The number of cloud-to-ground (CG) flashes over the contiguous United States (CONUS) has been estimated to be from as small as 25 million per year to as many as 40 million. In addition, many CG flashes contact the ground in more than one place. To clarify these values, recent data from the National Lightning Detection Network (NLDN) have been examined since the network is performing well enough to make precise updates to the number of CG flashes and their associated ground contact points. The average number of CG flashes is calculated to be about 23.4 million per year over the CONUS, and the average number of ground contact points is calculated as 36.8 million per year. Knowledge of these two parameters is critical to lightning protection standards, as well as better understanding of the effects of lightning on forest fire initiation, geophysical interactions, human safety, and applications that benefit from knowing that a single flash may transfer charge to the ground in multiple, widely spaced locations. Sensitivity tests to assess the effects of misclassification of CG and in-cloud (IC) lightning are also made to place bounds on these estimates, and the likely uncertainty is a few percent.

Nepal has a very large topographical variation; this elevation change has a major influence on lightning occurrence and human casualties. The Himalayan peaks cover the northern part of Nepal with low population density, the middle is covered by hills with intermediate density, and the southern plain with the greatest density. This study will leverage lightning detection by Vaisala’s Global Lightning Dataset GLD360 network with a recent detailed compilation of lightning casualties from 2011 through 2020. Over one million lightning strokes per year were detected from 2016 through 2020. Stroke density is least over high elevations to the north, moderate in hilly regions, and very frequent over the south. The thunderstorm season begins in March and ceases by August after the annual monsoon cycle. Of all the natural disasters, lightning has been recorded to be the second highest killer after earthquakes. The Ministry of Home Affairs reports an average of 103 lightning deaths per year. The fatality rate of 3.8 deaths million−1 year−1 is highest among the South Asian countries. Fatalities over high mountains are rare, with most casualties over the center of Nepal. Lightning Fatality Risk is not a good indicator of the fatalities that occur in a district.

Lightning over the Caribbean, and Jamaica in particular, has received minimal attention until recently. Locations of Jamaica lightning from a global detection network from 2017–2021 show greater stroke densities over the interior than along the coasts. Nearly all lightning occurs from May through October, and from 1200 to 1800 EST. The resulting impacts are considered by summarizing two damaged buildings, two sports delays, and 18 human casualty reports resulting in 16 deaths and 39 injuries from 2005 through 2021. Jamaica lightning casualties are most often males between 10 and 29 years old, occur between June and October, and in the afternoon. Being near trees, farming, playing soccer, and seeking safety inside small structures are recurring scenarios.

The U.S. National Lightning Detection Network (NLDN) underwent a complete sensor upgrade in 2013 followed by a central processor upgrade in 2015. These upgrades produced about a factor-of-5 improvement in the detection efficiency of cloud lightning flashes and about one additional cloud pulse geolocated per flash. However, they also reaggravated a historical problem with the tendency to misclassify a population of low-current positive discharges as cloud-to-ground strokes when, in fact, most are probably cloud pulses. Furthermore, less than 0.1% of events were poorly geolocated because the contributing sensor data were either improperly associated or simply underutilized by the geolocation algorithm. To address these issues, Vaisala developed additional improvements to the central processing system, which became operational on 7 November 2018. This paper describes updates to the NLDN between 2013 and 2018 and then focuses on the effects of classification algorithm changes and a simple means to normalize classification across upgrades.

The location accuracy of the U.S. National Lightning Detection Network (NLDN) has been evaluated using as ground‐truth rocket‐triggered lightning data or video records but only at a few specific locations. In this study, by using the NLDN data for the events attributable to lightning strikes to towers, the location error of the NLDN across the entire contiguous United States was evaluated for the first time. We found that, on average, the NLDN median location error reduced from 198 to 84 m after the 2013 NLDN upgrade. The location error at the periphery of the network is significantly larger than that in its interior. In the coastal regions, there is directional location bias toward the water. Simulation results suggest that the bias is related to the lengthening of field waveform front due to electromagnetic wave propagation over lossy ground coupled with the asymmetrical sensor configuration relative to the strike point (lack of offshore sensors).

