Evidence for solar wind modulation of lightning

Abstract

The response of lightning rates over Europe to arrival of high speed solar wind streams at Earth is investigated using a superposed epoch analysis. Fast solar wind stream arrival is determined from modulation of the solar wind V y component, measured by the Advanced Composition Explorer spacecraft. Lightning rate changes around these event times are determined from the very low frequency arrival time difference (ATD) system of the UK Met Office. Arrival of high speed streams at Earth is found to be preceded by a decrease in total solar irradiance and an increase in sunspot number and Mg II emissions. These are consistent with the high speed stream's source being co-located with an active region appearing on the Eastern solar limb and rotating at the 27 d period of the Sun. Arrival of the high speed stream at Earth also coincides with a small (~1%) but rapid decrease in galactic cosmic ray flux, a moderate (~6%) increase in lower energy solar energetic protons (SEPs), and a substantial, statistically significant increase in lightning rates. These changes persist for around 40 d in all three quantities. The lightning rate increase is corroborated by an increase in the total number of thunder days observed by UK Met stations, again persisting for around 40 d after the arrival of a high speed solar wind stream. This result appears to contradict earlier studies that found an anti-correlation between sunspot number and thunder days over solar cycle timescales. The increase in lightning rates and thunder days that we observe coincides with an increased flux of SEPs which, while not being detected at ground level, nevertheless penetrate the atmosphere to tropospheric altitudes. This effect could be further amplified by an increase in mean lightning stroke intensity that brings more strokes above the detection threshold of the ATD system. In order to remove any potential seasonal bias the analysis was repeated for daily solar wind triggers occurring during the summer months (June to August). Though this reduced the number of solar wind triggers to 32, the response in both lightning and thunder day data remained statistically significant. This modulation of lightning by regular and predictable solar wind events may be beneficial to medium range forecasting of hazardous weather.

Full text

Evidence for solar wind modulation of
lightning
C J Scott, R G Harrison, M J Owens, M Lockwood and L Barnard
Department of Meteorology, University of Reading, Reading, Berkshire, UK
E-mail: chris.scott@reading.ac.uk
Received 12 May 2013, revised 21 March 2014
Accepted for publication 4 April 2014
Published 15 May 2014
Abstract
The response of lightning rates over Europe to arrival of high speed solar wind streams at Earth
is investigated using a superposed epoch analysis. Fast solar wind stream arrival is determined
from modulation of the solar wind V
y
component, measured by the Advanced Composition
Explorer spacecraft. Lightning rate changes around these event times are determined from the
very low frequency arrival time difference (ATD) system of the UK Met Office. Arrival of high
speed streams at Earth is found to be preceded by a decrease in total solar irradiance and an
increase in sunspot number and Mg II emissions. These are consistent with the high speed
stream’s source being co-located with an active region appearing on the Eastern solar limb and
rotating at the 27 d period of the Sun. Arrival of the high speed stream at Earth also coincides
with a small (∼1%) but rapid decrease in galactic cosmic ray flux, a moderate (∼6%) increase in
lower energy solar energetic protons (SEPs), and a substantial, statistically significant increase in
lightning rates. These changes persist for around 40 d in all three quantities. The lightning rate
increase is corroborated by an increase in the total number of thunder days observed by UK Met
stations, again persisting for around 40 d after the arrival of a high speed solar wind stream. This
result appears to contradict earlier studies that found an anti-correlation between sunspot number
and thunder days over solar cycle timescales. The increase in lightning rates and thunder days
that we observe coincides with an increased flux of SEPs which, while not being detected at
ground level, nevertheless penetrate the atmosphere to tropospheric altitudes. This effect could
be further amplified by an increase in mean lightning stroke intensity that brings more strokes
above the detection threshold of the ATD system. In order to remove any potential seasonal bias
the analysis was repeated for daily solar wind triggers occurring during the summer months
(June to August). Though this reduced the number of solar wind triggers to 32, the response in
both lightning and thunder day data remained statistically significant. This modulation of
lightning by regular and predictable solar wind events may be beneficial to medium range
forecasting of hazardous weather.
Keywords: solar wind, lightning, thunder, cosmic ray
1. Introduction
The Sun undergoes an approximately 11 year activity cycle
driven by the differential rotation rate of the solar convection
zone. This differential rotation of the solar plasma distorts the
solar magnetic field, gradually converting a polar field into a
toroidal one throughout the solar cycle (Babcock 1961). As
the magnetic field becomes more distorted, complex regions
of intense magnetic field emerge through the photosphere.
