Once the distance to the discharge
is determined, the B field ampltitude (assumed to be purely radiation
field) can be used, together with an assumed return stroke propagation
velocity, in the transmission line model to estimate the peak
current in the stroke. You could also use the E field
to estimate peak current. The magnetic direction finding
technique is the only one that can provide estimates of peak current
amplitudes.
The orthogonal loop antennas used in one of the prototype
lightning locating systems was a PVC pipe structure perhaps 8 feet
tall. A
picture of that antenna and the next generation antenna, maybe only 2
or 3 feet tall is
also shown in "Lightning
Direction-Finding
Systems
for
Forest
Fire
Detection,"
E.P.
Krider,
R.C.
Noggle,
A.E.
Pifer,
and
D.L.
Vance,
Bull.
Am.
Meteorol.
Soc.,
61,
980-986,
1980 (link to a PDF file). The current
sensor is considerably smaller.
Some typical large amplitude cloud discharge and return stroke
waveforms are shown below
|
|
In the original magnetic direction
finding systems the lightning waveform was subjected to a series
of waveshape tests. The main objective being to discriminate
between return stroke waveforms and waveforms from large amplitude
cloud discharges. We have implicity been assuming in our
discussion that the lightning channel is vertically oriented.
This is a pretty reasonable assumption for cloud-to-ground discharges,
especially at the time of peak field when the return stroke is close to
the ground. The unknown tilt of cloud discharge channels will add
signficant errors to the estimate of bearing angle.
The narrow positive bipolar pulse (NPBP) shown in the figure at
right (together with a 1st return stroke waveform for comparison) is an
as yet unidentified
cloud discharge of some kind and produces particularly strong VHF
radiation (the figure was adapted from
J.C. Willett, J.C. Bailey, and E.P. Krider, "A Class of Unusual
Lightning Electric Field Waveforms with Very Strong High-Frequency
Radiation," J. Geophys. Res., 94, 16255-16267, 1989).
If the waveform passes the waveshape tests, the peak ampltitudes
of the NS and the EW signals are measured. At the time of peak
signal, the return stroke is probably within about 100 m of the
ground. Estimating the bearing angle at this time is advantageous
because you eliminate the effects of channel branches, the channel is
usually fairly straight and vertical, and you're locating the point at
which the stroke actually struck the ground.
Once bearing angle estimates are made at multiple DF sensor
locations, you can then triangulate to locate the lightning strike
point. Errors in the bearing angle estimate of course
lead to uncertainty in the lightning strike location.
Here we see the location determined
using bearing angles from only 2 sensors (the minimum number
required). In the current NLDN network return strokes with a
current of 25 kA would be detected by 6-8 sensors. There are
sophisticated methods for determining the optimal location with
redundant data like that.
Large location errors can be present when a lightning strike is on
or near a baseline between two sensors.
In some of the original direction finder networks the signal amplitudes
were used to reduce the errors in locations on or near a baseline like
this. Now, of course, most strokes are detected at multiple
stations. Some of the other sensors
would be off the baseline and would provide more accurate location
information. As we shall see the newer sensors also determine the
time of arrival of the lightning signal at each sensor which provides
additional independent location data.
One of the first uses of DF systems to locate lightning that
might
cause forest fires in Alaska and the western US. For this
application, relatively larger location errors (4 to 8 km) were
acceptable. Later as lightning location data began to be used by
the power industry and insurance companies it became
evident that sufficient
location accuracy would not be possible using only magnetic direction
finding unless sensors were on the order of 100 km apart.
Operation of a network covering the continental US with that kind of
density would be too
expensive (in the current network sensors are roughly 300 to 350 km
apart
and
there are about 100 sensors covering the
continental US).
A need for greater location accuracy eventually led to development of
the so-called IMPACT sensor (improved accuracy from combined
technology) that utilized both MDF and TOA. The NLDN as
configured in the late 1990s is shown below (from K.L.
Cummins,
M.J.
Murphy,
E.A.
Bardo,
W.L.
Hiscox,
R.B.
Pyle
and
A.E.
Pifer,
"A
Combined
TOA/MDF
Technology Upgrade of the U.S. National
Lightning Detection Network," J. Geophys. Res., 103, 9035-9044, 1998).
IMPACT sensors are shown with triangles, LPATS sensors with
circles. The LPATS sensors were from a
lightning location
network using just the TOA technique manufactured by Atmospheric
Research
Systems (ARSI) that had been installed in the US in the late
1980s.
The IMPACT sensor was designed and manufactured by Lightning Location
& Protection, Inc. (LLP).
We will consider briefly the TOA technique below. We assume that
all three stations in the figure have either precisely synchronized
clocks or
accurate absolute timing (GPS timing).
There will be a constant difference in the time of arrival of a
signal at Stations A and C from lightning striking anywhere on the blue
curve (a hyperbola).
Similarly a hyperbola of constant TOA difference for Sensors B
& C can be drawn. The two curves intersect at two points.
You could resolve the location
ambiguityusing magnetic bearing angles from the 3 sensors as shown
above
Or you could draw another hyperbola
- the curve of constant TOA difference for sensors A & B.
