DECEMBER 2000
WILLIAMS ET AL.
2223
Global Lightning Variations Caused by Changes in Thunderstorm Flash Rate and by
Changes in the Number of Thunderstorms
E. WILLIAMS, K. ROTHKIN,
AND
D. STEVENSON
Parsons Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts
D. BOCCIPPIO
NASA Marshall Space Flight Center, Huntsville, Alabama
(Manuscript received 8 October 1999, in final form 10 April 2000)
ABSTRACT
Global lightning activity is highly variable on many timescales. This variability is attributable to changes in
the flash rate per thunderstorm, the number of thunderstorms, or a combination. The Tropical Rainfall Measuring
Mission provides lightning observations from the Optical Transient Detector (OTD) and the Lightning Imaging
Sensor (LIS) in space. Both are used to examine the response of these parameters to thermodynamic forcing of
deep convection on the diurnal and annual timescales. On both timescales, the changes in the number of storms
dominate the variations in total lightning activity. On the diurnal timescale, there is evidence that the mean flash
rate may vary with cloud buoyancy, peaking in early afternoon and declining in late afternoon, but the contribution
of number of thunderstorms is 2–3 times greater than the mean storm flash rate. On the annual timescale, almost
all of the total lightning response is due to changes in the number of storms, with a negligible contribution from
flash rate. Evidence is presented that the LIS/OTD ‘‘area’’ is a meaningful objective identifier for a thunderstorm,
despite known limitations in this data product.
1. Introduction
The lightning flash rate and the total flash count are
frequently used measures of the electrical activity of
thunderstorms. Flash rate is a widely recognized indicator of the strength of the storm updraft (Baker et al.
1995, 1999), with the largest flash rates occurring in
severe storms (Williams et al. 1999). In climate studies
and in the use of lightning and the global circuit as a
diagnostic for global change (Williams 1992; Price
1993; Jayaratne 1993; Markson and Lane-Smith 1994;
Petersen and Rutledge 1996; Fullekrug and FraserSmith 1997; Watkins et al. 1998; Reeve and Toumi
1999; Satori and Zieger 1999; Goodman et al. 2000),
one is concerned with the response of flash rate and
total flash count to external forcing. If, for example, the
thermally forced conditional instability of the atmosphere increases, does the mean flash rate per storm
increase, or do the numbers of storms increase, or is the
response a combination of these effects?
Attempts to answer this basic question with certain
Corresponding author address: Earle Williams, Parsons Laboratory, Massachusetts Institute of Technology, Bldg. 48-211, Cambridge, MA 02139.
E-mail: earlew@ll.mit.edu
q 2000 American Meteorological Society
global datasets are faced with problems. First and foremost, some objective measure of ‘‘thunderstorm’’ is
needed. For isolated airmass thunderstorms and the isolated tropical ‘‘hot towers’’ envisioned by Riehl and
Malkus (1958), with sizes on the order of the tropopause
height, this identification is often straightforward. In
radar displays of mesoscale convective activity, however, in which radar reflectivity can be contiguous over
horizontal scales that are large in comparison with the
tropopause height, thunderstorm cells are far less easily
identified. Even in these more complicated situations,
lightning activity is far more compact, because it depends so strongly on the vertical development of the
convection (Williams 1985), which is more concentrated
than the radar reflectivity at lower levels. In this study,
an objective measure for thunderstorm is adopted based
on optical measurements of lightning activity.
The second challenge toward addressing the response
of global lightning activity to thermodynamic forcing
with global datasets is access to a measure of thunderstorm electrical activity. The thunder day, the traditional
meteorological measure of lightning, is wholly inadequate for this task, because it cannot distinguish days
with a single lightning flash and days with tornadic supercells. Flash counters (e.g., Mackerras et al. 1998)
and ground flash networks suffer from limited coverage,
particularly in tropical continental zones. The back-
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JOURNAL OF APPLIED METEOROLOGY
ground Schumann resonance intensity has been used in
the climate context (Williams 1992; Nickolaenko and
Rabiniwicz 1995; Satori and Zieger 1996; Fullekrug and
Fraser-Smith 1997; Nickolaenko et al. 1998; Anyamba
et al. 2000), but in this measurement the waveforms of
individual lightning flashes overlap, preventing a discrete flash count. Furthermore, the integrated source parameter one extracts by this method, a vertical charge
moment squared per unit time (Heckman et al. 1998),
does not enable a distinction between 10 storms making
1 flash per minute and one storm making 10 flashes per
minute.
