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Lightning-Warning Systems for Use by Airports (2008)

Chapter: Chapter 1 - Background

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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
×
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
×
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2008. Lightning-Warning Systems for Use by Airports. Washington, DC: The National Academies Press. doi: 10.17226/14192.
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7Lightning Properties, Behavior, and Terminology A nearby lightning strike is a dramatic event that immedi- ately invokes fear and awe. As an obvious hazard for airport operations, it demands respect. Properly grounded buildings and well-designed electronics with surge protectors usually provide adequate protection to structures and electronic sys- tems. Fueling operations, which are at risk from sparks or other electrical discharges, are normally suspended during lightning activity. The greatest lightning danger is to airport ramp workers, who need to be moved indoors until the light- ning ends, which essentially shuts down ramp operations. Lightning is a complex process that, even after decades of intense investigation, is still quite mysterious. The electric fields and currents that help drive lightning are global in scale, while many of the charge separation processes that lead to a lightning strike involve microscopic interactions between small particles of ice and water in the core of intense thunder- storms. For every generality about lightning behavior, there seem to be exceptions. In this review of lightning properties and behavior we will start with a discussion of the earth’s electric field and then move on to the clouds and thunderstorms that create light- ning. This discussion involves a wide range of often unfa- miliar words and specialized terminology. For reference, a glossary of lightning terms, extracted from the American Meteorological Society’s Glossary of Meteorology, is pro- vided in Appendix B (1). This discussion also makes extensive use of a number of standard reference books and Internet references (2–11). The Earth’s Electric Field and Cloud Electrification The earth’s atmosphere is an integral part of a natural elec- trical system in which the earth and its atmosphere can be thought of as a spherical capacitor, with the earth as the lower conducting surface and the atmosphere as a slightly conduc- tive medium topped by a highly electrical region in the upper atmosphere, where unfiltered solar radiation effectively ion- izes atmospheric molecules and atoms into a highly conductive region called the ionosphere. The ionosphere (sometimes also termed the electrosphere) is positively charged, while the earth’s surface has a net negative charge. This charge imbal- ance creates an atmospheric electric field (roughly 100 V/m near the earth’s surface) and a corresponding air-earth elec- trical current directed downward from the ionosphere to the ground, where the direction of the current is defined as the direction that a hypothetical positive charge would flow. Without a mechanism to recharge the ionosphere, the air- earth current would quickly discharge this global capacitor. While historically there have been suggestions that charged particles from the solar wind might help maintain the positive charge in the ionosphere, most atmospheric scientists now accept that the global population of thunderstorms transfer electrical charges back to the ionosphere in a thunderstorm driven global circuit (see Figure 1). At any one time there may be as many as 2,000 thunderstorms occurring around the globe, generating a total of perhaps 40 lightning flashes every second. Our knowledge of atmospheric electricity is still ex- panding. Recent discoveries of a variety of electrical discharges extending upward from the tops of active thunderstorms have been termed jets, sprites, and elves. The presence of the atmospheric electric field may con- tribute to the earliest phases of cloud electrification. Even though relatively weak, the field can induce a degree of charge separation in water drops and ice particles, helping them cap- ture ions and other charged particles that are components of the fair weather current and giving them a net charge. The relatively low level electrification of small, shallow clouds is not, in itself, a hazard. The development of lightning requires additional charge separation in strong convective clouds. Airplanes flying through seemingly benign stratiform C H A P T E R 1 Background

clouds may, however, trigger an electrical discharge. Depend- ing on their history, these clouds may have moderate electrical fields as a result of earlier convective activity or from electri- fication associated with the melting of precipitation. In-flight lightning strikes are relatively frequent (averaging about one strike for every 3000 hr of flight), but they seldom do much damage since aircraft are generally well shielded against light- ning by their metal airframes (12). Thunderstorm Electrification and Lightning While small and mid-sized convective clouds may become electrified, they seldom produce natural lightning. Lightning requires a tremendous amount of charge separation before a discharge, and this generally happens only in the large con- vective storms we call thunderstorms. While there are still many unknown factors in the initiation of a lightning strike, years of studies have made it clear that the process involves collisions between super-cooled water and ice (including graupel and small hail) in the presence of strong updrafts and downdrafts. Most often, cloud tops have to cool to at least −20 °C before lightning begins, with the critical charge separation processes occurring in the portion of the clouds with temperatures between −5 °C and −20 °C (24 °F to −5 °F). Particle collisions, combined with size sorting and strong updrafts and downdrafts, separate the positive and negative charges. The descending particles tend to collect negative charges, and the ascending particles are predominately posi- tively charged. The idealized result of these interactions is a simple cloud dipole, with positive charges grouped at the top and negative charges grouped in the middle and lower areas of the cloud, in the −5 °C to −20 °C zone (see Figure 2). In addition to the charge separation within the cloud, the lower area of strong negative charges induces a compensating area of positive charge to form immediately below the cloud on the earth’s surface. Eventually, when the charges build up to a high enough level to cause an electrical breakdown in the air separating the charge centers, the built-up charges can dis- charge in a lightning stroke. This can either happen between the cloud and the ground, or between the positive and nega- tive charge centers within the cloud. The majority of natural 8 Earth Storm Curre nt Electrosphere Fair WeatherCurrent Rc A LT IT UD E (km ) 65 15 Figure 1. A simple conceptual model of the main global circuit. Thunderstorm “generators” drive current to the highly conductive electrosphere and back to the ground through the fair weather current (2). Figure 2. An idealized small thunderstorm with charges separated into a simple electrical dipole (5).

