00.8 (67)1.30.31.3 (7)0.7-CG all sources178 10751.532.99.60.8 (82)2.20.51.9 (13)0.5-CG at origin71345.744.36.50.8 (67)1.10.10.7 (20)0.7+CG all sources128 44651.027.713.21.1 (91)1.60.52.4 (18)0.5+CG at origin44550.137.17.60.7 (67)1.40.52.0 (0.0)0.7NSP all sources31 65148.410.717.62.6 (81)8.01.49.7 (20.4)1.7NSP at origin2410.00.00.00.0 (0.0)41.512.046.5 (34)0.0MP all sources12 65549.75.418.12.7 (77)12.51.29.1 (15)1.4MP at origin1000.00.00.00.0 (0.0)100.00.00.0 (0.0)0.0LP all sources18 99647.514.317.32.5 (85)4.91.510.1 (24)1.9LP at origin1410.00.00.00.0 (0.0)0.020.679.4 (34)0.0
Figure a and b show histograms of the altitude of the
VHF sources detected by the LMA. It can be seen that, whereas the altitude
histogram of the flash origin has a Gaussian-like shape with a mode of 8600 ma.m.s.l.
and median of 8200 ma.m.s.l. (Fig. b), when all sources are considered the histogram has a bimodal
shape with two distinct peaks: the main one at 7400 ma.m.s.l. and a
secondary one at 4000 ma.m.s.l. (Fig. a). This suggests that most of the IC lightning activity is generated at
the higher part of the clouds with the majority of the flashes roughly propagating
horizontally but a significant proportion descending into lower
layers. This observation is further confirmed by Fig. c and d in which the temperature at the location of each lightning
source, obtained from the COSMO-1 NWP model, can be seen. Indeed, the vast
majority of the sources are detected at freezing temperatures. The median
temperature for all sources is -20∘C, while the lightning origin
is at -25∘C.
Histogram during all days analysed of (a) VHF sources
altitude. (b) Only the first sources of each flash altitude. (c) The model air temperature of all
sources. (d) The first source's model air
temperature. Bluish area: all data. Greenish area: flashes without associated EUCLID CG
strokes. Reddish area: flashes with associated EUCLID CG strokes. Note that the
values outside of the histogram range are added to the bins at the
extremes.
Histogram during all days analysed of, from top to bottom,
Zh, Zdr,
ρhv and Kdp. (a, c, e, g) All
sources. (b, d, f, h) The first source only. Bluish area: all data. Greenish area: flashes
without associated EUCLID CG strokes. Reddish area: flashes with associated EUCLID
CG strokes. Note that the values outside of the histogram range are added to
the bins at the extremes.
The reflectivity data (Fig. a and b) of all
sources show a bimodal distribution with a main peak at 41 dBZ and a
secondary peak at 25 dBZ. Interestingly, when looking only at the
first source the main peak is maintained (at 41.5 dBZ), but the
secondary peak is barely visible. It is worth noting that a similar
behaviour was observed when looking at the altitude of the VHF sources (Fig. ).
We think that this is due to the tendency of flashes
to preferentially propagate horizontally through layers with a high density of
charge. The 2-D histogram of altitude–reflectivity and the analysis of
individual storms (not shown) show that there are three areas with a higher density
of flashes. Indeed, most sources are concentrated in an area with roughly the
same altitude and reflectivity as the flash origin while two other less dense
preferential areas appear: one at roughly the same altitude but with lower
reflectivity and another with similar reflectivity values but at another
altitude. Our interpretation is that flashes are likely to either propagate
horizontally at similar altitudes to where they are generated, sometimes
extending beyond the convective core (hence the lower reflectivity), or move
to a lower layer within the convective core. The
Zdr data (upper-middle panels) exhibit a similar
Gaussian-like shape both when all sources are considered and when only the
first source is considered. In both cases the distribution is centred around
0 but with very long tails. ρhv data
(lower middle panels) have a log-normal shape with most values well above
0.99. The mode is 0.9990 both when considering all sources and when only
considering the first one. Kdp values (lowermost
panels) are centred at 0∘km-1, but they are noticeably
skewed towards positive values.
Histogram during all days analysed of, from top to bottom, the dominant
hydrometeor at the radar gate collocated with the VHF source position,
the hydrometeor-classification-derived entropy at the radar gate collocated with
the VHF source position and the number of hydrometeor types with a significant
presence at the radar gate collocated with the VHF source position. (a, c, e) All
sources. (b, d, f) The first source only. Bluish area: all data. Greenish area: flashes
without associated EUCLID CG strokes. Reddish area: flashes with associated EUCLID
CG strokes. Note that the values outside of the histogram range are added to
the bins at the extremes.
Figure a and b show histograms of the dominant
hydrometeor at the location of the VHF sources. This information is tabulated
in Table . As it can be seen, the large majority of the
sources are produced in areas of rimed particles or dry hail. When
considering only the first sources, the proportions of these species are
essentially maintained, with a slight increase in the solid hail proportion.
The other classes with significant VHF sources are dry snow and ice crystals.
A high percentage of ice crystals are labelled as vertically aligned ice
crystals, which is indicative that those are ice crystals situated at the far
end of the radar, i.e. high up in the atmosphere. Again, similar proportions
are encountered when examining only the first sources, but there is a decrease in
vertically aligned ice crystals, which may indicate that flashes are less
likely to originate at the very top of the cloud. The percentage of VHF
sources detected in the mixed-phase or liquid-phase layers (i.e. wet snow, melting
hail or rain) is marginal, a mere 3.8 %. A total of 94.9 % of the flashes detected
originated at the solid-phase region of the precipitating systems whereas
only 2.0 % originated in the mixed-phase or liquid-phase regions of the
precipitating systems. A total of 3.1 % have an origin in regions where no radar echo was
detected but from examining the location (not shown) it can be inferred that for
the most part they correspond to the solid-phase region.