Observed in visible light, the emerged magnetic flux tubes
with larger diameters appear darker than the surrounding
photosphere and are known as sunspots. Solar influences on
the terrestrial atmosphere, and, in particular, effects on elec-
trified storms have been studied for many years, as sum-
marized by Schlegel et al (2001). Stringfellow (1974), found
a correlation between sunspot number and day on which
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thunder was heard (‘thunder days’) in the UK while other
studies (Pinto et al 2013) have found an anti-correlation
between solar cycle variations and thunder days. Brooks
(1934) analysed data from a variety of locations and found a
large variation in the relationship between sunspots and
thunderstorm activity. Markson (1981) demonstrated a posi-
tive correlation between galactic cosmic ray (GCR) flux and
ionospheric potential which, it has been argued, indicates a
sensitivity of thundercloud electrification to ambient electrical
conditions. Mechanisms have subsequently been postulated
by which solar activity could influence the frequency of ter-
restrial lightning through modulation of the solar irradiance,
the GCR flux or some combination of these two. These are
discussed below.
Increase in GCR flux may directly trigger lightning
through ‘runaway breakdown’of electrons, leading to
breakdown (Roussel-Dupré et al 2008). This is supported by
recent observations of energetic photons from thunderstorms,
as predicted by runaway breakdown theory (e.g. Gurevich
and Zybin 2005). In a study using 16 years of lightning data
over the USA, Chronis (2009) found lightning activity
dropped 4–5 d after a transient reduction in GCRs (a Forbush
decrease), with a positive correlation between lightning and
GCRs during the winter. Before the final triggering of light-
ning however, an increase in atmospheric ionization may also
reduce the effectiveness of thunderstorm charging processes.
In the extreme case of a simulated nuclear winter, in which
atmospheric ionization was assumed to be vastly increased,
Spangler and Rosenkilde (1979) estimated that charging of
thunderstorms would be inhibited. However, following the
Chernobyl reactor accident, in which lower troposphere
ionization increases occurred, an increase in lightning was
observed as radioactivity passed over Sweden, so the
response may be complex (Israelsson et al 1987). For
example, changes in atmospheric conductivity also occur with
natural variation in cosmic ray ionization (Harrison and
Usoskin 2010). Hence establishing the sign of the response in
lightning to GCRs may therefore be complicated by com-
peting processes, in which different regional meteorological
characteristics also play a role. The analysis here uses well-
defined marker events in the solar wind to investigate the
response in lighting over the UK, as detected by a very low
frequency lightning detection system.
2. Solar modulation of GCRs
While most of the solar atmosphere is retained by gravity,
energetic particles can still escape and form a continuous
stream of plasma into interplanetary space known as the solar
wind. There is also an extremely energetic, but intermittent,
population of particles known as solar energetic protons
(SEPs). The solar wind speed varies between 400 and 2000
km s
−1
and is modulated by the local solar magnetic field at its
point of emergence. Source regions connected to the helio-
spheric magnetic field (HMF) through ‘open’field lines are
associated with high speed solar wind streams while source
regions with ‘closed’magnetic topology are associated with
slow solar wind streams. Despite differential rotation of the
solar convection zone and surface, the magnetic field in the
solar atmosphere means it rotates as if it were a solid body,
resulting in a modulation of the solar wind at Earth of a period
close to 27 d as fast and slow solar wind streams sweep past
our planet. The passage of a fast solar wind stream also
generates a temporary enhancement in plasma density and
magnetic field strength of the solar wind at Earth called a ‘co-
rotating interaction region’(CIR) which further modulates the
GCR flux (Rouillard and Lockwood 2007). Because CIRs
persist for several solar rotations the decreases in GCR flux
they cause tend to recur at Earth every 27 d, whereas the
transient Forbush decreases do not.
Transient Forbush decreases at Earth are caused by the
passage of coronal mass ejections (CMEs). A CME is generated
after a reconfiguration of complex regions of magnetic field in
the solar atmosphere which result in vast magnetic ‘clouds’of
solar plasma erupting into interplanetary space. A typical CME
contains around one billion tonnes of material travelling at up to
2500 km s
−1
. The CMEs add to the quiet solar wind outflow
driven by the high temperaturesofthesolaratmosphereandas
CMEs and the solar wind propagate away from the Sun, they
extend the solar magnetic field into interplanetary space where it
becomes known as the HMF. The occurrence rate of CMEs is
modulated by the solar activity cycle, with more occurring at
solar maximum. The relative strength of the HMF is therefore
greater at the peak of the cycle (Owens and Lockwood 2012).
The HMF modulates the flux of highly energetic particles,
GCRs, which are pervasive throughout the solar system. These
particles have been accelerated to such high energies (typically
0.5 GeV–100 GeV) by extreme events in the Universe such as
supernovae. On entering the Earth’s atmosphere, these particles
collide with gas particles, generating neutrons that can be
detected by monitoring stations on the ground (e.g. Usoskin
et al 2009). The GCR flux measured in this way is inversely
proportional to the strength of the HMF, which in turn
approximately follows solar activity and sunspot number (e.g.
