The effect of anthropogenic aerosols on lightning is one of the least understood aspects of human‐induced climate change. Global aerosol clearly diminished during the COVID pandemic by 7.6%. A pronounced decrease in global lightning activity in the range 3.0%–5.8% is identified from various detection systems during this natural experiment. The Maritime Continent lightning chimney shows the largest reduction of 7.0% in aerosol accompanied by a lightning drop of 15%. The COVID period in 2020 also experiences a transition from pre‐COVID El Niño to a strong and sustained La Niña. Compensation for ENSO forcing of lightning activity is implemented to disclose the distinct responses of three global lightning chimneys to competing thermodynamic and aerosol effects. Our observational findings indicate a marked influence of aerosol on a global scale by virtue of the extraordinary COVID‐induced aerosol alteration.

ABSTRACTLightning strikes to wind turbines (WTs) pose significant hazards and operational costs to the renewable wind industry. These strikes fall into two categories: downward cloud‐to‐ground (CG) strokes and upward discharges, which can be self‐initiated or triggered by a nearby flash. The incidence of each type of strike depends on several factors, including the electrical structure of the thunderstorm and turbine height. The strike rates of CG strokes and triggered upward lightning can be normalized by the amount of local lightning activity, where the constant of proportionality carries units of area and is often termed the collection area. This paper introduces a statistical analysis technique that uses lightning locating system (LLS) data to estimate the collection areas for downward and triggered upward lightning strikes to WTs. The technique includes a normalization method that addresses the confounding factor of neighboring WTs. This analysis method is applied to 7 years of data from the National Lightning Detection Network and the US WT Database to investigate the dependence of collection areas on blade tip height. The results are compared against estimates of collection areas derived from counts of LLS‐detected CG strokes close to WTs.

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.

The Earth-ionosphere waveguide (EIW) determines the propagation of Very Low Frequency (VLF; similar to 3-30 kHz) waves. Characterizing the waveguide is a longstanding challenge due to its large spatial scale and the complex variability of the lower ionosphere. Here we apply a novel linear basis function regression technique to characterize attenuation in the EIW using broadband measurements of lightning-generated radio waves. The process begins with defining a basis function set, which ideally encompasses a feature set that can predict the variability seen in VLF attenuation properties. With this basis set defined, a system of linear equations is then constructed using sensor pair observations to eliminate the dependency on source amplitude in each observation. Using this formalism, an empirical attenuation model for broadband signals from lightning is constructed and the dependence on attenuation properties with the boundary conditions is explored. The empirically derived results show attenuation rates over ice that are 12 dB/Mm higher compared to paths over saltwater. Well-known east/west attenuation rate asymmetry stemming from anisotropic reflection coefficients of the ionosphere is also demonstrated and investigated. For example, under a daytime ionosphere, westward-propagating waves suffer up to 2.8 dB/Mm greater attenuation compared to eastward-propagating waves. The trained model is used for propagation corrections in a global lightning locating system (LLS), but this technique can be expanded to further study VLF attenuation rates by employing different sets of basis functions.

The importance of lightning has long been recognized from the point of view of climate-related phenomena. However, the detailed investigation of lightning on global scales is currently hindered by the incomplete and spatially uneven detection efficiency of ground-based global lightning detection networks and by the restricted spatio-temporal coverage of satellite observations. We are developing different methods for investigating global lightning activity based on Schumann resonance (SR) measurements. SRs are global electromagnetic resonances of the Earth-ionosphere cavity maintained by the vertical component of lightning. Since charge separation in thunderstorms is gravity-driven, charge is typically separated vertically in thunderclouds, so every lightning flash contributes to the measured SR field. This circumstance makes SR measurements very suitable for climate-related investigations. In this study, 19 days of global lightning activity in January 2019 are analyzed based on SR intensity records from 18 SR stations and the results are compared with independent lightning observations provided by ground-based (WWLLN, GLD360 and ENTLN) and satellite-based (GLM, LIS/OTD) global lightning detection. Daily average SR intensity records from different stations exhibit strong similarity in the investigated time interval. The inferred intensity of global lightning activity varies by a factor of 2-3 on the time scale of 3-5 days which we attribute to continental-scale temperature changes related to cold air outbreaks from polar regions. While our results demonstrate that the SR phenomenon is a powerful tool to investigate global lightning, it is also clear that currently available technology limits the detailed quantitative evaluation of lightning activity on continental scales.

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.