lightning strikes (about 75% to 80%) occur within the storm cloud itself. Anatomy of a Lightning Strike, Part I Even in this simple model of a thunderstorm, lightning strikes are quite complex. Figure 3 shows the development of a typical negative cloud-to-ground lightning strike. Both neg- ative and positive flashes can occur, but negative flashes are more common. Negative flashes bring negative charge to the ground, while positive flashes bring positive charge to the ground. In negative flashes, the descending current from the cloud moves downward in a series of short jumps, called a “stepped leader.” The individual steps in this process branch out in different directions, looking for the path of least resist- ance toward the ground. As a leader gets close to the ground, a corresponding streamer of positive charge moves up from the surface to meet the descending negative current. When these two currents connect they provide a highly conductive channel for charge transfer between the cloud and the ground. The initial descending negative charge is followed by an even stronger “return stroke” of positive charge from the ground, which seems to move up the channel and into the cloud. The actual charge transfer is, however, done by free electrons so the return stroke is really just a progressive draining of negative charge downward, with the upper limit of the drained path moving upward as electrons flow to the ground. Multiple strokes of dart leaders and return strokes can follow, produc- ing flickering strobe-like flashes of light (see Figure 4). The entire multiple discharge sequence of a lightning strike is normally called a flash and is typically made up of two to four separate strokes. In some cases, as many as 15 or more strokes have been observed. The subsequent strokes generally follow the established conducting channel, but the final strike point on the earth’s surface can jump around from strike to strike, with separations of up to several hundred meters or more. These cloud-to-ground flashes are normally called CG lightning, or simply ground lightning. Anatomy of a Lightning Strike, Part II Electrified thunderstorms are seldom as simple as the ide- alized dipole shown in Figure 2. There are complex areas of charge throughout the cloud, resulting in complex electrical fields. Figure 5 illustrates a more normal situation and gives examples of a number of different types of lightning flashes, including discharges between clouds (intercloud) and within a single cloud (intracloud). Both of these classes of lightning can be grouped together under the single term IC lightning, or cloud lightning. Unlike CG lightning flashes, IC strokes are not followed by return strokes, and they do not carry as much current as is typical for a CG flash. Cloud discharges and CG flashes both radiate energy over a wide spectrum of frequencies, predominately the radio fre- quency (RF) bands. During the “stepped” process that creates new channels, there are strong emissions in the very high fre- quency (VHF) range. High current discharges along previously established channels (“return strokes”) generate powerful emissions in the low frequency (LF) and very low frequency (VLF) ranges. Medium frequency (MF) emissions are centered in the AM radio band and are responsible for the static we hear on AM radio during lightning storms. Figure 6 illustrates the relative energy spectrum of CG and IC flashes in the VLF, LF, MF, and VHF frequency bands. Cloud and ground flashes produce significantly different RF emissions over different time scales, which can be used to distinguish between these two classes of lightning. With their high current and predominately vertically oriented return strokes that generate magnetic fields, CG flashes produce strong signals that can easily be associated with a single posi- tion near the point they strike the earth’s surface. The strong LF and VLF pulses generally follow the curvature of the earth and can be detected for ranges of 300–600 km (185–375 mi). IC strokes, on the other hand, are identified by their VHF emissions, which are a line of sight transmission that can normally only be detected out to ranges of 200 to 300 km (125 to 185 mi). In summarizing years of lightning research, the National Severe Storm Laboratory has concluded that taller, more com- plex storms produce more lightning and more CG flashes than do smaller, isolated storms. The first flashes produced by a storm are usually IC flashes, and if detected, they can signal the initiation of a thunderstorm. The ratio of IC flashes to CG flashes is quite variable, but cloud flashes predominate, often by a factor of five or more. Lightning Climatology Figure 7 shows two views of a lightning climatology for the continental United States (CONUS), Mexico, and southern Canada. The lightning data were extracted from a global database based on observations from two National Aeronautics and Space Administration (NASA) instru- ments in low-earth-orbit, the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS). The OTD data set was collected between May 1995 and April 2000, while the LIS data set was collected between January 1998 and December 2005—essentially a 10-year data archive. The satellite data are based on optical detection of lightning flashes, both during the day and at night, and represent the “total” lightning distribution, including both IC flashes and CG flashes as seen from space. The summaries have been processed to display the number of flashes per square kilometer per year. The upper panel 9