Rouillard and Lockwood 2004). The passage of a CME past
Earth is known to further modulate the GCR flux as it brings
with it a localized cloud of magnetized plasma. This enhanced
field results in a temporary reduction in the GCR flux, (a For-
bush decrease) used as marker events for comparison with
lightning in the study of Chronis (2009).
While Earth-directed CMEs generate the largest Forbush
decreases in cosmic ray flux, there are relatively few of these
events in any given solar cycle. In their analysis, for example,
Usoskin et al (2008) identified 39 strong Forbush decreases in
data from the World Neutron Monitor Network since 1964.
Instead, in this paper, we consider the arrival of high-speed
solar wind streams at Earth from 2000 to 2005 and combine
these in a superposed epoch analysis to look for a modulation
in lightning rates in data from the arrival time difference
(ATD) lightning detection network of the UK Met Office
(Lee 1989). While these solar wind streams cause smaller
decreases in GCR flux than CMEs, they are sufficiently
numerous to allow a meaningful statistical analysis (for
comparison, Usoskin et al (2008) identified 14 Forbush
events between 2000 and 2005).
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
2

3. Method
3.1. Identifying trigger events
The arrival of high speed solar wind streams at Earth can be
inferred from sudden changes in the V
y
component of the
solar wind in the Geocentic-Solar-Ecliptic (GSE) frame of
reference i.e., anti-parallel with the Earth’s orbital direction
(e.g. McPherron et al 2004; Denton et al 2009; Davis
et al 2012). Here we used solar wind data from the Advanced
Composition Explorer (ACE) spacecraft (Stone 1998), orbit-
ing the L1 Lagrangian point 0.01 au upstream from the Earth
in the solar wind, along the Sun–Earth line (the Xdirection of
the GSE frame). Arrival of a high-speed stream at Earth was
identified if the solar wind V
y
component increased by more
than 75 km s
−1
over 5 h. While the exact V
y
threshold used is
arbitrary, our results are robust to different choices; the
threshold described presents a good compromise, generating
532 pronounced events.
These event times were used as markers around which
responses in other solar wind and geophysical parameters
were averaged, which is essentially the super-posed epoch or
compositing technique originally described by Chree (1908).
Compositing provides a useful way of investigating weak yet
repeated signals that may otherwise be swamped by larger
random variations. By aligning the secondary data according
to the times identified in the primary data (the ‘trigger’times)
and calculating the median response, random responses will
average out to zero while any (even small but) consistent
signal will remain. Medians rather than means are calculated
to ensure that the combined result is not dominated by one or
more large outliers in the data. In our study, ‘trigger’times
were the times at which enhancements were observed in the
solar wind V
y
component. Repeating the analysis many times
using random trigger times, the probability of whether a given
response exceeds that expected by chance can be found by
calculating the 95 and 99 percentiles of these random
responses. The significance of any response can be further
investigated by comparing the data used to calculate median
values at a range of times before and after the ‘trigger’time
using a two-sided Kolmogorov−Smirnov test.
3.2. Geophysical parameters considered
In our study we first ensured that we were correctly identi-
fying the arrival of solar wind streams by calculating the
median solar-wind velocity, V
y
, and magnetic field strength,
B
t
from periods of data corresponding to an interval of 60 d
around the trigger times identified. These times were then
used to calculate the associated median variability in solar
parameters (total solar irradiance (TSI), sunspot number, Mg
II emission, SEP flux and GCR flux), terrestrial lightning rates
and thunderstorm activity.
The speed and density of the solar wind were calculated
using data from the NASA ACE Spacecraft (Stone
et al 1998). The associated variations in TSI, sunspot number
and Mg II emissions were used to investigate whether there
was any solar variation associated with the generation of
high-speed streams. The TSI data used is the PMOD com-
posite of observations (Fröhlich 2006) which is consistent
with other solar indicators and with irradiance modelling in its
long-term behaviour (Lockwood and Fröhlich 2008). The Mg
II emission index (Heath and Schlesinger 1986) was included
in this analysis as this is often used as a proxy for many UV
emissions (Viereck et al 2001).
Information about the solar wind energetic particles or SEPs
was obtained from the GOES dataset (GOES N Data-
book 2006), which combines data from several spacecraft.
Proton energies are recorded in seven channels, each identified
by its low energy detection threshold. They are; > 1 Mev, >5
Mev, >10 Mev, >30 Mev, >50 Mev, >60 Mev and >100 Mev.
The GCR flux incident at Earth was determined using data
from the neutron monitoring station at Oulu (Kananen
et al 1991). This flagship dataset is a widely-used standard
within the solar-terrestrial physics community. It is a continuous,
well-calibrated dataset, which, because of the station’shigh
latitude location, records cosmic rays of energies down to the
atmospheric cut-off of about 1 GeV (at lower latitudes, the
geomagnetic field shielding gives higher cut-off energies).