Advances in global lightning detection have provided novel ways to characterize explosive volcanism. However, researchers are still at the early stages of understanding how volcanic plumes become electrified on different spatial and temporal scales. We deconstructed the phreatomagmatic eruption of Taal volcano (Philippines) on 12 January 2020 to investigate the origin of its powerful volcanic thunderstorm. Satellite analysis indicated that the waterrich plume rose >10 km high before creating lightning detected by Vaisala's global lightning data set (GLD360). Flash rates increased with plume heights and cloud expansion over time, producing >70 flashes min(-1). Photographs revealed a highly electrified region at the base of the umbrella cloud, where we infer strong convective updrafts and icy collisions enhanced the electrical activity. These findings inform a conceptual model with overlapping regimes of charge generation in wet eruptions-initially due to ash particle collisions near the vent, followed by thunderstorm-like electrification in icy regions of the upper plume. Despite the wide reach of Taal's ash cloud, most of the lightning occurred within 20-30 km of the volcano, producing thousands of hazardous cloud-to-ground flashes over a densely populated area. The eruption demonstrates that volcanic lightning can pose a hazard in its own right, embedded within the broader hazards of explosive volcanism in an urban setting.

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.

Terrestrial gamma ray flashes (TGFs) are a class of enigmatic electrical discharges in the Earth’s atmosphere. In this study, we analyze an unprecedentedly large dataset comprised of 2188 TGFs whose signatures were simultaneously measured using space- and ground-based detectors over a five-year period. The Gamma-ray Burst Monitor (GBM) on board the Fermi spacecraft provided the energetic radiation measurements. Radio frequency (RF) measurements were obtained from the Global Lightning Dataset (GLD360). Here we show the existence of two categories of TGFs − those that were accompanied by quasi-simultaneous electromagnetic pulses (EMPs) detected by the GLD360 and those without such simultaneous EMPs. We examined, for the first time, the dependence of the TGF-associated EMP-peak-amplitude on the horizontal offset distance between the Fermi spacecraft and the TGF source. TGFs detected by the GBM with sources at farther horizontal distances are expected to be intrinsically brighter and were found to be associated with EMPs having larger median peak-amplitudes. This provides independent evidence that the EMPs and TGFs are produced by the same phenomenon, rather than the EMPs being from “regular” lightning in TGF-producing thunderstorms.

This study explores the causes of a severe thunderstorm outbreak north of 70 degrees N on 24-25 July 2014 and provides the first characterization of lightning over the Canadian Arctic Islands. Lightning data were obtained from the Global Lightning Dataset (GLD360) network. Convective available potential energy calculated using representative soundings and surface conditions indicated high instability that, combined with large vertical wind shear and storm-relative helicity, likely caused severe thunderstorms to form over Victoria Island. These storms subsequently drifted northeastward over Parry Channel, where they transitioned into elevated storms and travelled as far north as and passed close to Grise Fiord (76.4 degrees N). Satellite imagery suggested that overshooting tops reached 11.6 km. The GLD360 network detected more than 15,000 strokes north of the Arctic Circle and an unusually high ratio of positive strokes during this outbreak.

Flash-level comparisons between the Geostationary Lightning Mapper (GLM; primarily from GOES-16), the U.S. National Lightning Detection Network (NLDN), and the Global Lightning Dataset GLD360 have been done at quasi-climatological scale and in smaller samples of both severe and nonsevere thunderstorms. A small sample of data from GOES-17 has also been analyzed. These comparisons show that the total lightning detection efficiencies of the GLM instruments drop off within about 2,000 km of the edges of their fields of view, particularly over terrestrial areas. In severe storms, low detection efficiency by GLM is clearly associated with very high midaltitude reflectivity, consistent with the idea that large multiple scattering path lengths, together with absorption of the near-infrared signals by water (in all of its phases), depresses the GLM detection efficiency. This effect appears to be coupled with additional factors, including time of day, flash energetics, and the incident angle at the GLM sensor. The "lightning jump," the sought-after signature of severe storms in lightning observations, tends to be poorly correlated between NLDN and GLM unless the storms are fairly isolated, not close to the edge of the GLM field of view, and have moderate midaltitude reflectivity.

The 2016–2017 shallow submarine eruption of Bogoslof volcano in Alaska injected plumes of ash and seawater to maximum heights of ~ 12 km. More than 4550 volcanic lightning strokes were detected by the World Wide Lightning Location Network (WWLLN) and Vaisala’s Global Lightning Dataset (GLD360) over 9 months. Lightning assisted monitoring efforts by confirming ash-producing explosions in near-real time, but only 32 out of the 70 explosive events produced detectable lightning. What led to electrical activity within some of the volcanic plumes, but not others? And why did the lightning intensity wax and wane over the lifetime of individual explosions? We address these questions using multiparametric observations from ground-based lightning sensors, satellite imagery, photographs, acoustic signals, and 1D plume modeling. Detailed time-series of monitoring data show that the plumes did not produce detectable lightning until they rose higher than the atmospheric freezing level (approximated by − 20 °C temperatures). For example, on 28 May 2017 (event 40), the delayed onset of lightning coincides with modeled ice formation in upper levels of the plume. Model results suggest that microphysical conditions inside the plume rivaled those of severe thunderstorms, with liquid water contents > 5 g m−3 and vigorous updrafts > 40 m s−1 in the mixed-phase region where liquid water and ice coexist. Based on these findings, we infer that ‘thunderstorm-style’ collisional ice-charging catalyzed the volcanic lightning. However, charge mechanisms likely operated on a continuum, with silicate collisions dominating electrification in the near-vent region, and ice charging taking over in the upper-level plumes. A key implication of this study is that lightning during the Bogoslof eruption provided a reliable indicator of sustained, ash-rich plumes (and associated hazards) above the atmospheric freezing level.