Other datasets are better suited to address this issue.
Foremost among these are the new optical measurements of lightning from space with the Optical Transient
Detector (OTD) and the Lightning Imaging Sensor (LIS;
Christian et al. 1999; Boccippio et al. 2000b). These
observations enable objective measurements of thunderstorms and provide flash-rate information in both the
Tropics and extratropics. Furthermore, these global observations provide access to lightning’s response to forcing on the diurnal and the annual timescales. For climate
studies, longer timescales are obviously of interest. Our
strategy is to understand the physical response on two
widely separated timescales for which the origin of the
forcing is well understood.
2. OTD and LIS observations
The OTD has been operating in low Earth orbit since
April 1995. It was intended as a prototype for the LIS
optical sensor on the Tropical Rainfall Measuring Mission satellite. The details of the instrument and the measurement strategy are described in other publications
(Christian et al. 1999) and will not be repeated here. It
is appropriate to point out that the typical observation
time of the instrument over any given location is 2–3
min, an adequate interval to determine an instantaneous
thunderstorm flash rate. OTD sees latitudes up to and
beyond 6708, which enables observation of the contribution of the extratropics to the global circuit. The LIS
sensor has a shorter observation time of 90 s and sees
between 6358, a more restricted range of latitude
(Christian et al. 1999).
The OTD orbit precesses slowly in relation to the Sun
(the angle defined by Sun–satellite–Earth changes slowly), taking 55 days to return to its original position.
Consequently, 55 days are required to sample adequately the whole Earth at all local times of day (Christian
et al. 1999). Our seasonal analysis thus relies on two
55-day ‘‘windows’’ centered on 21 January 1996 and
21 July 1996. The LIS sensor requires approximately
49 days to return to its original position relative to the
Sun and the Earth, though the manual (Boccippio et al.
1998) recommends using a 100-day window. Because
LIS has a much smaller field of view than does OTD
but has a higher detection efficiency, we chose to use
two cycles, because it would give similarly sized da-
VOLUME 39
tasets for each. Because 100 days is longer than a calendar season, seasonal variations will tend to be
smoothed out in LIS data. Consequently, we use both
OTD and LIS to analyze diurnal variation but use only
OTD to study the difference between January and July.
LIS was not launched until late 1997, so that our
antialiasing window is for 100 days centered on 21 January 1998, which is not the same year as for OTD. We
chose an earlier OTD window because its sensor turns
off for increasingly long periods over time, always near
local noon and midnight (Boccippio et al. 2000a). A
1998 analysis window would have too many long gaps
for uniform diurnal analysis.
In addressing the response of total lightning and lightning flash rate from a ‘‘storm,’’ one needs an objective
observable for storm. As mentioned in the introduction,
storm is an ill-defined quantity in the multiscale realm
of turbulent atmospheric convection. In this study, multiple measures of storm have been considered to determine sensitivity to these definitions (further tests of the
behavior of these multiple measures for storm are considered in the next section).
One measure that may conform to the isolated thunderstorm in meteorology (a deep convective element
whose depth is comparable to its height and whose overall lifetime is on the order of 1 h) is the OTD/LIS ‘‘area’’
quantity. An ‘‘area’’ is defined solely in terms of optically defined flashes. For OTD, the centroid of every
new flash not within 22 km of a previous or simultaneous flash initiates an ‘‘area,’’ and any flash within 22
km (along latitude and longitude lines) of the initial flash
is then assigned to an existing ‘‘area.’’ Data processing
limitations (flagged in the OTD data file) may cause this
clustering rule to be violated up to 20%–30% of the
time in the OTD data (based on these flags). LIS areas
are defined similarly; any flash not within 16.5 km of
a previous or simultaneous flash initiates an area.1 Processing limitations do not affect application of the LIS
clustering algorithm. Because the typical OTD/LIS view
time is much shorter than a thunderstorm lifetime, no
lifetime is assigned to an ‘‘area.’’ The 22-km scale (16.5
for LIS), which admittedly is comparable to the pixel
size of the measurement (8–13 km for OTD, 3–6 km
for LIS) was chosen to bound the size of the majority
of isolated thunderstorms.
The second measure of storm, which is more removed
from the meteorological entity, is a 28 3 28 patch in
latitude–longitude observed by LIS/OTD. Such patches
are still substantially smaller than the nominal 1300 km
3 1300 km footprint of the OTD sensor (or 550 km 3
550 km for the LIS sensor) but considerably larger than
the isolated thunderstorm. Each location is given 24
possible time slots, one for each hour of the local solar
1
We are using version 4 of the LIS dataset, the most current released version. Version 5 will use a different area grouping algorithm.