Lightning rates were obtained from the ATD system of
the UK Met Office (Lee 1989). This system uses a series of
radio receivers located around Western Europe to detect the
broad-band radio emission emitted by lightning. Accurate
timing of the arrival of such ‘sferics’at a range of stations
allows the location of lightning to be determined with an
accuracy of 5 km over the UK. The ATD system has been
designed to have greatest efficiency in detecting cloud-to-
ground (CG) lightning over Europe. The current study uses
ATD data between September 2000 and June 2005, as this
represents a period when the detection sensitivity of the
system was not subject to modifications influencing its sen-
sitivity. After this period the system was expanded and
increased in sensitivity to form ATDnet, which detects a
much larger number of smaller sferics. While the ATD system
from 2000–2005 was capable of detecting lightning world-
wide, the sensitivity of the network was reduced for large
distances. In order to ensure some uniformity of the lightning
measurements within our analysis we therefore restricted our
data to any event that occurred within a radius of 500 km from
central England. The time range of the ATD data used in this
study encompasses 405 of the 532 trigger events identified in
the ACE spacecraft data.
The presence of thunderstorm activity is also recorded at
manned UK Met Office observing sites. Conventionally, a
‘thunder day’is considered as any day on which thunder was
heard at an observing site. While this observation is subject to
false positives (such as vehicle noise or explosions being mis-
identified as thunder) and is of a lower time resolution compared
with the lightning data, it provides an independent measure of
the presence of thunderstorm activity on a given day.
4. Results
After identifying when high-speed solar wind streams arrived
at Earth (as described in section 3.1), these times were used to
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
3

define t= 0 in all the geophysical datasets and the median
response was calculated for each parameter as a function of
event time tfor ±60 d around this time.
4.1. Solar wind
Figure 1presents the median change in solar wind parameters
measured by the ACE spacecraft. The top panel shows the
distribution of ‘trigger’events within the epoch under con-
sideration. As expected, the maximum number of triggers
(532) is seen at event time t= 0. Plotting the distribution of
triggers used in this study demonstrates that there are no other
times within 60 d of the trigger time at which there is such a
large number of high-speed streams arriving at Earth. This is
demonstrated by the middle panel of figure 1in which the
median response in the solar wind V
y
component is presented.
Around event time t= 0, the tangential solar wind decreases
from a background level just below 0−35 km s
−1
and then
increases to over 60 km s
−1
, all within a period of around 2 d,
with the greatest change at time zero. The grey band, in this
and subsequent plots, represents the standard error in the
median for all the data points within each time bin of the
composite analysis. Outside this time window there are no
other changes in V
y
that greatly exceed the 95 and 99 per-
centiles of the data (represented by the dot-dashed and dashed
lines respectively) though there is a hint of the solar rotation
rate with slight enhancements in V
y
at ± 27 d and ± 54 d.
These percentiles were estimated by repeating the composite
analysis one hundred times using the same number of trigger
times drawn at random from within the scope of the study.
The percentiles were then estimated by sorting the distribu-
tions in each time bin and ascertaining the 95 and 99 per-
centiles. The bottom panel of figure 1shows the associated
median change in magnetic field strength associated with
high-speed solar wind streams. At t= 0, the total magnetic
field strength, B
t
, peaks at about 13 nT compared with the
background of around 6 nT. The field rapidly increases and
decays over 2 d around the peak. Other than this peak around
t= 0, there are no significant enhancements in the median
solar wind magnetic field magnitude though again there are
hints of the solar rotation rate in enhancements at ±27 d
and ±54 d.
4.2. Solar irradiance
Three associated measures of solar activity are compared in
figure 2. The median TSI (figure 2, top panel) shows a small
(0.01%) but significant decrease some 7 d ahead of the arrival
of fast solar wind streams at Earth. This decrease is associated
with a rise in the median sunspot number, which lasts for
around 12 d. This is the time taken for half a solar rotation
(13.5 d) with respect to the Earth and is likely to be caused by
the appearance and rotation of active regions on the solar
surface. In the photosphere, active magnetic regions manifest
themselves as sunspots—darker cooler regions where the
convection of the plasma has been suppressed by the strength
of the local magnetic fields. Sunspots have been used as a
proxy of solar activity for many hundreds of years. The peak
sunspot number and minimum TSI will, on average, be when
the sunspots are close to the centre of the solar disk and this
occurs between t=−6 d and t=−4 d which is close to the
delay expected for the (radial) solar wind from such a region
to reach Earth. The complex magnetic field topology around
such regions is likely to lead to areas of open solar flux along
which fast solar wind streams can emerge and so it is not
unexpected that the two phenomena should be linked. The
bottom panel of figure 2presents the median Mg II index of
solar emission. This broad emission, centred on a wavelength
on 279.9 nm, has been found to be a convenient proxy for UV
emissions at other wavelengths. It presents similar behaviour
as sunspot number, peaking between 8 d and 2 d before t=0.