10 Figure 3. Anatomy of a lightning strike (5).

shows the overall annual average flash density distributions. The main features are the concentration of the lightning flashes over land and a general gradient from low flash densities in the Pacific Northwest to very high flash densities over Florida. The annual pattern, however, reflects both the geographical and seasonal frequencies of thunderstorms, with the south- ern states having a much longer annual lightning season. The lower panel shows the monthly average flash density for the month of August, displayed in terms of the expected annual lightning flash densities that would result if the August flash rates were continued for a full year. The August plot shows that during the late summer, thunderstorms are wide- spread throughout all areas of CONUS, with the exception of the extreme northwestern and northeastern states. Lightning can be a hazard every place in the lower 48 states; although not well represented in the satellite climatology, lightning storms are also a major hazard in Alaska during the long hours of summer sun, and they trigger a great number of forest fires every year. In addition to the geographic and seasonal variations in the frequency of lightning hazards, there is also an important daily diurnal variation. Over continental areas, convective activity—including thunderstorms and lightning—peaks in the mid to late afternoon, with a secondary nighttime maxi- mum across the Midwest. Lightning Detection Technologies Lightning flashes and strokes can be detected in many dif- ferent ways. Most notably the discharge of thousands of amperes of current in a fraction of a second generates temperatures estimated to be as hot as 30,000 °C, hotter than the surface of the sun, with a brilliant flash of light and an acoustic shock wave we call thunder. At the same time, the surging electrical currents release a wide spectrum of electro- magnetic radiation and modify the strength of the local atmospheric electrical field. Flash and Bang The flash and bang of nearby lightning strikes are hard to ignore, even without special instrumentation. Distant light- ning flashes can often be seen by an alert observer, particu- larly at night. For applications involving safety, however, these techniques are not reliable and are only appropriate in the absence of more quantitative technologies. While these “technology free” approaches can only esti- mate the position of a lightning flash in a general way, the difference in time between the observation of a flash and the arrival of the sound of thunder is a useful and practical way to estimate the distance (but not necessarily the direction) of the lightning. The lightning flash is seen virtually instanta- neously, while sound travels at about 750 mph, or approxi- mately 1 mi every 5 sec. The interval, in seconds, between the flash and the bang multiplied by 5 thus gives a useful estimate of the distance of the strike, in miles. Unfortunately, many small airports do not have any light- ning detection capabilities, and rules-of-thumb, such as the “flash-bang-multiply-by-5” estimate of the proximity of the lightning, provide the only information. Acoustic detectors. While the sound of thunder is usu- ally easy to recognize, it is difficult to use in any quantitative sense. Networks of acoustic detectors have been tested to try to locate lightning strikes, but with limited success, and acoustic detection systems have never been used operationally. Optical detectors. The instantaneous flash of light asso- ciated with lightning can be difficult to see in the daytime and, until lately, has not often been used for quantitative applica- tions. By using sensitive detectors and narrow bandwidth fil- ters, however, optical lightning detection systems have been developed that can be used in the daytime and which have been incorporated into ground-based sensors in conjunction 11 Figure 4. A well-known picture of a lightning flash made with a special lightning camera with film that moves rapidly during the exposure. Stepped leaders are frozen, while the multiple return strokes show up as separate strokes that follow exactly the same path (4).

12 INTER-CLOUD STRIKE (CLOUD-TO-CLOUD) TYPICAL CLOUD-TO-GROUND LIGHTNING BETWEEN GROUND AND NEGATIVE CHARGE CENTERS DISCHARGE WITHIN CLOUD BETWEEN NEGATIVE BASE AND POSITIVE TOP (INTRA-CLOUD) DISCHARGE BETWEEN NEGATIVE AND POSITIVE CHARGE CENTERS Figure 5. Multiple clouds with complex charge distributions. This figure illustrates the typical cloud-to-ground lightning flashes, as well as discharges between different portions of a single cloud and discharges between adjacent clouds (8). CG Flash VLF 1 to 10 kHZ LF 100 kHz MF 1 Mhz VHF 10 Mhz Scale 0.5 second Cloud Flash Figure 6. CG and IC flash emissions in various frequency ranges. VHF emissions are generally limited to line of sight propagation (200–300 km, or 125–185 mi.), while LF emissions propagate by ground waves that can follow the curvature of the earth and can be detected to ranges of 300–600 km, or 185–375 miles. VLF emissions can be reflected off the ionosphere and can be detected for thousands of kilometers, but in variably decreasing efficiencies (4).

with magnetic and electrostatic pulse analysis to reduce false alarms (for example, the Vaisala TSS-928 local-area lightning detection sensor). More important, optical detection systems have also been adapted for satellite-based lightning detection systems (satellite-based systems will be discussed in a separate section). Atmospheric Electric Field Measurements Electric field measurements have a long and important his- tory of use by scientists interested in atmospheric electricity and lightning. The most common instrument to measure the atmospheric electric field is the field mill (see Figure 8), although there are other instruments, including some that are proprietary, that can also be used to monitor the electric field. Nearby lightning discharges will produce sudden changes in the strength of the local electrical field, and these distinctive changes can be used to detect lightning—although without any direct way of measuring the distance or range to the light- ning flash. Nearby charge centers, such as a cloud developing directly overhead, can dominate the local electric field and may limit the detection of distant lightning strikes. Perhaps more important than detecting lightning, electric field mills can also monitor the buildup in the local electrostatic field, which normally precedes a lightning strike. Most currently available lightning detection systems that employ field mills use them to alert users to the electric field buildup and to warn them of a potential lightning event. This application is unique in focusing on anticipating the lightning “threat” rather than on detecting lightning strikes after they occur. The technology, however, has a somewhat uncertain range and de- tection efficiency, along with a potential for false alarms. Field mills are sensitive instruments that require periodic monitoring and cleaning; their readings can be influenced by blowing dust and by local air pollution. The strong electric fields that signal a potential lightning event, however, are normally easy to detect with fields mills that are properly maintained. Lightning alert and lightning prediction systems making use of electric field mills are available commercially and are a key component of the lightning hazard and launch evaluation systems employed at NASA’s Kennedy Space Flight Center. Electromagnetic Emissions from Lightning Strokes Most lightning detection systems currently available make use of the electromagnetic emissions, predominately RF, 13 70 50 40 30 20 15 10 8 6 4 2 1 .8 .6 .4 .2 .1 Annual NASA Satellite Climatology, Flashes per km2 per year Monthly NASA Satellite Climatology, Flashes per km2 per year 70 50 40 30 20 15 10 8 6 4 2 1 .8 .6 .4 .2 .1 August Figure 7. NASA satellite climatologies of “total” lightning (CG plus IC) flashes in terms of the average number of flashes per square kilometer per year, compiled over a 10-yr period. The upper panel shows the annual averages, while the bottom panel shows the monthly average flash density for the month of August (data provided by the Global Hydrology and Climate Center, NASA Marshall Space Flight Center). Figure 8. Electric field mill (from Boltek).