Figure c and d show histograms of the entropy of
the hydrometeor classification at the location of the VHF sources. It is
evident from the graph that the entropy tends to be rather high, with values
on the order of 0.3 and 0.4 dominating the distribution and representing
62.4 % of all the VHF sources and 64 % of all the flash origins where radar
data were present. Indeed, when looking at how many hydrometeor types have a
significant presence within the radar gates collocated with VHF sources (more than 10 % contribution to the hydrometeor proportions) (see Fig. e and f), it turns out that in a large majority
of them there is more than one hydrometeor type and up to a maximum of 6.
A total of 69 % are composed of two hydrometeor types, while only 22 % contain one single
dominant hydrometeor. If looking at the flash origin only, the number of
gates containing only one hydrometeor type decreases further by one point
(21 %).
Two-dimensional histogram of the type of the most-dominant and second most-dominant
hydrometeor at the radar gate collocated with the VHF source position. From
top to bottom: all data, flashes without associated EUCLID CG strokes,
flashes with associated EUCLID CG strokes. (a, c, e) All VHF sources in the
flash. (b, d, f) Only the first VHF sources.
Figure a and b show 2-D histograms of the
most-dominant and second most-dominant hydrometeors. The most likely
combination of hydrometeors in the presence of VHF sources by far is a
combination of rimed particles as the most-dominant type and solid hail as the second most
common. The second most likely is the combination of solid hail as the most-dominant type and rimed particles as the second most common. The third is a
combination of rimed particles as the most dominant and aggregates as the second most
common, while the fourth is rimed particles as single dominant hydrometeor.
When focusing on the flash origin this ranking is essentially maintained but
the likelihood of a combination of rimed particles and aggregates decreases.
It seems clear from these results that lightning tends to originate in areas
with an important presence of rimed particles or solid hail.
Characteristics of the flashes without associated EUCLID cloud-to-ground strokes
Here we analyse the characteristics of flashes without associated EUCLID CG
strokes, which we use as a proxy for IC flashes. This section discusses the
greenish area of the histograms in Figs. to
. A total of 90.30 % of the total flashes (10 892) correspond to
this category. Those flashes contain 81.94 % of the total detected sources
(1 299 821). The fact that flashes without associated EUCLID CG strokes have
fewer sources per flash (119 compared to 132) may be an indicator that this
type of flash is more short-lived and has a simpler structure.
Since a very large proportion of flashes are IC flashes, their
characteristics do not differ significantly from the general analysis
performed in the previous subsection. The VHF source power distribution (see
Fig. ) is very similar. The VHF source altitude (Fig. ) and the reflectivity distributions (Fig. a)
have a more marked bimodality.
The distribution of the values of the hydrometeor classification (see Fig. a and b and Table ) is essentially
the same as when all data are considered. As is the case with all the data,
the entropy is quite high (see Fig. c and d),
and most of the radar gates where VHF sources are located contain more than
one hydrometeor type (see Fig. e and f). Rimed
particles or solid hailstones are present in most regions where the flashes
propagate (see Fig. c and d).
Characteristics of the flashes with associated EUCLID cloud-to-ground strokes
Here we analyse the characteristics of flashes that have associated EUCLID CG
strokes, referred to here as CG flashes. This section discusses the reddish area of the histograms in
Figs. to . This category
contains a total of 1085 flashes, which correspond to 9.0% of the total.
Those flashes contain 17.60 % of all the sources detected during the days
analysed (279 199). On average the CG flashes during the campaign contain 257
sources. This would suggest that those flashes have a more complex structure
than the IC flashes. Figure c and d show the
spatial distribution of all the VHF sources of these flashes (left) and the
first VHF source of each flash (right). The spatial distribution of all VHF
sources approximately covers the same area that was covered by all data.
However, the density of the flash origin is much lower and there are few
detections in the northeast band of lightning activity, suggesting that
individual storms have a varying ratio of CG to IC flashes. That is further
confirmed by looking at the time of occurrence of the flashes (see Fig. a), since the shape of the distribution
changes significantly. The flash duration distribution (Fig. b) does not follow an exponential
distribution anymore but has a mode of 350 ms, and a large number of
flashes (17 %) have a duration of more than 900 ms. The area covered
by the flashes (Fig. ) also tends to be
larger. Only 15 % of the flashes cover an area of less than 200 km2
and 3 % of the flashes cover an area of more than 1900 km2.
In terms of source power (Fig. ), CG flashes exhibit
similar characteristics to those of the global analysis. Their histogram again has
a Gaussian-like shape with the median a bit higher (19.5 dBm).
When only the first sources are considered the median is the same as in the
global analysis, 20.5 dBm. Regarding the altitude of the VHF sources,
there are remarkable differences (see Fig. a and b)
to the global data. When all sources are considered, the histogram exhibits
a Gaussian-like distribution but skewed towards lower altitudes with a median
of 7000 ma.m.s.l. and a mode of 7400 ma.m.s.l. When only
considering the origin of the flashes, the histogram has an almost
uniform-like distribution with a mode of 8700 ma.m.s.l. and median of 7900 ma.m.s.l.
There is a 300 m difference between the median of CG
flashes with respect to the global data, which may indicate that those flashes
are more likely to be generated at lower altitude. This is backed also by the
fact that the median temperature at the flash origin (Fig.
bottom right panel) is -25∘C compared to the -28∘C
of the global data.