DECEMBER 2000
WILLIAMS ET AL.
2225
day. If any lightning is observed in the 28 3 28 region
during each overpass, it is a storm. It may help to think
of a storm patch as a lightning hour analogous to thunder
day. There are 388 800 possible patch hours (24 h 3
16 200 28 3 28 patches on the Earth), of which 296 177
(98%) were ever in OTD’s view and 168 516 (43%)
were ever in LIS’s view. For OTD, only 32 687 (or 11%
of patches in view) had any lightning; for LIS only
18 045 (11% of patches in view) had any lightning.
Because of the size of a patch, it is often the case
that there are two or more areas that appear in a single
patch. It also is common to find more than one distinct
thunderstorm within 48 400 km 2 of each other in other
datasets. With more than one storm flashing simultaneously within one patch observation, we will calculate
a higher flash rate, in part combining the effect of number of storms with that of flash rate. This effect gives
reason to prefer the ‘‘area’’ measure should it prove
reliable.
The behavior of ‘‘areas’’ and 28 3 28 patches has
been examined on both the diurnal and annual timescales. The results for each timescale are covered in
separate sections below.
3. Results: Diurnal timescale
As stated previously, both the OTD and the LIS sensors are used in the diurnal analysis. The derived values
from the two sensors may differ for four reasons.
FIG. 1. The diurnal variation of total flash count and land flash
count for (a) OTD and (b) LIS observations.
1) Detection efficiency is different for the two sensors,
and we do not correct for it.
2) The sensors are observing different spatial domains.
3) The LIS and OTD viewtime spectra are different
(much broader for OTD than for LIS), which leads
to different structures for the two observed flash-rate
distributions. For both datasets, we discard observations that were not in view for at least 85 s, but
that does not make them intercomparable.
4) The two datasets use different clustering algorithms
to determine boundaries of each flash and each area.
This difference in algorithms can lead to systematic
differences in flash rates.
analyses, we did not separate land areas from ocean; the
interested reader is referred to Boccippio et al. (2000b).
OTD observations are preferable to LIS observations
in two respects: the OTD instantaneous field of view
(FOV) is 5.6 times greater than that of the LIS, and its
orbital coverage extends substantially into the extratropics. The first comparison guarantees that more flashes, more areas, and more patches will be seen by OTD
than by LIS for fixed total observation times. This fact
has important implications for the variance of the satellite measurement of flash rate—already a highly variable parameter. The mean flash rate for each ‘‘area’’
was computed by taking the total number of flashes
composing that ‘‘area’’ and dividing by the time that
spot was in the sensor FOV. The mean flash rate for a
28 3 28 patch was computed by taking the total number
of flashes in that patch (220 km 3 220 km at the equator)
and dividing by the time that patch was in the FOV. As
the sensor moves across the earth, occasionally the
whole patch is not in view. We do not correct our counts
or flash rates for spatial incompleteness, which means
that our estimated counts and rates are low. This bias
should be equally true for all times of day and year and
for all locations, so it is a uniform undercount and will
not affect our conclusions about the relative influence
of number of storms and flash rates.
Figure 2a shows the flash-rate distribution functions
for OTD ‘‘areas’’ and 28 3 28 patches, illustrating the
The diurnal variation in the OTD flash rate can be directly compared with the diurnal variation in the LIS
flash rate, and this comparison is the subject of this
section.
To determine a collective diurnal variation, all observed ‘‘areas’’ and 28 3 28 patches with lightning were
binned in local solar time (regardless of location). The
diurnal variations of total flashes and all flashes over
land are shown in Figs. 1a (OTD) and 1b (LIS), and
the different numbers of land and ocean storms appear
in Table 1. The large peak-to-trough variation in total
lightning is dominated by land and is otherwise consistent with earlier local analyses [Williams and Heckman (1993) and references therein]. Therefore, for most
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FIG. 2. Distribution of flash rates for (a, top) OTD and (b) LIS.
low mean flash rate of about 1.5 flashes per minute (fpm)
for ‘‘areas’’ and 2.4 fpm for 28 3 28 patches. The larger
mean in the latter case is due to the larger footprint of
patches relative to ‘‘areas.’’ Each distribution has a long
tail at higher flash rates, and flash rates exceeding one
flash per second (60 fpm), near the severe-storm threshold, are exceedingly rare, as found in Williams et al.