associated with the electrical discharge (see Figure 6). Light- ning strokes produce RF static (mostly in the MF band) and are familiar to listeners of AM radios. CG strokes generate strong signals in the LF band, which can be detected at ranges of many hundreds of kilometers. IC strokes, on the other hand, predominately generate VHF, line-of-sight emissions. Lightning detectors based on RF electromagnetic emissions range from relatively simple, low-cost, handheld devices to sophisticated sensors and groups of sensors organized into detection networks. Low-end systems, however, are of uncer- tain sensitivity and are subject to false detections. They are most commonly marketed for hikers, sports activities, and outdoor gatherings. The most basic systems do not try to identify the direction of the lightning, but may try to produce a rough estimate of the lightning distance by measuring the amplitude of the signal. This technology can be enhanced by using more sophisti- cated receivers that can monitor the signal at multiple fre- quencies and analyze the time evolution and properties of the signal to minimize false alarms. Analysis of the incoming signal can also be used to distinguish between CG flashes and discharges from an IC stroke. With the addition of orthogonally crossed loop antennas or other radio direction finding technologies (the SAFIR lightning detection systems developed in France, for example, use VHF interferometric dipole antennas for direction find- ing), it is also possible to determine the direction from the detector to the source of the lightning signal. Used individu- ally, high-end receivers of this sort are employed to identify the direction of nearby lightning strikes and, with a simple signal amplitude algorithm, to also estimate the range. Such sensors are often included in automatic weather stations de- signed to produce fully automatic METAR reports (aviation routine weather reports) summarizing the current weather at an airport. For this application, the lightning detection sys- tem is used as an indicator of the nearby presence of a thun- derstorm and gives an approximate indication of the storm’s position and distance relative to the airport. Lightning Detection by Networks of Electromagnetic Sensors Networks of sophisticated electromagnetic sensors can provide very accurate position information for CG lightning strokes. The most immediately obvious approach is through triangulation of the direction information obtained by two or more sensors. Since the strong LF and VLF signals from ground lightning tend to follow the surface of the earth and are detectable at ranges of many hundreds of kilometers, it is possible to construct a network to cover a very large area with a reasonable number of detectors—something on the order of slightly over 100 sensors for CONUS. With this density of receivers, most lightning strokes can be detected by three to four different sensors. Sensor networks can also locate the position of a lightning strike by making use of the high-accuracy time references provided by global positioning system (GPS) satellites to determine the difference in time between two or more de- tectors’ observations of the same lightning stoke. Using sophisticated algorithms, the differences in the “time of ar- rival” of the signal can be used to identify the location and time of the lightning strike. Depending on the position of the lightning strike and the position and spacing of the detectors, time of arrival solutions can require as many as three or more detectors to record the signal from the same lightning stroke. Using sensitive receivers designed to minimize false detec- tions, lightning detection networks have been shown to be capable of detecting cloud-to-ground lightning strokes with a detection efficiency of over 90% and position accuracy of significantly better than 1 km (0.625 mi). Two such networks, run by commercial companies, currently provide lightning information for CONUS. Ground-based lightning detection networks are primarily designed to detect CG lightning and can provide information about each individual stroke within a lightning flash. With recent improvements to these same detectors they can now de- tect a significant percentage of the nearby IC lightning strokes, but at a variable and as yet not well characterized detection efficiency that depends on the properties of the stroke and the distance from the network sensors. Since the IC lightning strokes are frequently horizontal and extend for great dis- tances, it is harder to assign a single position to each stroke. CG flashes also extend over long distances inside the cloud, while the ground strike positions are normally well defined. Since there are significantly more cloud lightning strikes than ground strikes, and since within-cloud lightning is normally observed preceding the first ground strokes, cloud lightning detection systems that are optimized for VHF emissions have a great po- tential for enhancing our current detection capabilities. These systems will, however, require a significantly higher density of stations to provide uniform, high-detection-efficiency cover- age for future applications. At present, there are a number of regional “total lightning” detection systems that are being used for research and for the testing of future application products. Lightning Detection from Space Space-borne sensors can also be used to detect lighting. While some satellite-based sensors can detect the electrical emissions from the lightning flash, the most promising space- borne approach is based on optical detection of the lightning strikes. Optical detectors, normally filtered to look at a strong oxygen emission band in the near infrared (IR) and analyzed 14