In terms of distribution, the polarimetric variables show subtle differences
with respect to the global data (see Fig. ). When all
sources are considered, the secondary peak in the reflectivity distribution
is almost unnoticeable and the mode is lower (39 dBZ) and the median
higher, 36.5 dBZ. When only the origin is taken into account, both the median
and the mode are decisively larger (40 and 44 dBZ,
respectively). The Zdr distribution is similar but
with comparatively fatter tails. ρhv has
slightly lower median (0.996 both when all sources are considered and when
only the first source is considered). The Kdp
distribution is very similar but shifted towards higher values, particularly
for the source origin, where the median has moved to 0.15∘km-1.
Although the general distribution is maintained with respect to the global
data analysis, the proportions of each hydrometeor class are slightly
different (see Fig. a and b and Table ).
When considering all VHF sources in the solid phase, their
proportion decreases slightly but not dramatically. As would be expected, the
percentage of sources transiting through the rain medium is remarkably higher
with respect to IC flashes. When looking at the origin of the flashes, the
percentages of flashes originating in the solid phase decreases with respect
to the global data. It is interesting to notice that there is a marked
increase in flashes having their origin in solid hail regions and a decrease
in flashes produced in the dry snow or ice crystals regions with respect to
the global data. The percentage of VHF sources where hydrometeor
classification could not be performed is lower than in the global analysis,
which corroborates the statement that non-classified data are located mostly
at high altitude.
As was the case with the global data, the entropy of the hydrometeor
classification is rather high, with a large percentage of VHF sources located
in regions with entropy on the order of 0.3–0.4 (see Fig. c and d). Again, flashes are more likely to be
generated and propagate in areas where at least two hydrometeor types are
present in significant proportions (see Fig. e and f).
Figure e and f show 2-D histograms of the
most-dominant and second most-dominant hydrometeors for sources associated
with EUCLID CG strokes. When looking at all sources (Fig. e) the distribution is rather
similar to the global data. The main difference is that the combination of
solid hail as the most dominant and rimed particles as the second most dominant has a
comparatively higher weight. However, when looking at the flash origin (Fig. f) the mentioned combination
becomes the most likely.
LMA flashes stratified by associated positive and negative CG activity
In this subsection we further stratify the data into flashes associated with
negative EUCLID CG strokes (hereby -CG flashes) and flashes associated with
positive EUCLID CG strokes (hereby +CG flashes). This section discusses the
histograms presented in Figs. –. In those figures the greenish area of the histograms
correspond to -CG flashes while the reddish area of the histograms correspond to
+CG
flashes.
Distribution of the flashes for all days analysed: (a) time of
occurrence, (b) duration and (c) 2-D projection area over the day
for all days analysed. (d) Number of detected EUCLID CG strokes per
LMA flash. Bluish area: all flashes with associated EUCLID CG strokes. Greenish area:
flashes with associated EUCLID -CG strokes. Reddish area: flashes with associated
EUCLID +CG strokes. Note that the values outside of the histogram range are
added to the bins at the extremes.
Histogram during all days analysed of (a) VHF sources
altitude, (b) only the first sources of each flash altitude, (c) all sources model air temperature and (d) the first source's model air
temperature. Bluish area: all flashes with associated EUCLID CG strokes. Greenish area:
flashes with associated EUCLID -CG strokes. Reddish area: flashes with associated
EUCLID +CG strokes. Note that the values outside of the histogram range are
added to the bins at the extremes.
There are 713 -CG flashes and 445 +CG flashes detected in the dataset. It
should be noted that of the total CG flashes, 73 have both positive and
negative CG strokes. Although the existence of bipolar flashes has been
documented in the past, at this point we believe that this is mainly due to
the limitations in the technique used to stratify the flashes. The necessary
tolerance in time and space to associate multiple strokes into flashes may
have resulted in the misattribution of strokes for flashes that are very close in
time and/or space. In any case, the proportion of +CG flashes with respect to
the total number of CG flashes (41 %) is significantly higher than that
observed on the Säntis tower over a 2 year period (15 %)
. That is due to the fact that on 3 out
of the 8 analysed days (10 and 19 July and 1 August), the proportion of +CG
flashes is abnormally high (see Table ). The percentage of
+CG flashes on 19 July (72.6 %) is particularly noteworthy. On that day,
large swathes of terrain south of the Säntis tower were affected by hail
according to the POH algorithm. There was also extensive hail recorded on
1 August. A higher proportion of +CG flashes have been linked to severe
hail-bearing storms in past studies (see the introduction of
, for a summary). The -CG flashes have a total of 178 107
VHF sources while +CG flashes have 128 446 VHF sources, thus +CG flashes have
a more complex structure, with an average of 289 sources per flash with
respect to the 250 sources associated with -CG flashes.
Histogram during all days analysed of from top to bottom,
Zh, Zdr,
ρhv and Kdp. (a, c, e, g) All
sources. (b, d, f, h) The first source only. Bluish area: all flashes with associated EUCLID
CG strokes. Greenish area: flashes with associated EUCLID -CG strokes. Reddish area:
flashes with associated EUCLID +CG strokes. Note that the values outside of
the histogram range are added to the bins at the
extremes.