Updates were made to the NLDN central processor (CP) on August 18, 2015. In this study, we examine the effect of the latest updates by comparing lightning data reported by the new and old NLDN central processors in the interior of the network. About 13.1 million lightning events (CG strokes and cloud pulses) were reported by the NLDN during the chosen period (August 20 and December 10, 2015). Of these, the majority, about 63%, were cloud flashes. On average, 2.3 pulses were reported per cloud flash. The average multiplicity (number of strokes per flash) for negative and positive cloud-to-ground flashes was 2.7 and 1.4, respectively. Overall, the new CP reported 30% more cloud pulses and 8.5% more cloud flashes relative to the old CP. There is no major change in the number of reported negative first and subsequent strokes. The 15 kA peak current limit below which all positive lightning events were classified as cloud has been removed in the new NLDN CP. This has resulted in a significant change in the classification of positive polarity events. Further investigation is necessary to examine the characteristics of positive events, especially those in the 2-10 kA range, being reported by the new CP as cloud-to-ground strokes. Keywords— U.S. NLDN; performance characteristics; cloud lightning; cloud-to-ground lightning; detection efficiency; location accuracy; peak current

Updates were made in 2013 to the U.S. National Lightning Detection Network (NLDN) that has led to performance improvements. Vaisala’s LS7002 sensors have been deployed, replacing the older generation LS7001 and IMPACT sensors. The LS7002 takes advantage of the LS7001’s digital sensor technology and provides improved embedded software with enhanced features. This improves the sensitivity of the sensor to low amplitude lightning-generated signals and leads to enhanced detection of cloud and cloud-to-ground lightning. Additionally, the central processor algorithms in the NLDN are being updated to include new techniques for classifying lightning using multiple waveform parameters, a “burst processing” algorithm for geolocation of multiple pulses in lightning pulse trains, and improved handling of electromagnetic wave propagation resulting in smaller arrival-time errors. The median location accuracy (given by the length of the semi-major axis of the 50% error ellipse) the NLDN is expected to be about 200 m in the interior of the network. These performance characteristics continue to be validated by triggered lightning, tower strikes, network inter-comparison, and camera studies. We examine lightning discharges reported by the NLDN in early September to late November, 2013 within the interior of the contiguous United States. The large majority (87%) of flashes reported by the NLDN were ICs. Of the CG flashes reported by the NLDN during this period 81% were negative and 19% were positive. The average multiplicity (number of strokes were flash) for negative CG flashes was 2.7 and for positive CG flashes was 1.4. The negative and positive first stroke median peak current was 15 kA and 19 kA, respectively. Keywords—U.S. NLDN; performance characteritics; cloud lightning; cloud-to-ground lightning; detection efficiency; location accuracy; peak current

In spring and summer 2013, Vaisala upgraded all sensors in the U.S. National Lightning Detection NetworkTM (NLDNTM) to the new LS7002 sensor. This improved sensor has enhanced sensitivity to cloud discharges, including the ability to process multiple pulses in cloud discharge pulse trains, or “bursts”, and to send that information back to the central processor. To accompany the new sensor development, we also deployed new localization algorithms, one of which properly handles inter-pulse time intervals within pulse bursts and is capable of determining the positions of multiple pulses within bursts. These improvements are expected to improve the cloud flash detection efficiency of the NLDN as well as the spatial resolution of cloud flashes. During the summer and fall of 2013, data from some small thunderstorms were processed using the improved algorithms, and the results were compared to highresolution VHF lightning mapping data from two Lightning Mapping Arrays. The objectives of this analysis were to determine the extent to which the anticipated improvements in cloud flash detection efficiency have been realized and to determine where there may be room for additional improvements. Keywords—cloud lightning, NLDN, validation

Using measured wideband electric field waveforms and the Hertzian dipole (HD) approximation, we estimated peak currents for 48 located compact intracloud lightning discharges (CIDs) in Florida. The HD approximation was used because 1) CID channel lengths are expected to range from about 100 to 1000 m, and in many cases can be considered electrically short and 2) it allows one to considerably simplify the inverse source problem. Horizontal distances to the sources were reported by the U. S. National Lightning Detection Network (NLDN), and source heights were estimated from the horizontal distance and the ratio of electric and magnetic fields. The resultant CID peak currents ranged from 33 to 259 kA with a geometric mean of 74 kA. The majority of NLDN-reported peak currents for the same 48 CIDs are considerably smaller than those predicted by the HD approximation. The discrepancy is primarily because NLDN-reported peak currents are assumed to be proportional to peak fields, while for the HD approximation, the peak current is proportional to the peak of the integral of the electric radiation field. An additional factor is the limited (400 kHz) upper frequency response of the NLDN.