Or you could use all of the available location data.
The figure below shows an actual example of a discharge located using
data from 5 stations in the NLDN (from the Cummins et al. article
mentioned above).
Three IMPACT sensors (highlighted in brown, purple, and yellow)
provide TOA information and bearing angle data. Two LPATS sensors
(at the centers of the blue and green circles) provided just TOA
data. Thus 8 independent pieces of information were used to
locate this discharge.
A more recent network upgrade (see Cummins
et
al. in the Second Conference on Meteorological Applications of
Lightning Data, Atlanta GA, 2006) was done in 2002 and all of the
IMPACT and LPATS sensors were replaced with IMPACT ESP sensors.
The ESP (enhanced sensitivity and performance) sensors provide both MDF
and TOA information. The
sensors are more sensitive and have faster processing times.
These improvements have increased the detection efficiency for low
amplitude return strokes. The new sensors also have the
capability of detecting and locating some intracloud discharges.
Lightning location data from the NLDN is now being used in
a wide
variety of applications and it
would seem appropriate to briefly discuss some recent attempts to
measure the network detection efficiency and location accuracy.
Video ground truth data is probably the most common method of checking
network performance. Images of lightning strikes captured by two
or more video cameras can be used to triangulate and
determine strike locations just as is done with data from the MDF
antennas. The table below summarizes results collected from a
small network of cameras operated in and around Albany, NY, in 1993,
1994, and 1995 (Idone et al. 1998a
& 1998b;
full
citations
are
given
at
the end of this section). Fast E
field data were also recorded. An upgrade of the NLDN, a switch
from using just MDF to a network combining MDF and TOA techniques, was
started and completed during the period of this experiment.
Albany, NY
Year
|
Flash DE
|
Stroke
DE
|
Location
Accuracy
|
Comments
|
1993
|
67%
(517 flashes)
|
---
|
|
NLDN data for
individual strokes
wasn't available at this time
|
1994
|
86%
(893 flashes)
|
67%
(2162 strokes)
|
2.61 km
(median NLDN-video location separation)
|
|
1995
|
72%
(433 flashes)
|
47%
(1242 strokes)
|
435 m
|
the number of NLDN
sensors in the Albany
area was decreased slightly in 1995 at the
conclusion of the network upgrade
|
Video data does have some limitations. First, the time resolution
is somewhat limited. A conventional video camera
acquires 30 frames per second. Each
frame consists of two interlaced fields which can be displayed
separately during playback. Video is not be able
to
resolve two strokes that occur within the same video field, i.e.
within a time of 16.7 ms. And, actually, two
strokes that occur on successive fields might be judged to be the
same stroke if there is a long and luminous continuing current
following the first stroke. On the other hand a
rebrightening of the lightning channel caused by an
M component might be counted as separate stroke. Some of
these uncertainties can be resolved
using a simultaneous record of fast E field changes. It is
practical to only cover a relatively small area with a video camera
network.
The study above shows a slight improvement in DE after the network wide
upgrade (72% vs 67%). There was a marked increase in LA (435 m vs
2.61 km). Locations and peak E field values were available for 92
strokes in the study. The DE was shown to be a function of peak
stroke current. 39 of 40 strokes with peak currents greater than
14 kA were detected by the NLDN. Only 18% of strokes with peak
currents between 6 and 10 kA were detected, and no strokes with peak
currents below 6 kA were detected.
During the Albany experiment lightning was observed to strike a couple
of tall buildings and a radio tower. 11 of these strokes were
detected and located by the NLDN. The mean difference between the
known strike location and the NLDN location was 518 m. 10 strokes
to a tall radio tower were also captured on video (1 of the strokes was
detected by the NLDN). The mean difference between the known
strike location and the video location was 38 m; this provided a good
check on the accuracy of the video locations.
In 2002-2003 the NLDN underwent another major upgrade wherein all of
the IMPACT and LPATS sensors were replaced with IMPACT ESP (enhanced
sensitivity and performance) sensors. This was done partly to
improved DE and LA near the boundaries of the network. The table
below summarizes measurements of DE made by Biagi
et
al.
2007 in southern Arizona, Texas, and Oklahoma.
Southern Arizona
Year
|
Flash DE
|
Stroke
DE
|
Corrected
stroke
DE
|
2003
|
95%
(671 flashes)
|
78%
(2290 strokes)
|
70%
|
2004
|
91%
(426 flashes)
|
73%
(1330 strokes)
|
66%
|
Overall
|
93%
(1097 flashes)
|
76%
(3620 strokes)
|
68%
|
Texas and Oklahoma
Year
|
Flash DE
|
Stroke
DE
|
Corrected
stroke
DE
|
2003
|
81%
(59 flashes)
|
75%
(126 strokes)
|
|
2004
|
94%
(308 flashes)
|
87%
(756 strokes)
|
|
Overall
|
92%
(367 flashes)
|
86%
(882 strokes)
|
77%
|
Data were collected with just a single video camera so the location
accuracy was not
measured.