Regarding the time of occurrence (see Fig. a), for both types of CG flashes there is a well-defined peak of
occurrence between 16:00 and 18:00. However, while the number of -CG and
+CG
flashes occurring between 16:00 and 17:00 is roughly the same, between 17:00
and 18:00 the number of -CG flashes is double that of +CG flashes. This
indicates that individual storms have a preference to produce either one type
of flash or the other. The flash duration distribution (Fig. b) is very similar for both -CG and
+CG flashes but +CG flashes tend to cover a larger area (Fig. c). Indeed the mode and the median
of the +CG flashes area coverage is 450 and 650 km2,
respectively, while that of the -CG flashes is 50 and 350 km2. Figure d shows the
distribution of number of EUCLID CG strokes per LMA flash, i.e. its
multiplicity. +CG flashes are mostly associated with a single EUCLID +CG stroke
whereas -CG flashes are more likely to have several EUCLID -CG detections
associated with them. The maximum number of EUCLID strokes detected for -CG flashes is
20 while for +CG flashes it is just 5.
In terms of source power (not shown), when looking at all VHF sources the
distribution is very similar for both +CG flashes and -CG flashes and the
median value is the same, 19.5 dBm. However, when looking at the first
source the median power of +CG flashes is larger (21.5 dBm compared to
20.5 dBm).
Regarding the altitude of the VHF sources, there are remarkable differences
between the two CG flash types (see Fig. a and b). -CG flashes exhibit a bimodal distribution with a peak at 7400 ma.m.s.l.
and another one at roughly 4000 ma.m.s.l. By contrast,
+CG flashes have a Gaussian-like distribution with median value 6900 ma.m.s.l. When looking at the flash origin the contrast is even more marked.
+CG flashes have a median altitude of 7500 ma.m.s.l., while -CG flashes
have a larger median altitude of 8000 ma.m.s.l. Looking at the
temperature data from the COSMO model (see Fig. c and d) we again observe a modest decrease in median value when all
sources are considered from -CG flashes to +CG flashes (-19
to -18∘C) but a larger decrease when focusing on the flash
origin (from -26 to -22∘C). Therefore, it seems
clear +CG flashes tend to have an origin at lower levels in the precipitating
system.
In terms of the distribution of the polarimetric variables (see Fig. ), some minor differences can also be noticed. The
reflectivity distribution of -CG flashes has a Gaussian-like shape, although
skewed towards lower values, with median 37 dBZ, while +CG flashes have
an almost uniform distribution with median value 34.5 dBZ when all
sources are considered. When only the first sources are considered, the median is
40.5 dBZ for -CG flashes and 39 dBZ for +CG flashes. The other polarimetric
variables have very similar distributions.
Focusing on the dominant hydrometeor types at each flash location (see Table )
it is worth highlighting that a higher percentage of +CG
flashes originate in the liquid-phase region than the corresponding
percentage of -CG flashes (0.8 %). Also worth noting is the fact that a
larger percentage of -CG flashes have an origin in regions where solid hail is
the dominant particle with respect to +CG flashes. Having said that, as has
been the case throughout all the data analysis, the entropy of the
hydrometeor classification is rather high (0.4 mode), and most of the radar
gates contain two or more hydrometeor types in significant proportions.
2-D histogram of the type of the most-dominant and second most-dominant
hydrometeor at the radar gate collocated with the VHF source position. From
top to bottom: all flashes with associated EUCLID CG data, flashes with
associated EUCLID -CG strokes, flashes with associated EUCLID +CG strokes.
(a, c) All VHF sources in the flash (b, d) and only the first VHF sources.
Figure examines the most likely combination of
hydrometeors at the location of the VHF sources. When looking at all sources,
the most likely combinations for -CG flashes are solid hail and rimed
particles, regardless of the dominant type, followed by a combination of rimed
particles as the most dominant and aggregates as the second most common. When looking at
the flash origin, the most likely combination is clearly dominant solid hail
and rimed particles as the second most-dominant hydrometeor followed by rimed
particles as the most dominant and solid hail as the second most dominant. When looking at
+CG flashes the distribution is similar but there are some significant
differences. The most likely combination when looking at all VHF sources
clearly becomes rimed particles as the most dominant and solid hail as the second most
dominant. In second place with similar percentages there is solid hail as
the most dominant and rimed particles as the second most dominant and rimed particles as
the most dominant and aggregates as the second most dominant. When looking at the flash
origin, the most likely combination is rimed particles as the most dominant and solid
hail as the second most dominant followed by solid hail as the most dominant and rimed
particles as the second most dominant. A significant percentage of flashes have
an origin in areas where rimed particles are dominant but aggregates are the
second most dominant and in areas where the radar volume essentially contains
solid hail.
Characteristics of the flashes with an origin in the liquid or mixed-phase regions
Here we focus our attention on LMA flashes with an origin in the liquid or
mixed-phase regions. The reason for that is that those flashes are more
likely to be of the upward lightning type. For our classification we have
considered flashes whose first VHF source was in areas where the dominant hydrometeor was light rain,
rain, melting hail or wet snow as belonging to the mixed-phase or liquid-phase regions . Flashes located in regions of wet snow are
considered to have an origin in the mixed phase while flashes with sources in
light rain, rain or melting hail are considered to have an origin in the
liquid-phase
region. This section discusses the histograms presented in Figs. to .
In those figures, the bluish area of the histogram corresponds to flashes with an origin in
either the mixed-phase or liquid-phase regions, the greenish area of the histograms corresponds
to flashes with an origin in the mixed-phase regions and the reddish area of the histograms
correspond to flashes with an origin in the liquid phase. In the following we
will call flashes with an origin in the liquid-phase (LP) flashes, flashes with
an origin in the mixed-phase (MP) classes and flashes with an origin either in the
mixed-phase or the liquid-phase non-solid-phase (NSP) flashes.