We examined 52 positive cloud-to-ground flashes containing 63 return strokes recorded in Gainesville, Florida, in 2007-2008. The U.S. National Lightning Detection Network located 51 (96%) of the positive return strokes at distances of 7.8 to 157 km from the field measuring station and correctly identified 48 (91%) of them as cloud-to-ground discharges. The average number of strokes per flash (multiplicity) is 1.2. In three (38%) of eight two-stroke flashes, the second stroke likely followed the channel of the first stroke and in five (62%) flashes it likely created a new termination on ground. The characteristics of positive return-stroke electric field and field derivative waveforms are analyzed. The GM values of initial electric field peak normalized to 100 km for 48 positive return strokes and corresponding NLDN-reported peak current are 18.1 V/m and 74.6 kA, respectively.

We examined wideband electric fields, electric and magnetic field derivatives, and narrowband VHF (36 MHz) radiation bursts produced by 157 compact intracloud discharges (CIDs). These poorly understood lightning events appear to be the strongest natural producers of HF‐VHF radiation. All the events transported negative charge upward (or lowered positive charge), 150 were located by the U.S. National Lightning Detection Network (NLDN), and 149 of them were correctly identified as cloud discharges. NLDN‐reported distances from the measurement station were 5–132 km. Three types of wideband electric field waveforms were observed. About 73% of CIDs occurred in isolation; 24% occurred prior to, during, or following cloud‐to‐ground or “normal” cloud lightning; and 4% occurred in pairs, separated by less than 200 ms (“multiple” CIDs). For a subset of 48 CIDs, the geometric mean of radiation source height was estimated to be 16 km. It appears that some CIDs actually occurred above cloud tops in clear air or in convective surges (plumes) overshooting the tropopause and penetrating deep into the stratosphere. For the same 48 CIDs, the geometric mean electric field peak normalized to 100 km (inclined distance) was as high as 20 V/m, and for 22 events within 10–30 km (horizontal distance), it was 15 V/m, both of which are higher than that for first strokes in negative cloud‐to‐ground lightning. The geometric means of total electric field pulse duration, width of initial half cycle, and ratio of initial peak to opposite polarity overshoot were 23 μs, 5.6 μs, and 5.7, respectively.

Video recordings of cloud-to-ground (CG) lightning flashes have been analyzed in conjunction with correlated stroke reports from the U. S. National Lightning Detection Network (NLDN) to determine whether the NLDN is capable of identifying the different ground contacts in CG flashes. For 39 negative CG flashes that were recorded on video near Tucson, Arizona, the NLDN-based horizontal distances between the first stroke and the 62 subsequent strokes remaining in a preexisting channel had a mean and standard deviation of 0.9 +/- 0.8 km and a median of 0.7 km. The horizontal distances between the first stroke and the 59 new ground contacts (NGCs) had a mean and standard deviation of 2.3 +/- 1.7 km and a median of 2.1 km. These results are in good agreement with prior measurements of the random errors in NLDN positions in southern Arizona as well as video-and thunder-based measurements of the distances between all ground contacts in Florida. In cases where the distances between ground contacts are small and obscured by random errors in the NLDN locations, measurements of the stroke rise time, estimated peak current, and stroke order can be utilized to enhance the ability of the NLDN to identify strokes that produce new ground terminations.

The U.S. National Lightning Detection Network (NLDNTM) has been providing real-time, continental-scale information on cloud-to-ground (CG) lightning to research and operational users since 1989, and has been the lightning data source for the NOAA National Weather Service for more than a decade. This network has undergone regular improvements during its 15year lifetime. The intent of this paper is to provide research and operational users of NLDN data with a contemporary view of the strengths and limitations of this data resource.

This study compares the lightning locations reported by the National Lightning Detection Network (NLDN) with the lightning locations determined by the Lightning Imaging Sensor (LIS). The NLDN system identifies the rf signature of cloud-to-ground lightning. The LIS data is the top level of a hierarchy of optical data objects. The centroid and timing of each LIS lightning activity center are compared with each flash in a subset of the NLDN long range lightning location data in a portion of the Atlantic Ocean and the Caribbean Sea consisting of those locations more than 625 km from any sensor. This subset is produced by analyzing each reported NLDN location to determine if that location is within the LIS field of view at the time of the reported flash. The Tropical Rainfall Measuring Mission Satellite (TRMM) orbit limits the cross-sensor comparison to tropical and sub-tropical regions. Because the rf-detection system depends on ionospheric propagation conditions, a separate analysis was made for daylight conditions at both source and sensor as well as nighttime at both places. A full year of data is compared to provide an adequate sample of each data set. Confirmation of lightning in the general location of the NLDN report is established when LIS detected one or more centers of lightning activity within a 2 degree radius from the NLDN location.