to detect short bursts of radiation such as expected from a lightning strike, can be used both day and night. In the 1970s and 1980s, Bernard Vonnegut designed an early handheld detector of this sort for use by U-2 research aircraft and Space Shuttle astronauts (13, 14). This approach was subsequently refined and employed in NASA’s LIS on the TRMM satellite and in the OTD flown on the Microlab-1 satellite. Similar optical detection systems are currently being developed for use on the GOES-R series of U.S. operational geostationary weather satellites. The Geostationary Lightning Mapper (GLM) being devel- oped for GOES-R is expected to provide full coverage over the United States, South America, and adjacent oceanic areas. From geostationary orbit, the GLM lightning sensor will not be able to match the accurate positioning of the current ground-based networks, but will provide uniform, high- efficiency detection of total lightning, including both cloud and ground flashes over virtually all of the visible earth disk as seen from space. This new data set will not replace the current ground-based lightning networks, but will provide extremely valuable “total lighting” information to augment the high-resolution CG flash information currently available. Warning Criteria Detecting lightning strokes is a critical initial step in any lightning safety system, but needs to be combined with a set of warning criteria. In general, most dedicated lightning systems provide two levels of warning: an alert, saying that lightning may develop or move into the area in the near future, and an alarm, saying that lightning has been detected in the imme- diate vicinity or is expected to develop at any moment. In systems based exclusively on measurements of the atmospheric electric field, unusually high fields will trigger an alert, with alarms being triggered by electric fields reaching a level where imminent discharges could be expected (typically 2000 V/m). In systems based on detections of CG flashes, the warning criteria are based on the distance to the lightning strokes being detected and the time since the last stroke was detected within a specified distance from the area of interest. While there are no universally recognized standards for issuing alerts or alarms for airport ramp operations, the American Meteo- rological Society and the National Oceanic and Atmospheric Administration (NOAA) have endorsed the “30-30 rule.” This rule states that outdoor activities should be limited or curtailed whenever there has been a lightning strike detected within 6 mi (based on 30 sec between an observed flash and the sound of the thunder) within the past 30 min. Lightning warning system vendors often recommend this standard, but allow users to set their own criteria for alerts and warnings. In some cases, airport operators report using a standard as short as 10 min since the last lightning strike before going back to work (see Chapter 2). In any situation of this sort, there is a continual tension between providing an adequate warning to prevent injuries and not stopping work unnecessarily. Advocates of conservative (safety first) warning criteria emphasize that lightning injury statistics show that injuries are most likely at either the very beginning of the lightning event or near its end (15, 16). Their goal is to be able to issue a lightning warning before the first strike reaches the ground and then to allow enough time before work is resumed to ensure that the hazard has passed. This is a serious problem, since individual lightning strikes are essentially impossible to predict, either as to time or loca- tion. There are well-documented examples of “bolts from the blue”—lightning strikes that occur when an observer can see blue sky above (see Figure 9). On the other hand, current pro- cedures are generally believed to provide a safe environment for ramp workers, as evidenced by the very low numbers of reported lighting deaths or injuries. Review of Current Airport Lightning Detection Technologies This section reviews and evaluates most of the lightning detection systems and technologies currently in use at airports or marketed for use by airports, airlines, and ramp workers. As a rather specialized market, it is surprising how many dif- ferent commercial systems are available. All the systems included in this discussion seem to be rep- utable and should be able to detect lightning strikes within ranges of concern to airport workers. There are, however, no formal standards for lightning detectors, and no agency or organization is responsible for routinely testing these instru- ments for accuracy, reliability, or durability. While it would be relatively easy to perform comparisons between instruments, this would require cooperation from the various system ven- dors. Lacking a requirement for a license or a certification process, this is not likely to happen. More important, verifi- cation and validation of lightning detection system perfor- mance requires an independent system for detecting ground truth. Some limited testing of this sort has been done, mostly to document the performance of the National Lightning De- tection Network (NLDN) using triggered lightning strikes or triangulation of strike impact positions from simultaneous photographs taken by multiple cameras. Handheld or Portable Systems Based on RF Emissions Handheld systems are the entry-level product for lightning detection. These systems are relatively low cost (some priced 15

under $100) and only detect the RF static discharges of a nearby lightning strike. While the systems may not be uni- formly sensitive in all directions, they have no way to detect or indicate the direction of the lightning strike. They do, how- ever, generally try to give some indication of the relative range of the strike, based on the amplitude of the RF signal. These systems often monitor the amplitude of the lightning signals over time and indicate whether the lightning is getting closer or further away, based on the trend in the signal amplitude. This is not a particularly accurate way to estimate range, making the devices mostly useful as an “objective” detection system that might be carried by individual workers or used at a small airport to help them notice or evaluate a potential lightning hazard. In general, these systems are not appropriate for workers at large airports or for airport operations managers. Specific products in this category include • StrikeAlert (www.strikealert.com), • SkyScan (www.skyscanusa.com/main.html), and • ThunderBolt (www.spectrumthunderbolt.com). Directional Detectors Based on RF Emissions These systems are a step up from the handheld or portable systems discussed earlier. The systems add a fixed antenna to identify the direction to the detected lightning strike. The distance to the lightning strike, however, is still estimated from the amplitude of the lightning signal. Prod- ucts in this category can range from fairly basic systems using personal computers, which are primarily targeted at meteorological hobbyists or commercial users seeking a general awareness of nearby lightning activity, to sophisticated systems engineered for specific airport applications (for example, automatic thunderstorm detection for METAR reports). As single sensor detection systems, these systems are some- what limited for applications that require high-accuracy de- tection and tracking of lightning strikes in the vicinity of an operational facility, such as airport ramp operations. These systems can be quite useful, but they should not be used for applications for which they were not intended. 16 A Bolt from the Blue! Figure 9. Two illustrations of lightning strikes that develop within a convective storm, but exit the side of the storm and strike the ground relatively far from the visible edge of the storm. These two illustrations are from different storms, but show a strikingly similar pattern. The picture on the left was taken by Al Moller. The illustration on the right, provided by Bill Rison from the New Mexico Institute for Mining and Technology, is a vertical cross-section of a storm, as seen by a research radar, overlaid with a full depiction of a lightning stroke based on a specialized lightning mapping system capable of detecting each step in the lightning stroke. In this case, the lightning strikes the ground about 5 km (3 mi) from the edge of the radar echo.