There are only 241 NSP flashes in the dataset. These flashes generated a
total of 31 651 VHF sources. Of those, 100 are MP flashes (with 12 655 VHF
sources) and 141 are LP flashes (with 18 996 sources). Regarding their
position, Fig. shows that they are mostly
distributed in a narrow area going from southwest to northeast in line with
the direction of the Alps. It is interesting to notice that a higher
concentration of flash origins can be seen at the location of the Säntis
tower and at another location south of it that we have identified as the
Gamsberg area. This backs our assumption that a large percentage of those
flashes have origins on the ground.
Position of detected VHF sources for the days examined. (a, c, e) All
VHF sources. (b, d, f) Only the first sources of each flash. From top to bottom:
flashes with an origin in the liquid- and mixed-phase regions, flashes with
an origin in the mixed-phase region, and flashes with an origin in the liquid-phase region.
Regarding the time of occurrence (see Fig. a), it is interesting to note that those types of flashes are
distributed in a more uniform manner than when considering all the flashes.
The flash duration distribution (Fig. b) shows that most flashes are relatively short-lived. The median
duration of NSP flashes is 150 ms. They also cover a reduced area with
a median of 50 km2 (see Fig. c).
Distribution of the flashes for all days analysed: (a) time of
occurrence, (b) duration and (c) the 2-D projection area over the day for
all days analysed. Bluish area: flashes with an origin in the liquid- and mixed-phase
regions. Greenish area: flashes with an origin in the mixed-phase region. Reddish area:
flashes with an origin in the liquid-phase region. Note that the values outside of the
histogram range are added to the bins at the
extremes.
In terms of source power (Fig. ), when all
VHF sources are considered, these flashes have a lower median than the
general data, 18.5 dBm. When only the first VHF source in the flash is
considered, the median power is 19.5 dBm for MP flashes and 18.5 dBm for LP flashes. It should be noticed that the distribution is not
Gaussian-like but has two distinct peaks. A main one at roughly 20 dBm
and a second one around 5 dBm, although this could simply be due to
undersampling.
Histogram of VHF sources power for all days analysed. (a) All
sources. (b) Only the first sources of each flash. Bluish area: flashes with an origin
in the liquid- and mixed-phase regions. Greenish area: flashes with an origin in the
mixed-phase region. Reddish area: flashes with an origin in the liquid-phase region. Note
that the values outside of the histogram range are added to the bins at the
extremes.
Regarding the altitude of the VHF sources, there are remarkable differences
with the global data (see Fig. a and b).
As it should be expected NSP flashes are first detected at low altitudes
(median of 3500 ma.m.s.l. for MP flashes and 3200 ma.m.s.l. for
LP flashes), but their altitude when considering all sources has a bimodal
distribution with a main peak at 3600 ma.m.s.l. for MP flashes (3800
for LP flashes) and another roughly at 9000 ma.m.s.l. for both. These
data are further confirmed when looking at the temperature from the model
(Fig. bottom panels). When first detected,
NSP flashes are located in regions with a temperature of 0∘C or
a positive temperature, but they seem to extend higher up and concentrate in two main
layers, one roughly at -5∘C and the other at -30∘C.
Histogram during all days analysed of (a) VHF sources
altitude, (b) only the first sources of each flash altitude, (c) all sources model air temperature, and (d) the first source's model air
temperature. Bluish area: flashes with an origin in the liquid- and mixed-phase
regions. Greenish area: flashes with an origin in the mixed-phase region. Reddish area:
flashes with an origin in the liquid-phase region. Note that the values outside of the
histogram range are added to the bins at the
extremes.
The distribution of the polarimetric variables (see Fig. ) has significant differences with the global
data. The reflectivity has a uniform-like distribution extending from roughly
10 to 50 dBZ, with two barely visible peaks at 10 and 40 dBZ.
There is not enough data to fully characterise the reflectivity at the flash
origin, but it appears to have a Gaussian-like distribution with a median of 35.5 dBZ
for NSP flashes and 32 and 40 dBZ when stratifying into MP
and LP flashes, respectively. Zdr has a
Gaussian-like shape centred at 0 dB when considering all VHF sources.
When considering only the flash origin, the distribution is also
Gaussian-like but with a positive median of 0.3 dB for NSP flashes
(0.3 and 0.6 for MP and LP flashes, respectively).
ρhv also has a much wider distribution than the
global data, particularly when considering the flash origin. The mode is
0.997 for NSP (0.998 for MP flashes and 0.994 for LP flashes).
Kdp is skewed towards positive values. The large
prevalence of values 2∘km-1 or larger in LP flashes is
particularly remarkable.
Histogram during all days analysed of, from top to bottom,
Zh, Zdr,
ρhv and Kdp. (a, c, e, g) All
sources. (b, d, f, h) The first source only. Bluish area: Flashes with an origin in the
liquid- and mixed-phase regions. Greenish area: flashes with an origin in the mixed-phase
region. Reddish area: flashes with an origin in the liquid-phase region. Note that the
values outside of the histogram range are added to the bins at the
extremes.
Figure a and Table
show the distribution of the dominant hydrometeors at the
flash source locations. There are remarkable differences with respect to the
global data. When considering NSP flashes, as usual the most common
hydrometeor is rimed particles with 48.4 % but it is followed by dry snow
with solid hail being the third most common. A large percentage of sources are
located in areas of rain and wet snow. When further stratifying the data
according to the flash origin, it can be seen that there is a larger
proportion of sources located in the mixed phase for MP flashes with respect
to LP flashes. The most salient feature is a significant increase in
the solid hail proportion of LP flashes. What is most remarkable though is
that when examining the entropy of the hydrometeor classification (see Fig. middle panels) at the flash origin, it is
much higher than that of the global data. Indeed, LP flashes have an entropy
mode of 0.5 and MP flashes have an even higher entropy mode of 0.6. That
translates into a higher proportion of flashes with an origin in radar gates
containing a mix of at least two and up to five hydrometeors (see Fig. e and f).