(1999). The apparent cutoff at low flash rates is the
direct result of the limited viewing time (i.e., 1 flash in
a typical view time of 3 min is 0.33 fpm).2
Figure 2b shows the same distributions for the LIS
flash rates by ‘‘area’’ and 28 3 28 patch. The mean flash
rate for a LIS ‘‘area’’ is 2.6 fpm, and the mean ‘‘patch’’
flash rate is 4.9 fpm. LIS flash rates are higher than
those of OTD in part because the LIS view time is half
2
Because the OTD sensor grid is not always aligned with the
direction of its travel, some spots on the ground are in view for longer
than 3 min, allowing for real flash rates of less than 0.33 fpm (no
less than 0.33 divided by Ï2).
that for OTD (meaning lower flash-rate storms simply
are not observed), in part because LIS has a higher
detection efficiency, and in part because LIS sometimes
splits a true lightning into two or more ‘‘flashes.’’ The
spikes in the distribution result from sampling—it observes integer flash counts in a time window that is often
90 s. If the true flash rate were one flash in 100 s, or
one flash in 80 s, it would appear to be 1/90 most of
the time. More obvious spikes in the LIS distributions
arise because the sensor footprint is square to the direction of its movement across the earth, so observation
times do not vary much. The OTD sensor rotates as it
travels, making for a large variation of observation
times, giving the appearance of more continuous flashrate measurements (Boccippio et al. 1998).
The computed results for the diurnal variation of flash
rates and numbers of storms, using both 28 3 28 patch
and ‘‘area’’ measures, are shown in Fig. 3. Figures 3a
and 3b (top two) contain OTD data for both January
and July (110 days together). In Fig. 3a, the 28 3 28
patch flash rate declines from midnight until 1100 (local
DECEMBER 2000
WILLIAMS ET AL.
2227
FIG. 3. Diurnal variation of flash rate and number of storms. (a) OTD 28 3 28 patch measure of storm, (b) OTD area measure of storm,
(c) LIS patch measure, (d, bottom right) LIS area measure. Flash rates are variable, though some diurnal variation can be seen for all curves
but LIS patches.
solar time) after dawn, and then rises abruptly to peak
in midafternoon (1500 local solar time) before declining
again through the afternoon. The flash rate for ‘‘areas’’
(in Fig. 3b) is similar but not identical to the behavior
for patches. The amplitude variation is greater for 28 3
28 patches than for ‘‘areas.’’ The overall mean is about
1.6 fpm, which is generally consistent with local thunderstorm observations (e.g., Williams et al. 1989). The
maximum area flash rate occurs later in the diurnal cycle
for ‘‘areas,’’ and the flash rate declines more rapidly for
patches, peaking during the late afternoon near sunset.
For OTD patches, the flash rate is 2.1 times as large at
1500 (3.3 fpm) than at 1100 local solar time (1.4 fpm).
Caution should be used in interpreting this finding, because the standard deviation of flash rate for any given
hour is at least 3 fpm; there is clearly a difference beTABLE 1. Different measures of land and ocean storms.
Instrument
OTD
OTD
LIS
LIS
Measure
Ocean
Land
Mean no. of storm patches in 110 days
per 28 3 28 patch hour
Mean no. of OTD areas in 110 days per
28 3 28 patch hour
Mean no. of storm patches in 100 days
per 28 3 28 patch hour
Mean no. of LIS areas in 100 days per
28 3 28 patch hour
0.08
0.29
0.12
0.58
0.10
0.53
0.13
0.76
tween morning and afternoon, but the magnitude of the
difference and the times of peak and trough are variable
and should be calculated over a much larger data interval. The diurnal variation of total flashes in Fig. 1a
shows a substantially greater amplitude variation than
either of the two diurnal variations of flash rate in Figs.
3a and 3b.
The diurnal variation of LIS data is similar, shown
in Figs. 3c and 3d (the bottom two). The LIS area flash
rate declines (from about 3.2 to 1.9 fpm) from 2000 to
0700 local solar time then rises to a peak of 3.1 fpm at
1500 local solar time. The difference between the times
of peak for OTD and LIS is very likely the result of
the large variance in the LIS observations, as discussed
earlier. The typical standard deviation in the LIS determination of mean flash rate is nearly twice the mean
value: 2.6 6 4.9 fpm.
The observed differences in flash rate between ‘‘areas’’ and patches is tentatively explained as follows.