This category includes Boltek (www.boltek.com). Note, however, that there is a cooperative lightning detection network based on shared observations by Boltek system users—the StrikeStar Lightning Detection Network—but as a coopera- tive effort it is clearly and properly labeled as “Not for use for protection of life or property.” The following two thunder- storm sensors designed for automatic weather stations are also in this category: • All Weather Inc. Thunderstorm Detector, Model 6500 (www. allweatherinc.com/meteorological/lightning_detection_ 6500.html), and • Vaisala Local Lightning Sensor TSS928 (www.vaisala. com/businessareas/measurementsystems/thunderstorm/ producingsystems/tss9281). The single-sensor thunderstorm detection systems in- tended for use with an automatic weather station may not be appropriate for high-resolution detection and tracking of nearby lightning activity. Two or more of these units could, however, be combined into a local lightning detection network that could provide a local-area, high-accuracy, real-time lightning detection capability. At present, no commercial vendors offer this type of system. Electric Field Mills (or Other Electric Field Monitoring Systems) By monitoring the buildup of the local electric field strength, electric field mills (or other electric field monitoring systems) can sense the increasing potential for a nearby lightning strike. In this sense, field mills are a rather unique product in that they offer the promise of being able to “predict” the first lightning strike and offer protection for airport personnel in the case of a storm that develops lightning directly overhead and does not move into range as a fully developed, active thunderstorm. There are a number of manufacturers of field mills, mostly sold as individual units and not as an integrated lightning de- tection and warning product suitable for airport applications. Several commercial lightning detection systems employ, or have the option to employ, field mills as a component of their systems. Only two vendors offer full commercial systems based exclusively on the monitoring of the atmospheric electric field: Thor Guard (thorguard.com) and TOA Systems (www. toasystems.com/TOASystems/ALWS.htm). Thor Guard provides complete lightning warning systems, complete with horns and lights. Their standard installation is based on a single sensor, but for larger areas they provide systems with several sensors. They have an extensive customer list, including some small airports. TOA Systems offers an Advanced Lightning Warning Sys- tem (ALWS), based on three or more electrical field mills and designed to monitor an area 6 mi or more in range. Their field mill systems can also be integrated with lightning reports from a separate network (such as their own U.S. Precision Lightning Network, USPLN). Field mills can offer important information on the initial development of electrical activity in the vicinity of an airport, but are probably best used as a component of a detection and warning system that also uses RF lightning detection technologies. Commercial Lightning Detection Networks At present, the United States is covered by two separate, in- dependent lightning detection networks. These networks are intended to provide real-time lightning data for a wide vari- ety of commercial and government applications. The older of the two networks, NLDN, is now operated and maintained by Vaisala. NLDN (www.vaisala.com/weather/ products/lightning/knowledgecenter/aboutnldn) was recently upgraded with new sensors that combine both magnetic direc- tion finding (MDF) and time of arrival (TOA) technologies to increase system reliability, detection efficiency, and location accuracy. The current system is estimated to have a 90%–95% detection efficiency for CG flashes, with a median location accuracy of better than 500 m (17, 18). In 2005, Vaisala’s NLDN received a 5-yr contract to provide lightning detection data to the National Weather Service and other U.S. govern- ment agencies. USPLN (www.uspln.com/index2.html) is owned and main- tained by TOA Systems, Inc., in collaboration with its partner, WSI Corporation. WSI is responsible for sales and marketing of the data, including sales to value-added retailers. This re- cently completed network is based on a new generation of sensors, exclusively using time-of-arrival technologies. TOA Systems estimates that their national network provides greater than 90% detection efficiency and an accuracy equal to, or better than, 250 m. Airport Lightning Detection Systems Based on National Lightning Networks Given the availability, accuracy, and impressive effi- ciency of the national lightning detection networks, it is natural that most of the commercially available airport lightning detection systems are based on the network light- ning data sets. While some systems make use of the lightning data by itself, other vendors integrate the lightning data with other, more general-purpose weather information, including radar products. The lightning-specific products are clearly directed 17

18 toward applications such as ramp operations, with the intent of providing a focused product that meets the specific user’s needs. The more general integrated displays, on the other hand, are normally directed toward a broader audience, including users such as airline managers and dispatchers that need to monitor both flight and ramp operations. Ideally, an inte- grated product should provide separate displays or tools to switch focus between different, independently optimized views of the available data. Versatile systems, optimized for meteo- rologists, are often too complicated for focused applications such as ramp operations. The Vaisala thunderstorm warning system is based on real- time lightning observations provided by Vaisala’s NLDN. The system can optionally be augmented by the addition of up to seven electric field mills. The warning system provides an extensive set of custom displays showing the location of light- ning strikes and generating specific alert and alarm messages. The warning system can be customized by visual and audible alarms and electronic notification. The most recent software upgrade supports an unlimited number of circular or polygon warning areas, with the alert and alarm criteria customized by the user (see Figure 10). The current version of the Vaisala lightning warning system is the TWX300, which was released in 2007 (www.vaisala.com/ weather/products/lightning/). Earlier versions of the Vaisala system were distributed as the Precision Lightning Warning System (PLWS), which was released in 1995, and the TWX1200, which was made available in 2004. All of these versions of the Vaisala system are currently in use at a variety of airports. ARINC is a licensed installer and value-added reseller of Vaisala lightning equipment and can provide customized in- stallations with external alarms (horns and beacons) and a variety of different options for communication links (www. arinc.com/products/weather/forewarn/index.html). ARINC’s ForeWarn precision lightning system is based on Vaisala’s Thunderstorm Warning System software, with user options. Figure 10. A captured image of the main display screen of the Vaisala TWX300 lightning warning system (with annotations added). The age of the displayed lightning strokes is indicated by their color, while the bottom panel summarizes the current alarm and alert status. As the storm approaches the airport, the display can be zoomed in for a closer, higher resolution view (figure courtesy of Vaisala).