Histogram during all days analysed of, from top to bottom, the dominant
hydrometeor at the radar gate collocated with the VHF source position,
the hydrometeor-classification-derived entropy at the radar gate collocated with
the VHF source position, and the number of hydrometeor types with a significant
presence at the radar gate collocated with the VHF source position. (a, c, e) All
sources. (b, d, f) The first source only. Bluish area: flashes with an origin in the
liquid- and mixed-phase regions. Greenish area: flashes with an origin in the mixed-phase
region. Reddish area: flashes with an origin in the liquid-phase region. Note that the
values outside of the histogram range are added to the bins at the
extremes.
Figure examines the most likely combination
of hydrometeors at the location of the VHF sources. Unlike in the other data
analysed, when all VHF sources are considered, the most common combination is
that of rimed particles and snow, followed by rimed particles and dry hail.
The most striking feature when looking at the flash origin is that the most-dominant combination is a mixture. In the case of MP flashes the most likely
combination is wet snow and rain, followed by wet snow and rimed particles.
LP flashes, on the other hand, have a mixture of rain and wet snow as the most
likely.
A 2-D histogram of the type of the most-dominant and second most-dominant
hydrometeor at the radar gate, collocated with the VHF source position. From
top to bottom: Flashes with an origin in the liquid- and mixed-phase regions,
flashes with an origin in the mixed-phase region, and flashes with an origin in the
liquid-phase region. (a, c, e) All VHF sources in the flash. (b, d, f) Only the first VHF sources.
Discussion
Our dataset is dominated by data taken from 2 days: 1 August and
19 July. Both of these days represent 62% of the total number of flashes in the
dataset but 86 % of the CG flashes and an outstanding 93 % of the CG+
flashes, a fact that has to be taken into account in order to interpret the
results.
Most of the lightning activity during the 8 d analysed took place in the
late afternoon. This seems to hint that a strong diurnal cycle, possibly
reinforced by topographically induced wind systems, is what enables the level
of convection necessary to trigger the lightning production mechanism
. The passage of a cold front, typically from
west-southwest to east-northeast in this region and synchronised with the
diurnal cycle, might have increased the severity of the storms and had a
positive impact on lightning production .
Observing the synoptic situation on the days analysed (not shown) this seems
to be the case for the 1 August and the 10 and 30 July.
Most flashes were intra-cloud and only 9 % reached the ground, although this
percentage varied widely from day to day, from a minimum of 1.5 % on 1 August to 17.6 % on 29 June. This result is consistent with that reported
for storms during the summer period in the Ebro Valley (6.9 %) by
, which is the largest study with LMA data in the
Mediterranean basin so far. Also consistent with that study, IC flashes tended to be
shorter lived and of a smaller area than CG flashes. Flashes with an origin in the
liquid- or mixed-phase layers of precipitation represented approximately 2 %
of the dataset. Here there were again large day-to-day variations, from 1.1 %
to 12.4 %.
The large majority of the flashes detected in our study originated in areas
where rimed particles and/or solid hail were dominant. In a significant
number of cases, the presence of other hydrometeors such as aggregates was
non-negligible. Most flashes had an origin at relatively high altitudes
(8000–9000 ma.m.s.l.). It is interesting to notice that, examining the
median origin altitude of individual days (not shown) it can be observed that
on days with less activity, the flash origin altitude is remarkably lower
(4000–5000 ma.m.s.l). Although no data were available during the
campaign about the vertical wind at the onset of lightning, the widespread
presence of rimed particles makes it very likely that, either at the onset of
lightning or moments before, a significant number of super-cooled liquid
water was present. Considering the altitude at which they were located, it is
also safe to assume that flashes were most likely originated in transition
areas between regions dominated by rimed particles and regions where the
effects of the updraft were diminished and ice crystals or aggregates were
dominant. Overall the data agrees with the graupel–ice collision mechanism
e.g.,
whereby individual particles acquire charge by collisions between
precipitation particles and cloud particles, and gravity acts as a charge
separator by pulling down most of the precipitating particles (i.e. rimed
particles), while cloud particles (i.e. ice crystals or small aggregates)
remain aloft. A shallower region dominated by rimed particles seems to result
in lower lightning activity. Thus, in line with research from past studies
e.g., we find a
relationship between the vertical extent of the regions dominated by rimed
particles and the intensity of lightning activity.
When analysing GC flashes in detail we found that, with respect to IC
flashes, there was a remarkable increase in flashes with an origin in regions
dominated by hail and a noticeable increase in those with an origin in the
liquid- and mixed-phase regions. That, coupled with a lower median origin
altitude, suggests that flashes generated at the lower parts of the
convective system are more likely to reach the ground. The general picture
that emerges from these considerations is that of a classical tripole
with a small positively charged layer at
the bottom (close or at the melting layer), a higher negative layer at the
centre (in a region of high density of rimed particles) and a positive layer
at the top (in the region where fewer rimed particles are formed and more ice
crystals and aggregates are present). Most of the flashes are generated in
the transition between the top negative and positive layers and propagate
through the negative layer. The bottom layer tends to be less active but
flashes generated there are more likely to reach the ground.