The downward overall trends in these parameters results from
this study using data from the declining phase of the solar
cycle. All three of these distributions appear towards the
lower end of their percentile ranges which is a consequence of
a minority of triggers coming from the times of enhanced
solar activity at the beginning of the study period. We have
chosen not to subtract a median value from each epoch of data
before calculating the median in these parameters to be con-
sistent with the analysis of all the other parameters in which
we are looking for a threshold effect where absolute values
are pertinent to their relative weighting.
4.3. Energetic particles at Earth
Figure 3presents the response of high energy GCR and lower
energy SEP fluxes to the arrival of fast solar wind streams at
Earth. The top panel presents the median daily change in
cosmic ray flux at Earth, as measured by the Oulu neutron
counter. With the approach of the solar wind stream and its
associated increase in magnetic shielding, the average GCR
flux decreases by 1.4% from around 141 570 counts to a
minimum of 139 571 at t= 0. This minimum is significantly
outside the 95 and 99 percentiles of the dataset (the dashed
and dotted lines, respectively). Before the decrease, the
count rates are higher than average (just above the 99 per-
centile) as was shown to be a persistent feature ahead of CIR s
(Rouillard and Lockwood 2007) and demonstrating that the
interaction regions are significant depressors of the overall
average GCR flux. The decrease starts some 5–10 d before
t= 0 and the subsequent recovery to pre-event levels takes
around 40 d. This is because the fast/slow solar wind inter-
action establishes a planar interaction front that is wound into
a spiral configuration. Because of the large gyroradius of
GCRs in the heliosphere, this can deflect GCRs that would
have reached Earth even before it arrives at the Earth (at t < 0),
but becomes a more effective shield as it passes over Earth,
giving the sudden decline in fluxes seen at t= 0. As the
interaction front moves outward GCRs can diffuse into its
wake, giving the gradual recovery to pre-event levels that we
observe.
Associated with the CIRs are enhancements in SEPs. The
lower panels presents a selection of energy channels (>1
Mev, > 30 Mev, >100 Mev) measured by the GOES satellites
(GOES N Databook 2006). These channels demonstrate the
evolution of SEP flux through the observed energy spectrum.
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
4

There is a doubling in the median proton flux in the lower
energy channel (>1 MeV) for 10 d around t= 0, along with
subsequent smaller enhancements 27 and 54 d later. Fluxes of
protons with energies exceeding 30 Mev (third panel) reveal a
9% increase in particle flux in the 3 d ahead of t= 0, dropping
to a level 5% above the pre-trigger levels and decaying from
this level over the subsequent 50 d. The highest energy pro-
tons (>100 MeV) are once again enhanced over the pre-trig-
ger levels by around 9% and remain elevated for the
subsequent 40 d, varying in intensity with a period of 18 d.
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
5
Figure 1. The response of solar wind parameters in a superposed epoch analysis using enhancements in ACE V
y
data as the trigger times,
during 2000 to 2005. The top panel presents the number of triggers within each hourly time bin of the superposed epoch analysis. 532 events
were identified in the ACE solar wind data corresponding to times at which the V
y
component of the solar wind increased by more than
75 km s
−1
in 5 h. Such an enhancement is indicative of the arrival of a high-speed solar wind stream at Earth. The middle panel contains the
median response of the V
y
component of the solar wind as measured by the ACE spacecraft. In this, and subsequent plots, the median
response is represented by a solid line, the standard error in this median as a grey area around the line while the dashed lines and the dotted
lines correspond to the 95% and 99% levels of the dataset respectively. These percentile levels were calculated by repeating the analysis
many times using random trigger times and determining the levels in each time bin that contained 95 and 99% of the data points. The lower
panel contains the median response in the magnitude of the interplanetary magnetic field, B
t
.

4.4. Lightning and thunder days
The top panel of figure 4presents the median daily response
in lightning rates as measured by the ATD system of the UK
Met Office. Since the meteorological conditions necessary to
produce lightning are not always present, these data are
dominated by times for which there was little or no lightning.
In order to calculate a meaningful median, these zero values
were not included in our calculations by requiring a minimum
mean lightning rate of one stroke per hour. This is not
unreasonable since it is just recognition of the fact that con-
vective instability must be present for lightning to occur. This
reduces the number of data points included in each time bin of
the composite analysis to a mean value of 135 ± 2 (of 405
trigger events) with no bin containing fewer than 93 data
points, ensuring that any median value is taken from a dis-
tribution containing sufficient points that the median would
not be influenced by outliers. There is a significant
enhancement in median lightning rates starting 10 d before
t= 0 compared with median lightning rates from earlier times.