The Weather Decisions Technologies (WDT) real-time lightning display (www.wdtinc.com/pages/home_page/ lightningDSS/realtimeLD/web_page.xml) provides a simple, direct view of nearby lightning strikes (see Figure 11). WDT’s main focus, however, is on a more comprehensive Lightning Decision Support System (LDSS) that can be augmented to include lightning range alerting and a lightning prediction algorithm. Weather Services International (WSI) has a number of systems designed to provide general-purpose weather information for airports and weather-sensitive applica- tions (www.wsi.com/aviation/solutions). Their systems are based on a dedicated workstation at the airport with a satel- lite data feed that provides general weather information, including radar and satellite imagery, augmented by real- time NLDN or USPLN lightning observations. Their Weather Workstation product is used by Delta, UPS, and FedEx. Figure 12 shows a detail from the WSI Fusion Display, combining radar imagery, flight tracks, and real-time light- ning observations. DTN/Meteorlogix offers a general airport weather infor- mation system, featuring real-time NEXRAD radar data from NOAA. As one component of this system, NLDN lightning data are overlaid on top of the radar display, with an on-screen panel indicating the current alert or alarm status (defined in terms of lightning strikes within a user-specified warning and advisory area, indicated by a circle centered on the airport). The WeatherSentry system (www.meteorlogix.com/industry/ aviation.cfm) is provided as an online web application (see Figure 13). The Integrated Terminal Weather System (ITWS) is a U.S. government–sponsored development of a comprehensive terminal area weather system (www.ll.mit.edu/Aviation Weather/sitdisplay.html). It is intended for installation at large airports that have been provided with Terminal Doppler Weather Radar (TDWR). The basic ITWS display is relatively complex, but includes a simple “lightning within 20 nautical miles” display light based on real-time access to NLDN data (see Figure 14). It would be relatively easy to enhance the lightning warning features of this system in an environment that has the capacity to integrate lighting observations with other meteorological data sets. Lightning Prediction Technologies Lightning warning systems often make a distinction be- tween lightning detection and prediction. Detection systems, as the name implies, simply detect and report lightning Figure 11. An example of the WDT real-time lightning display. The age of the displayed lightning strokes is indicated by their color on a zoomable map display (figure courtesy of WDT). 19

20 strikes after they occur. Prediction systems, on the other hand, provide warnings that a lightning strike is likely to occur. Most of the time there is not much of a difference be- tween the two approaches. If an active thunderstorm moves towards an airport, lightning detection technology will con- tinually monitor the locations of the CG lighting strikes. When the activity reaches a specified distance from the air- port, the system will generate an alert or warning—essentially a prediction, based on the proximity of the lightning, that the storm presents an imminent threat and hazard. In some cases, however, a lightning storm may develop directly over an airport, and the very first strikes can put airport workers at risk. In this case, a prediction system may be able to pro- vide a uniquely valuable warning. Even the best predictions only give a general indication that a lightning strike is likely to occur in the immediate vicinity. The timing and path of an individual lightning stroke are, for all practical purposes, unpredictable. There are two distinctly different approaches to predicting lightning hazards. The first, based on monitoring the buildup of the atmospheric electric field in response to nearby charged clouds, represents a true prediction. Electric field measure- ments will not, however, necessarily predict all nearby light- ning strikes, and they can be expected to produce occasional false alarms (19, 20). The other approach to lightning prediction is to monitor the growth and movement of the systems that develop into thunderstorms using techniques that have been developed for short-term weather forecasts (“nowcasting”), using general storm properties that can be monitored by radars or satellites as a proxy for lightning activity. This approach can provide significantly longer advance warnings of pos- Figure 12. Detail of a screen image from the WSI Fusion Display, showing a combination of aircraft track, flight plans, and radar imagery (in shades of green) as a background for CG lightning strikes that are color-coded, with the most recent strikes plotted as white “plus” signs (figure courtesy of WSI).