Our dataset contained an unusually high proportion of +CG flashes with
respect to -CG flashes. That is mostly due to the very large proportion of
+CG flashes in 3 out of the 8 d analysed. On those days hail was
reported, and hence those results confirm past observations that associate and increase
in +CG flashes with hail on the ground
e.g.. The origins and the
paths of the +CG flashes emerging from our data are not clear-cut. It is
somehow surprising that the percentage of flashes that have an origins in regions
where hail is dominant is lower than that of -CG flashes. It is also
interesting to notice that there is simultaneously an increase in the
percentage of flashes with origins in regions where aggregates are dominant
(i.e. high up in the cloud structure) and an increase in flashes having
origins in the mixed-phase and liquid-phase layers. Coupling that with a more
uniform distribution of the altitude of the flash origin and the reflectivity
values it emerges that +CG flashes have multiple generating mechanisms with
none of them being dominant.
In regular storms, they may be generated at the transition between the lower
positive layer and the negative layer of the classical tripole structure
(which would result in a significant percentage being generated in areas of
melting hail and wet snow) or they may be generated at the top positive layer
(and thus a significant percentage would have an origin in aggregate areas).
That is the likely scenario for those days where the percentage of +CG
flashes with respect to the total is in line with what has been reported in
past literature. However, most flashes present in the statistics were
generated on two particular days. For those days we suspect that a
significant percentage of flashes have been generated at the transition
between the top positive and negative layers in an inverted tripole structure
. That would explain both the lower percentage of hail
as the most-dominant hydrometeor in the statistics (since at those altitudes likely
smaller rimed particles may be dominant) and the high altitude at which those
flashes tend to originate.
The triggering mechanisms for flashes first detected in the liquid- or mixed-phase layers of a storm seem to be significantly different than those of the
other lightning types. Examining the lightning path shows that they are much
less likely to propagate through areas where hail is dominant. In contrast,
they are significantly more likely to propagate in areas of dry snow. Therefore, it
seems that they are less likely to be generated in areas of deep
convection. In fact the lowest percentage of this type of lightning is
registered on the 2 days with the most lightning activity. The behaviour of
these flashes seems to be in good agreement with upward lightning, probably
triggered by other lightning in the area. In the first place they are highly
concentrated in the mountainous areas with a clear hot spot at the actual
Säntis tower. In line with the studies performed specifically over the
Säntis tower during the campaign , a vast majority
of flashes propagate upwards, up to areas of transition between rimed
particles and dry snow and then extend horizontally within those areas.
Conclusions
We have presented an analysis of a large dataset of lightning and
polarimetric weather radar data collected in the context of a lightning
measurement campaign that took place in the summer of 2017 in the area
surrounding Säntis, in northeastern Switzerland. In this
campaign, for the first time in the Alps, a lightning mapping array was
deployed. This paper focuses on data from 8 d where lightning activity was
registered in the immediate vicinity of the Säntis tower. A total of 1 586 394
VHF sources, corresponding to 12 062 flashes (i.e. and average of 132 sources
per flash) were detected by the LMA.
In this paper we have investigated the characteristics of the LMA flashes and
related their VHF sources to co-located polarimetric radar measurements in
order to determine the characteristics of the precipitation systems that
enable the initiation and propagation of lightning. We have performed a
general assessment and proceeded to stratify the data into the usual
categories, i.e. intra-cloud, cloud-to-ground (positive or negative according
to the associated EUCLID strokes) and flashes with an origin in the liquid- and
mixed-phase layers as a proxy for upward lightning.
The general data analysis shows that there is a clear diurnal cycle in the
days analysed with most flashes occurring in the late afternoon. Most
lightning-producing systems travelled from southwest to northeast, roughly
following the foothills of the Alps. VHF sources are more likely to be
detected at altitudes between 3000 and 9000 ma.m.s.l. Their origin is more likely to be located at altitudes between 7000 to 9000 ma.m.s.l. Flashes thus originate in the upper part of convective
clouds and either propagate at roughly the same altitude or move towards a
lower layer. Most of the flashes originate in areas of high reflectivity
(roughly 40 dBZ), low Zdr, low
Kdp and high ρhv. A
large majority of flashes originate in regions with a high concentration of
particles with a certain degree of riming (either small rimed particles or
solid hail), and, for the most part, they propagate within such regions.
However, these regions are characterized by a high entropy and the radar
resolution volume is likely to contain more than one hydrometeor type in
significant proportions. The most likely combination of hydrometeors is rimed
particles and solid hail, regardless of which one is dominant. Very few
flashes originate in the mixed phase or liquid phase of precipitation and the
number of VHF sources in those regions is also rather small, suggesting that
flashes may transit through them but with a vertical direction.
Most of the examined flashes did not produce an associated EUCLID CG stroke,
i.e. they were IC. CG flashes constitute approximately 10 % of the total dataset. There are significant differences between IC and CG flashes. CG flashes
tend to generate more VHF sources, last significantly longer and have a
larger projected area. The median altitude at which they are generated is
lower than the IC ones and the temperature in the regions of generation is
higher, a clear indicator that they are generated lower in the cloud. The
co-located polarimetric variables have fairly similar distributions to those
of the IC flashes, except that generally speaking they are wider. The
reflectivity at the flash origin location, in particular, has a significantly
larger median, suggesting that CG flashes are more likely to occur in regions
of higher particle concentration and/or larger particle size and density,
increased, for example, as a consequence of riming. That aspect is further
confirmed by an increased proportion of flashes having their origin in areas
where solid hail is the dominant hydrometeor. Indeed, the most likely
combination of hydrometeors at the CG flash origin is one having solid hail
as the most dominant and rimed particles as the second most dominant.