This enhanced lightning rate decays back to pre-event levels
over the next 50 d. While the lightning rates remain enhanced
for many days, there is a variation of around 8 d within these
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
6
Figure 2. The top panel contains the median total solar irradiance (TSI) measured around the times of the high-speed solar wind streams
arriving at Earth. The middle panel contains the median response in sunspot number (SSN). The third panel contains the median response in
the Mg II emission.

enhanced values and a relatively low response from t=0d to
t= 5 d. The mean lightning rate for the 40 d before t=0 is
321 ± 17 while the mean lightning rate for the 40 d after t=0
is 422 ± 30. A spectral analysis of the daily ATD counts
revealed no significant periodicities in the original data.
Because operation of the lightning detection system
depends on the propagation properties of the ionosphere,
which may also be influenced by the solar changes, we also
consider a less sensitive but highly robust measure of thun-
derstorms, manual acoustic detection of thunder on ‘thunder
days’. If thunder has been heard by an observer within a 24 h
period, a value of 1 is recorded while the absence of thunder
over the same period is recorded as 0. Such a binary mea-
surement contains less information than a count of lightning
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
7
Figure 3. Median response in galactic cosmic ray flux (top panel) as measured by the ground-based neutron monitor at Oulu, Finland. The
second, third and fourth panels present median proton flux measurements from the GOES satellite dataset for three energy channels; >1 Mev
(top), >30 Mev (middle) and > 100 Mev (lower). The median response in each parameter is represented by a solid line, the standard error in
this median as a grey area around the line while the dashed lines and the dotted lines correspond to the 95% and 99% levels of the dataset
respectively. These percentile levels were calculated by repeating the analysis many times using random trigger times and determining the
levels in each time bin that contained 95 and 99% of the data points.

strokes. The advantage of using such data is that it does
provide an independent measure of the presence of thunder
storms. Since a thunder day is a record of thunder being
heard, it is potentially susceptible to other noises, such as
explosions or nearby traffic, being wrongly identified as
thunder. Such errors are likely to be localized and can be
minimized by taking a median value across a number of
stations and by setting a threshold to ensure that the results are
not dominated by the measurements where little or no light-
ning is occurring. This threshold was set at 3% of the
observed range of values to allow a similar number of (though
not necessarily the same) events on average to be recorded as
was seen in the daily medians of ATD lightning data (top
panel, figure 4). The median fraction of stations on which
thunder was heard at around 450 Met stations situated in
marine and land locations across the UK is shown in the
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
8
Figure 4. The top panel contains the median daily lightning rate over the UK as measured by the arrival time difference (ATD) system of the
UK Met Office, during 2000–2005. The lower panel shows the median response in thunder days recorded at all UK Met Stations scaled by
the number of stations making manual measurements each day. The median response in each parameter is represented by a solid line, the
standard error in this median as a grey area around the line while the dashed lines and the dotted lines correspond to the 95% and 99% levels
of the dataset respectively. These percentile levels were calculated by repeating the analysis many times using random trigger times and
determining the levels in each time bin that contained 95 and 99% of the data points.

second panel of figure 4. Since the number of manned stations
is expected to have varied throughout the interval being stu-
died, thunder day counts were normalized by the number of
stations known to have made manual thunder day observa-
tions each day. The number of thunder days after t=10 is
clearly enhanced compared with the number of thunder days
prior to t= 10, with an encouraging agreement between the
most significant peaks (exceeding the 99th percentile) and the
peak lightning rates seen in the ATD data. As the thunder day
data effectively records the presence of lightning with suffi-
cient energy to generate audible thunder (Mackerras 1977), it
provides an independent measure compared with the radio
detection of lightning rates used by the ATD system. The
mean fraction of stations recording thunder in the 40 d before
t= 0 was 0.0424 ± 0.001 compared with 0.0445 ± 0.002 for
the 40 d after t= 0. The significance of the enhancements in
lightning and thunder day rates was investigated by con-
ducting Kolmogorov−Smirnov tests on these distributions
over 40 d before and after t= 0. This test determines whether
the two distributions represent subgroups from the same
population or whether they come from statistically distinct
distributions. One additional advantage of this test is that it is
independent of the shape of the event distribution being
investigated. For both the ATD data and the thunder day
distributions, values in the 40 d after t= 0 were significantly
(to confidence levels >99.9%) different from the distributions
of the same parameters in the 40 d before t= 0. Using hourly
triggers to identify responses in daily data can result in
multiple-selection of response data in a given time bin,
effectively weighting the response by the longevity of the
solar wind stream. Repeating the analysis for hourly lightning
data generates a similar, if noisier, response which passes the
KS test at confidence levels far in excess of 99.9%. Such a
reanalysis is not possible for the thunder data since it is a
daily measurement. There is a sufficiently large number of
trigger times within the epoch under consideration that it is
highly likely that a small number of lightning data points
corresponding to the same trigger time will appear in several
time bins of the composite analysis. The top panel of figure 1
shows that while most trigger times are assembled at time = 0,
there are a small number of triggers distributed throughout the
composite time frame being considered. The fact that the
lightning distributions before and after time = 0 pass the
Kolmogorov−Smirnov test despite this cross-contamination
of points strengthens the statistical significance of this result.