Because the 28 3 28 patch is large in comparison with
the size of a thunderstorm, it is likely that more than
one true thunderstorm resides in each storm patch, generating lightning contemporaneously. As supporting evidence, each patch observation often contains more than
one ‘‘area.’’ If so, the patch measure confounds the
number of true thunderstorms with the flash rate of each
storm within the larger patch, as discussed in the introduction.
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FIG. 4. Diurnal variation of flash rate for different observation
scales: (a) OTD and (b) LIS. The 4 3 4 area is not possible for LIS
because of the more limited field of view with this sensor.
These ideas are further substantiated by multiplescale observations on the diurnal timescale. The OTD
results are shown in Fig. 4a. Here we consider the total
lightning flash rate for patch observations of various
sizes (48 3 48, 28 3 28, and 18 3 18) and including the
OTD ‘‘area’’ at the smallest scale. A consistent and
expected downward trend is noted in the mean flash
rate. The diurnal amplitude variation of mean flash rate
can be summarized by the ratio of the maximum to
minimum flash rate over the day. This ratio decreases
with storm size, from the patch sequence to ‘‘area.’’
This convergent behavior lends credence to the selection
of ‘‘area’’ as the approach most consistent with other
definitions of thunderstorm. The characteristic size of
thunderstorms is widely regarded to be smaller than a
18 3 18 (110 km 3 110 km) patch, and the ‘‘area’’
measure is smaller as well. Similar results for the LIS
are shown in Fig. 4b. The LIS sensor is too small to
measure 48 3 48 patches, because they almost never
would be completely in view; however, Fig. 4b shows
the scaling of LIS storm sizes as cleanly as those of
OTD, which makes the LIS ‘‘area’’ another credible
proxy for thunderstorm. We reiterate that there is insufficient reason to think that OTD ‘‘areas’’ and LIS
‘‘areas’’ are directly comparable, though they both appear to be good proxies for storms for this purpose.
Figure 3 also shows the diurnal variation in the number of storms, where storm is identified with an ‘‘area’’
or a 28 3 28 patch with lightning. The shape of the
VOLUME 39
diurnal variation of storm counts is very similar to that
of total flashes, shown in Fig. 1 and is unlike the flashrate curves in Fig. 3. The amplitude variations between
peak and trough are similarly strong for numbers of
storms and numbers of flashes and are much more pronounced than the flash-rate curves.
The OTD peak–trough diurnal variation for the number of 28 3 28 patch storms (Fig. 3a) is interestingly
only about a factor of 4, less dramatic than that for
number of ‘‘areas’’ (Fig. 3b) or flashes (Fig. 1a). Because the 28 3 28 flash rate showed some diurnal variation similar to the curve for number of flashes, this
result lends further evidence that the patch measure for
storm does not cleanly distinguish between number of
thunderstorms and flash rate per thunderstorm. The
overall amplitude variation of flash rate is appreciable
but still smaller than the diurnal variation in the number
of ‘‘areas,’’ a quantity that clearly peaks later in the
afternoon. Further comparison between Figs. 3b and 1a
shows that the diurnal variation of the total number of
‘‘areas’’ still dominates the contribution of ‘‘area’’ flash
rate in determining this large diurnal variation of total
flashes. The peak–trough flash-rate ratio is about 1.7 for
LIS (Figs. 3c and 3d). Flash rate of storm patches peaks
well before the number of storm patches, though the
latter curve tracks the flash count diurnal variation much
more closely.
4. Results: Annual timescale
Numerous observations with both optical (Orville and
Henderson 1986) and Schumann resonance methods
(Fullekrug and Fraser-Smith 1997; Satori et al. 1999)
support the idea that the global lightning activity is at
a maximum in Northern Hemisphere (NH) summer and
a minimum in NH winter. The seasonal behavior of the
‘‘direct current’’ (dc) global circuit appears to follow
the same behavior in phase but with reduced amplitude
variation (Adlerman and Williams 1996). It is increasingly apparent that this annual cycle is strongly influenced by the extratropics and by the pronounced land–
ocean asymmetry that is manifest primarily in the extratropics (Williams 1994); this asymmetry is well illustrated in global maps of integrated OTD activity (not
shown). The earth’s mean temperature is highest in July
and lowest in January (Jones et al. 1999). The OTD
flash analysis on the annual timescale has therefore centered on two months: January and July. Table 2 summarizes the relevant quantities for both ‘‘areas’’ and 28
3 28 patches.