Simultaneous fast time resolved measurements of fast E field and
optical signals were also made. These data were used to estimate
that about 13% of the strokes were not resolved on the video because of
the 16.7 ms video field integration time. This was used to
determine the corrected stroke DE values above.
Clearly the increased sensitivity of the IMPACT ESP sensors has
improved the DE. With this comes the possibility, however, that
more low amplitude cloud discharge signals will be detected by the NLDN
and mistakenly classified as cloud-to-ground (CG) discharges. The
data of Biagi
et
al. 2007 indicate this is a problem primarily for
positive polarity signals.
Positive Polarity (TX and OK only)
peak
current
|
confirmed
as
CG
discharges
|
Ipk ≤
10 kA
|
1.4 - 7%
|
10 kA
< Ipk ≤ 20 kA |
4.7 -
26%
|
20 kA
< Ipk
|
67 - 97%
|
Negative Polarity (S. AZ, TX, and
OK)
peak
current
|
confirmed
as
CG
discharges
|
Ipk ≤
10 kA
|
50 - 87%
|
As a final example we will give results from a study of NLDN
performance in Florida using rocket triggered lightning (see Jerauld
et
al., 2005).
Year
|
Flash DE
|
Corrected Flash DE
|
Stroke DE
|
Location Accuracy
|
2001
|
82%
(11 flashes)
|
91%
(11 flashes)
|
52%
(33 strokes)
|
0.27 km
(median NLDL - known location separation)
|
2002
|
86%
(14 flashes)
|
|
57%
(77 strokes)
|
0.83 km
|
2003
|
83%
(12 flashes)
|
95%
(12 flashes)
|
69%
(49 strokes)
|
0.45 km
|
Overall
|
84%
(37 flashes)
|
|
60%
(159 strokes)
|
0.60 km
|
Detection efficiency was again found to depend on return
stroke
peak current. Essentially 100% of strokes with a peak current
greater
than 30 kA were detected. 60% or 70% to about 90% of strokes with
currents between 10 and 30 kA were detected. Somewhat less than
30% of
strokes with currents less than 10 kA were detected and no strokes with
currents less than 5 kA were detected.
The corrected flash DE above attempts to account for the fact that
triggered lightning flashes do not contain a first return like found in
natural lightning. We would expect first strokes to be detected
more frequently than subsequent strokes because first strokes generally
have higher peak currents. This is discussed in somewhat more
detail in Cummins
et
al. 2006.
Large (greater than 2 km) location errors were found for about 21% of
the strokes in the study. The majority (54%) of these had peak
currents in the range of 5 to 10 kA. About 55% of the cases with
large location errors were located with only 2 sensors.
A study involving triggered light also allows a comparison between
estimates of peak stroke current derived from the NLDN data with direct
measurements of current. Mean peak current values are given in
the table below.
Year
|
Camp
Blanding
|
NLDN |
2001
|
25.1 kA
|
19.1 kA
|
2002
|
17.0 kA
|
15.7 kA
|
2003
|
14.8 kA
|
12.2 kA
|
Overall
|
17.6 kA
|
14.8 kA
|
Clearly the NLDN values understimate the true stroke current
ampltitude. This is also discussed in Cummins
et
al. 2006. The source of this error is probably the
attentuation correction that is made to the measured peak radiation
field signals measured at the NLDN sensors sites before they can be
used to estimate the peak current. The attentuation of the fields
due to propagation was probably being underestimated.
List of references cited in this
section
Biagi,
C.J.,
K.L.
Cummins,
K.E.
Kehoe,
and E.P. Krider, "National Lightning
Detection Network (NLDN) performance in southern Arizona, Texas, and
Oklahoma in 2003-2004," J. Geophys. Res., 112, D05208,
doi:10.1029/2006JD007341, 2007.
Cummins,
K.L.,
J.A. Cramer, C.J. Biagi, E.P. Krider, J. Jerauld, M.A. Uman, V.A.
Rakov, "The U.S. National Lightning Detection Network: Post-Upgrade
Status, in the 2nd Conference
on
Meteorological Applications of
Lightning Data, AMS Annual Meeting, Atlanta GA, 2006.
Idone,
V.P.,
D.A.
Davis,
P.K.
Moore,
Y. Wang, R.W. Henderson, M. Ries, and P.
Jamason, "Performance evaluation of the U.S. National Lightning
Detection Network in eastern New York 1. Detection efficiency" J.
Geophys. Res., 103, 9045-9055, 1998a.
Idone,
V.P.,
D.A.
Davis,
P.K.
Moore,
Y. Wang, R.W. Henderson, M.
Ries, and P. Jamason, "Performance evaluation of the U.S. National
Lightning Detection Network in eastern New York 2. Location accuracy,"
J. Geophys. Res.,
103, 9057-9069, 1998b.
Jerauld,
J.,
V.A. Rakov, M.A. Uman, K.J. Rambo, D.M. Jordan, K.L. Cummins and
J.A. Cramer, "An evaluation of the performance characteristics of the
U.S. National Lightning Detection Network in Florida using
rocket-triggered lightning," J. Geophys. Res., 110, D19106,
doe:10.1029/2005jD005924, 2005.