Though the selection of solar wind triggers is indepen-
dent of any seasonal changes at Earth, they could nevertheless
introduce a seasonal bias into the analysis of lightning data if
they are not evenly distributed throughout the year. Lightning
rates increase dramatically in spring and decline rapidly in
autumn. Any bias in the number of trigger events between
spring and autumn could therefore potentially introduce a bias
throughout the 121 d time period of the superposed epoch
analysis. This is indeed the case for the above analysis, with
more trigger events occurring in the spring (132) than in the
autumn (100) months. In order to investigate the possibility
that the observed increase in lightning rates was due to a
seasonal bias, we repeated the analysis for triggers occurring
during the summer months only and further restricted the
selection of triggers to ensure that only one trigger per day
could contribute to the analysis. Given that the width of the
superposed epoch analysis window is of the order of four
months, it would still be possible, despite the restriction in
trigger times, for data outside of the summer months to be
convolved in the final result. In order to discount this possi-
bility, no data falling outside the summer months were used
when calculating the median values in each daily time bin in
the restricted superposed epoch analysis. The results of this
analysis are presented in figure 5. It can be seen that the
responses in both daily lightning and thunder day data are
preserved and that the thunder day response is in fact more
pronounced. As before, these responses were tested using a
Kolmolgorov−Smirnov test to see if the median values for the
40 d either side of t= 0 were drawn from different distribu-
tions. Both passed at ≫99.9% (≪0.1% probabilities that
these results occurred by chance). The mean values also
passed a two sample T-test at 99.1% and ≫99.9% confidence
levels (0.9% ≪0.1% that these results occurred by chance) for
lightning and thunder data respectively.
While these distributions were calculated from a much
smaller number of triggers (32), the presence of lightning
during the summer months ensured that a high proportion of
data in each time bin contained lightning (with a mean of
17.7 ± 0.3).
5. Discussion
Having determined that the arrival of fast solar wind streams
at Earth is associated with a subsequent increase in lightning
rates, some possible mechanisms can be considered. Figures 4
and 5present evidence that lightning and thunder rates are
enhanced following the passage of an interaction region over
similar timescales to the observed depression in GCR fluxes
reaching Earth. This appears to contradict the results of earlier
studies that have indicated an anti-correlation between sun-
spots and thunder days (Pinto et al 2013). While sunspots
themselves are merely a convenient proxy for solar activity,
the mechanism for the observed anti-correlation is thought to
be through the modulation of the HMF throughout the solar
cycle. At sunspot maximum, the HMF is stronger, providing
greater shielding from energetic GCRs at Earth. With GCRs
implicated in the triggering of lightning (Roussel-Dupré
et al 2008; Gurevich and Zybin 2005), this provides a
mechanism by which sunspot number and thunder days
would be anti-correlated over solar cycle timescales. In con-
trast, our study, taken from the declining phase of a single
solar cycle, considers the response in lightning rates to the
arrival of high-speed solar wind streams at Earth. These co-
rotating solar wind streams are associated with a localized
enhancement of the HMF and a concomitant drop in GCR
flux that ought to, at face value, have the same effect as solar
cycle variations. However the physics of these short timescale
events is very different. The enhancement of the HMF is at
the fast/slow stream interface in the solar wind, resulting in a
relatively small (though long-lived) ∼2% decrease in GCR
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
9

flux. An explanation may be found in the enhancement of
lower energy protons of solar origin measured in bands
between > 1 Mev and > 100 Mev also associated with these
high-speed streams. For those channels with higher energies
(>30 Mev) these fluxes are enhanced to around 9% above pre-
event levels for 40−50 d after t= 0. Of these, only higher
energy particles (>500 Mev) are capable of penetrating the
atmosphere far enough to directly modulate atmospheric
conductivity in the lower atmosphere (e.g. Calisto et al 2012;
Cliver 2006). The evolution in particle distribution seen in the
energy channels presented (particle fluxes starting earlier and
remaining elevated for longer as the energy threshold
increases) is likely to continue beyond the highest detection
threshold available on the GOES spacecraft. Furthermore,
these particles, being more localized and of lower energies
that GCRs, can be significantly deflected by the Earth’s
magnetic field, modulating their spectrum further. This could
explain why the modulation of lightning rates begins before
the arrival of the high-speed stream at Earth and peaks
between 12 and 18 d afterwards. Particles > 500 Mev have
Environ. Res. Lett. 9(2014) 055004 C J Scott et al
10
Figure 5. Median lightning rates (top panel) and thunder days (lower panel) in response to a restricted set of 36 solar wind trigger occurring
during the months of June−August. In order that any seasonal bias does not influence the median values in each time bin of the superposed
epoch analysis, all data from times outside this strict seasonal window were excluded before median values were calculated.