21 sible lightning activity than other approaches, but with less accuracy. The convective nowcasting approach is well-suited for haz- ardous operations such as missile ranges and weapons test- ing, which require a long lead time to shut down or reschedule operations and a high probability of detection of a potential hazard. These systems will, however, normally have a corre- spondingly high false alarm rate. With respect to commercial airport operations, most long-range predictions of this sort would be considered only as an advisory forecast; they would not mandate that activities be rescheduled or that operations be shut down. Shutting down ramp operations at a busy airport is a major decision that cannot be taken lightly; there is thus a low tolerance for false alarms. In most cases, there will likely be a natural hesitancy to clear the ramp on the basis of a “pre- diction” without some additional evidence of nearby lightning strikes. While most studies of lightning prediction have naturally concentrated on forecasting the initial onset of lightning activity, the same observing systems may also be able to pro- vide valuable information about the cessation of a lightning hazard as storms are dying down and moving out. In those cases, the technologies may be able to provide objective crite- ria for shortening the duration of ramp closures after a warn- ing is sounded. Monitoring the Local Atmospheric Electric Field As already discussed, electric field measurements can de- tect the presence of high levels of charge separation in nearby clouds that suggests a strong likelihood of current or future lightning activity. These systems have the unique potential to provide advance warning of the first lightning strike from a developing storm. This ability to offer an advance prediction of the first light- ning strike makes these systems particularly attractive for applications where response time is critical, such as athletic fields and golf courses with limited access to sheltered areas and stadiums that would take a long time to clear of spectators. Monitoring and Predicting Overall Storm Evolution Lightning activity is an integral part of the life-cycle of a thunderstorm. For example, Figure 15 shows a summary of Figure 13. A screen image of the DTN/Meteorlogix online Lightning Manager, showing a combination of radar and lightning data, with a user-configured warning and advisory pop-up window (figure courtesy of DTN/Meteorlogix).

22 the evolution of an intensely studied, microburst-producing thunderstorm. The bottom two panels show vertical profiles of the time evolution of the storm radar reflectivity and updraft strength, while the top panel shows the IC and CG lightning activity. In this storm, the initial mid-level strengthening of the radar echo preceded an intensive growth period, with the highest lightning flash rates well correlated with the period of the maximum updrafts. This storm’s ratio of IC to CG light- ning strikes was unusually high, but follows the normal pattern of IC lightning developing several minutes before the first CG stroke. Storm studies such as shown in Figure 15 indicate that lightning data, particularly IC lightning data, are a valuable indicator of the updraft strength and can play an important role in short-term prediction of storm behavior. At the same time, observations of storm strength and evolution can be used as an approximate indicator of lighting activity. In recent years, there have been a number of significant advances in the short-term forecasting of thunderstorm activity, including pre- dicting areas of new growth and explosive development (22). Using standard meteorological data sets, including output from numerical models, radar, and satellite observations, storm nowcasting has proved to be a valuable tool for understand- ing and predicting storm behavior and evolution. Given the importance of timely predictions of hazardous weather, it is natural that storm forecasters are now beginning to generate short-term, high-resolution lightning forecasts (23). Figure 16 shows a graphical depiction of the results of a lightning prediction algorithm included in WDT’s Lightning Decision Support System (LDSS). This algorithm combines real-time lightning observations with storm-cell motion tracks to identify separate moderate and high threat areas out to 30 min in advance. A similar system, which combines radar and lightning observations to provide lightning warn- ings for a variety of public service applications, including airport ground operations, is currently under development in Australia (24). Figure 14. A screen image of the main ITWS weather display, including a simple lightning alert button.

23 Total Lightning as a Predictor for Ground Strikes The CG lightning events that are the focus of the NLDN and the USPLN lightning detection networks make up only a small fraction of all lightning activity. Studies, such as the one depicted in Figure 15, show that systems that can monitor all lightning strokes will be able to perform detailed monitoring of the time-resolved flash rates and the areal extent of a storm’s lightning activity. Since IC lightning is normally a precursor to the first CG strokes, total lightning systems can be used to identify storms that are entering an active lightning-generation period and act as a predictor for subsequent CG lightning strikes (25). While it is important to remember that it is the CG lightning flashes that represent the actual hazard to ground operations, IC lightning activity is a direct indicator of a given storm’s lightning potential and thus should be a uniquely valuable short-term predictor of the CG hazard. As a predictor, total lightning is also attractive since it is based on an observed event, rather than dependent on extrapolated storm behaviors. While current lightning detection networks can detect some IC lightning flashes, high-efficiency detection of IC lightning events will require the network sensors to be enhanced, com- bined with a significant increase in the number of network sensors. As an attractive alternative to a nationwide enhance- ment of the current lightning detection networks, a number of regional total lightning networks could well be embedded within the national CG networks. The regional total light- ning systems could provide improved storm monitoring and prediction capabilities as well as enhanced lightning de- tection capabilities for a wide variety of community-based applications. Sometime after 2014, the next generation of U.S. geosta- tionary meteorological satellites is expected to include a large- area optical lightning mapper. From geostationary orbit, this instrument will provide total-lightning observations at a spatial resolution of about 10 km. While this is much lower resolu- tion than would be provided by a dedicated regional sensor network, the 10-km resolution would still provide a valuable measurement of the extent of the IC lightning and help define the areal extent of the lightning hazard. Perhaps more impor- tant, data from the satellite-based system would be available via free, real-time broadcasts from space. Figure 15. Lightning and precipitation history of a severe thunderstorm (21). The bottom panel shows the updraft strength in the main cell as a function of time and height. The middle panel shows the corresponding evolution of the radar reflectivity, while the top panel shows the lightning activity correlated with significant features in the storm’s evolution.

24 Figure 16. An example of the WDT lightning prediction algorithm running within the WDT LDSS. The algorithm is based on the current lightning observations, coupled with the expected evolution of the storm, as reflected by its radar signature and indicates the location and magnitude of the expected lightning threat 30 min into the future (figure courtesy of WDT).

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TRB’s Airport Cooperative Research Program (ACRP) Report 8: Lightning-Warning Systems for Use by Airports explores the operational benefits associated with delay reductions that lightning detection and warning systems may be able to generate. The report is designed to help in the assessment of whether such systems are cost-beneficial on an individual airport or airline basis.

An ACRP Impacts on Practice related to ACRP Report 8 was produced in 2011.

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