The general findings for the annual timescale are different from the diurnal results: the variation in number
of storms (by either measure) completely dominates
over mean flash rate in controlling the factor-of 2 annual
variation in total global lightning between summer and
winter months (Boccippio et al. 2000b). For example,
the number of 28 3 28 storm patches detected by OTD
in July (27 959) is nearly double the number for January
DECEMBER 2000
TABLE 2. Annual variation in the number of storms and the storm
flash rate (fpm). Differences within OTD between a 55-day interval
centered on 21 Jan 1996 and a 55-day interval centered on 21 Jul
1996 for both OTD areas and 28 3 28 patches.
LIS/OTD areas
Flash
No. areas rate
Jan OTD
Jul OTD
23 879
36 590
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WILLIAMS ET AL.
1.3
1.5
28 3 28 patches
No.
28 3 28
Flash
rate
Total
flash
count
14 313
27 959
2.3
2.2
90 351
180 188
(14 313), but the mean ‘‘area’’ flash rates agree to within
5% (2.2 vs 2.3 fpm). A self-consistent picture is presented by the other numbers in Table 2.
5. Discussion and conclusions
The use of optical measurements to count thunderstorms has shown that the OTD/LIS ‘‘area’’ behaves
consistently with other plausible metrics. The LIS/OTD
mean flash rates (1–3 per minute) are self consistent and
are also in line with the early estimates (Marriott 1908)
that figured strongly in initial determinations of the
global flash rate (Brooks 1925).
The distinction between the contributions of flash rate
and number of storms to total lightning production is a
subtle but important one and has been shown to be an
achievable goal with optical observations from the two
satellites. The comparison of different measures for
storm, including a test of diurnal behavior with different
observation scales, has shown that the ‘‘area’’ parameter
is a reliable metric.
On the diurnal timescale, both flash rate and number
of storms make significant contributions to the variation
of total lightning. The behavior of flash rate sheds new
light on the link between conditional instability (i.e.,
cloud buoyancy) and lightning. Earlier analyses (Price
1993; Markson and Lane-Smith 1994) emphasized the
lag in dc global circuit response from the time of maximum surface air temperature. The OTD results in Fig.
3 show a tendency for flash rate to peak 1–3 h earlier
in the diurnal cycle than do the number of storms and
the total lightning. This result may be interpreted as
evidence that flash rate follows more closely in phase
with cloud buoyancy and Convective Available Potential Energy (CAPE), because wet bulb potential temperature, a good proxy for CAPE on the diurnal timescale (Williams and Renno 1993), is known to peak in
early afternoon over land (Albright 1939) and to decline
in the late afternoon and into the early morning hours.
The evidence for sustained total lightning into the late
afternoon and evening (see Fig. 3) is likely due to the
nonlinear effects of cold outflow boundaries that increase the number of storms by destabilizing the atmosphere over a larger total area—a kind of domino
effect. The finding that the mean flash rate peaks in the
afternoon is also consistent with the diurnal variation
of severe thunderstorms that exhibit the largest flash
rates (Williams et al. 1999).
On the longer annual timescale, variations in the OTD
flash rate per storm are hardly detectable, and the dominant response to forcing is an increase in the number
of thunderstorms, a result supported by all selections of
OTD parameter to represent storms. This finding is consistent with analyses of daily frequency variations in the
earth’s Schumann resonances on the seasonal timescale,
which are sensitive to the number of thunderstorms and
insensitive to storm flash rates (Nickolaenko and Rabinowicz 1995; Nickolaenko et al. 1998). If the annual
timescale is representative of increasingly longer timescale behavior, this result also suggests that changes in
cloud buoyancy and local vertical air velocity will not
be a major contributor to changes in total lightning. In
this same context, it remains to be shown whether the
reported interannual variations in global lightning (Williams 1992; Reeve and Toumi 1999) are due to changes
in flash rate or to changes in the numbers of storms.
This question is difficult to answer with lightning observations from low Earth orbit because of the aliasing
effects of the pronounced diurnal cycle. An optical sensor in geostationary orbit is better suited for this task.
This study has focused on changes in flash rate and
number of storms for thermodynamic forcings on different timescales. A companion study by Boccippio et
al. (2000b) has focused on the same question but for
continental versus oceanic convective forcing. A similar
result has been found: the number of thunderstorms rather than the mean flash rate per storm dominates the large
land–ocean lightning contrast.
Acknowledgments. MIT thanks NASA Marshall
Space Flight Center for support on Grant NAG8-935 to
investigate observations from the OTD and for timely
provision of the data tapes. Discussions with R. Blakeslee, K. Driscoll, S. Goodman, S. Heckman, E. Huang,
D. Mach, V. Mushtak, and N. Renno are greatly appreciated.
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