sufficient energies to modulate the atmospheric conductivity
above and within thunderclouds though they do not have
sufficient energy to be detected at ground level. If these
particles are subsequently responsible for the observed mod-
ulation in lightning rates it would explain why this result is in
apparent contradiction to earlier studies which found an anti-
correlation between sunspot number and thunder days. Stu-
dies carried out on solar-cycle timescales will be detecting the
modulation of GCRs by the HMF. Enhancements of this field
during times of high solar activity (large sunspot number) will
shield the Earth from GCRs, reducing the rate at which they
could trigger lightning. In our study however, the ∼2%
decrease in GCR flux is accompanied by a 9% increase in the
flux of SEPs, the higher energy flux of which could penetrate
the atmosphere far enough to trigger lightning in the same
way that GCRs are thought to do (e.g. Gurevich and Kar-
ashtin 2013). Indeed, the sharpest drop in GCR flux around
t= 0 is accompanied by a relative drop in lightning rates,
indicating that the total lightning rate is in fact a convolution
of triggering by two distinct populations of particles. While
the exact mechanism by which this occurs is still unknown,
this study demonstrates that solar wind and atmospheric
conditions on these small timescales are very different from
the long-term average. It is perhaps not surprising therefore
that the response in lightning rates to co-rotating solar wind
streams differs from that over a solar cycle.
While a small 27 recurrence can be seen either side of
t= 0 in the median response in GCR flux (top panel, figure 3)
no such recurrence is apparent in the lightning data (top panel,
figure 4). While the arrival times of solar wind streams at
Earth can be determined with some precision (figure 1), the
subsequent elevation of SEPs lasts for tens of days. If this
elevated particle flux is indeed responsible for the observed
modulation of lightning rates, any 27 d recurrence would be
blurred out in the median values of elevated particle flux and
lightning rate.
Some further inferences are possible from the upgrade of
the ATD lightning detection system to ATDnet which
occurred in 2007 following our analysis period, which led to a
much more sensitive lightning detection network for
meteorological purposes. The number of lightning strokes
detected increased by an order of magnitude, preventing
continued detection of the solar wind effects observed
between 2000 and 2005. This implies that, in the earlier
period considered here, it may have been the magnitude of
individual lightning strokes that was increased. Such a shift
would bring more lightning strokes above the detection
threshold of the ATD system and appear as an increase in the
number of strokes. The lack of response in later, more sen-
sitive ATD data is also consistent with a change in the
spectrum of lightning magnitude. In the more recent ATD
data the detection threshold is much lower, allowing a greater
number of smaller lightning strokes to be detected. Without
any record of lighting stroke magnitude however, this cannot
be tested with the current dataset. A worthwhile future study
would be to repeat this analysis using data from a global
lightning network such as the World Wide Lightning Loca-
tion Network (Rodger et al 2005).
It is, however, unlikely that the relatively small changes
observed in TSI, SSN and Mg II index (figure 2) could in
themselves explain the increased lightning rates through
direct modulation of solar irradiance. Furthermore, if irra-
diance effects were the origin of the changes observed, the
much greater variability apparent in these parameters
throughout the eleven year solar activity cycle would be
expected to modulate the lightning rates over a far greater
range than has been observed.
Clearly the existence of suitable weather conditions
allowing thunderstorms to form is a pre-requisite for mod-
ulation of lightning. The approximately 8 d periodicity seen in
peak lightning rates after t= 0 is more comparable with the
timescales of weather systems than individual storms though
the cause of such a period in our observations remains
unexplained. The data presented above does provide evidence
that, if weather conditions are suitable to generate active
convection and electrified storms, lightning rates appear to be
modulated by the SEPs associated with high-speed solar wind
streams. Since these high-speed streams co-rotate with the
27 d solar rotation, their arrival at Earth is predictable in
advance. This, coupled with an increasing understanding of
energetic particle effects on the atmosphere, makes it worth-
while pointing out the potential benefits to forecasting
hazardous weather.
Acknowledgements
The authors would like to thank the UK Met Office for use of
data from their ATD network and observing stations which
were made available via the British Atmospheric Data Centre,
the Sodankyla Geophysical Observatory for the use of the
Oulu cosmic ray data (http://cosmicrays.oulu.fi), D J McCo-
mas (Southwest Research Institute) and N Ness (Bartol
Research Institute) for the use of ACE data which were made
available via CDAweb (http://cdaweb.gsfc.nasa.gov). The
thunder day data were obtained from the Met Office Inte-
grated Data Archiving System (MIDAS) land and marine
surface stations (1853-current), made available by the NCAS
British Atmospheric Data Centre (http://badc.nerc.ac.uk).
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