We have also attempted to further stratify the LMA flashes associated with
EUCLID CG strokes into those generating a positive stroke and those
generating a negative stroke. Roughly two-thirds of the flashes in the
dataset are -CG and one-third are +CG. The characteristics of both types of
flashes are rather similar although with some significant differences. +CG
flashes tend to cover a larger area. -CG flashes are more likely to be
associated with multiple EUCLID strokes. The median of the signal power at
the origin of the discharge is slightly larger for +CG flashes. The altitude
and temperature distributions also have significant differences. +CG flashes
originate at a significantly lower altitude than -CG flashes. When all VHF
sources are considered, the distribution of -CG flashes is bimodal while the
distribution of +CG flashes is Gaussian-like. This would suggest that -CG
flashes tend to propagate in multiple layers while +CG flashes have a more
vertical structure. There are not many differences between the distribution
of polarimetric variables of -CG and +CG flashes. The most remarkable
difference is in the distribution of the reflectivity when all VHF sources
are considered. -CG flashes have a Gaussian-like shape while +CG flashes have
an almost uniform distribution. Again, this would suggest that -CG flashes
are more likely to propagate in the cloud layer where they originated.
whereas +CG flashes have a more vertical structure. As with all the data
analysed, the entropy of the hydrometeor classification is rather high and it
is very likely to have multiple hydrometeor types with significant
proportions within a radar resolution volume. The proportion of dominant
hydrometeors is similar for both types of flashes. The main difference is a
larger percentage of -CG flashes that have an origin in areas of solid hail.
However, in both cases the most likely combination of hydrometeors at the
flash origin is solid hail and rimed particles, albeit in different
proportions.
We have also examined the characteristics of LMA flashes that have their origin
in the liquid- and mixed-phase layers. The rationale for that is that there is
an increased likelihood that those flashes are upward lightning. Only 241
flashes in the dataset had an origin in the mixed-phase or liquid-phase layers and, of
those, 141 had an origin in the liquid layer. One aspect that sets apart this
type of flash is that their origins are not randomly distributed within the
path of the storm but we have identified areas of higher concentration. One
of them is the Säntis tower and another is the Gamsberg. That is a
strong indicator that indeed these flashes originate by interactions with the
terrain and man-made objects. These flashes tend to be short-lived and occupy
a reduced projected area, which would indicate a vertical orientation. As would be expected, they are first detected at low altitudes but their
altitude distribution is bimodal with a secondary peak at roughly 9000 ma.m.s.l., a rather high altitude within the precipitating system. The distribution
of the polarimetric variables is also fairly different from the rest of the
data analysed. Overall, these distributions suggest that this sort of flash
encounters a larger variety of precipitation regimes along their path. This is
further confirmed by the fact that the entropy of the hydrometeor
classification is even higher than in the previously examined cases,
particularly at the flash origin, and it is rather common to have more than two
species in significant proportions at the flash origin. Unlike with the rest of
the data examined, rimed particles or solid hail are not part of the most
common species in the mixture at the location of the flash origin, the most
common being a mixture of wet snow and rain. However, when examining all the
VHF sources, the most common mixture at the VHF source position is rimed
particles and snow. Solid hail, on the other hand, does not have as much of a
significant presence as it does the global data. This would indicate that this
sort of flashes can be initiated even in moderate convection conditions.
From our analysis we can conclude that a systematic detection of lightning
with polarimetric radar data is not possible, but radar data can be extremely
useful to indicate regions with favourable conditions for lightning
initiation. A high concentration, i.e. high reflectivity, of rimed particles
and/or solid hail and a high entropy of the hydrometeor classification are a
primary indicator of lightning activity. Whether the generated flashes are IC
or CG is not something that can be readily determined by just observing
the polarimetric radar data, although there are indicators that suggest that
CG flashes tend to generate at a lower cloud level and, therefore, looking at
the vertical structure of the precipitating system can provide hints on
whether the flashes are more likely to be contained within the cloud or
propagate to the ground. Upward lightning poses another challenge because
this type of flash has not shown as clear radar signatures as the rest
of the examined categories and seem to be driven mostly by the interaction of
the storm with the terrain and man-made structures. Nevertheless, in
that case a degree of convection also seems to be necessary to initiate a flash.
In any case, to estimate the probability of this sort of flashes it seems
clear that either the orography (including man-made structures) or a
climatology has to be included in any flash nowcasting system.
Code and data availability
Code used to post-process the radar data is available
on github https://github.com/meteoswiss-mdr (last access: 21 May 2019). Data are available on
request by contacting the authors.
Author contributions
JFiV performed the radar data processing and the data analysis contained in this paper.
NB and JG contributed to the radar data processing and data interpretation.
OvdV, DR, JM, NP, AS, AM, MA, MR and FRH deployed the LMA network and processed
its data. UG and AH advised on the content of the paper. JFiV prepared the paper with
contributions from all authors.
Competing interests
The authors declare that they have no conflict of interest.
Financial support
This research has been supported by the Swiss National
Science Foundation (grant no. 200020_175594), the Horizon 2020 Framework
Programme (grant LLR 737033), the Spanish Ministry of Economy, and the European Regional Development
Fund (FEDER) (grant nos. ESP2013-48032-C5-3-R, ESP2015-69909-C5-5-R and
ESP2017-86263-C4-2-R.)
Review statement
This paper was edited by Gianfranco Vulpiani and reviewed by three anonymous referees.
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