Large numbers of Bangladesh lightning fatalities during the pre-monsoon season have resulted in speculation about causes for this annual event. The present study addresses the situation with lightning occurrence, lightning fatality, and agricultural data. Of the 1,434 lightning deaths from 2013 to 2017 in Bangladesh, an average of 1.73 deaths occur per day in the pre-monsoon season, 0.71 in the monsoon, and very small averages in other seasons. More than half of the deaths are related to agriculture. Population-weighted fatality rates are large in several northeastern districts. Lightning fatalities are frequent in April and especially May during both morning and afternoon. Based on 37.2 million strokes from the Global Lightning Dataset GLD360 network over Bangladesh from 2013 to 2017, lightning is also most frequent in the northeast from mid-April through early June at all hours of the day. Several districts with large lightning stroke densities and fatality rates are the same as with the greatest farming participation. A common crop is Boro rice harvested during April and May in several districts with frequent lightning. As a result, temporal and spatial connections exist among lightning fatalities and occurrence, and agricultural workers. This study identifies the lightning fatality maximum during the pre-monsoon season as frequent lightning coincident with labor-intensive agricultural practices in specific locations. As a result, measures can be taken to address the underlying lightning vulnerability. Additionally, agricultural studies at the times and locations identified here need further exploration. The final steps are to provide meteorological warnings and lightning-safe locations for the most vulnerable population.

Very low frequency (VLF, 3–30 kHz) transmitter remote sensing has long been used as a simple yet useful diagnostic for the D region ionosphere (60–90 km). All it requires is a VLF radio receiver that records the amplitude and/or phase of a beacon signal as a function of time. During both ambient and disturbed conditions, the received signal can be compared to predictions from a theoretical model to infer ionospheric waveguide properties like electron density. Amplitude and phase have in most cases been analyzed each as individual data streams, often only the amplitude is used. Scattered field formulation combines amplitude and phase effectively, but does not address how to combine two magnetic field components. We present polarization ellipse analysis of VLF transmitter signals using two horizontal components of the magnetic field. The shape of the polarization ellipse is unchanged as the source phase varies, which circumvents a significant problem where VLF transmitters have an unknown source phase. A synchronized two‐channel MSK demodulation algorithm is introduced to mitigate 90° ambiguity in the phase difference between the horizontal magnetic field components. Additionally, the synchronized demodulation improves phase measurements during low‐SNR conditions. Using the polarization ellipse formulation, we take a new look at diurnal VLF transmitter variations, ambient conditions, and ionospheric disturbances from solar flares, lightning‐ionospheric heating, and lightning‐induced electron precipitation, and find differing signatures in the polarization ellipse.

We present the performance characteristics of a high-sensitivity radio receiver for the frequency band 0.5-470 kHz, known as the Low Frequency Atmospheric Weather Electromagnetic System for Observation, Modeling, and Education, or LF AWESOME. The receiver is an upgraded version of the VLF AWESOME, completed in 2004, which provided high sensitivity broadband radio measurements of natural lightning emissions, transmitting beacons, and radio emissions from the near-Earth space environment. It has been deployed at many locations worldwide and used as the basis for dozens of scientific studies. We present here a significant upgrade to the AWESOME, in which the frequency range has been extended to include the LF and part of the medium frequency (MF) bands, the sensitivity improved by 10-25 dB to be as low as 0.03 fT/Hz, depending on the frequency, and timing error reduced to 15-20 ns range. The expanded capabilities allow detection of radio atmospherics from lightning strokes at global distances and multiple traverses around the world. It also allows monitoring of transmitting beacons in the LF/MF band at thousands of km distance. We detail the specification of the LF AWESOME and demonstrate a number of scientific applications. We also describe and characterize a new algorithm for minimum shift keying demodulation for VLF/LF transmitters for ionospheric remote sensing applications.

Continuous detection by Vaisala’s Global Lightning Dataset GLD360 network now makes it possible to examine lightning across the globe. This study apportions continent-scale detection of 8.8 billion strokes from 2013 through 2017 by month through the year. Northern Hemisphere lightning peaks from May through September, while Southern Hemisphere strokes peak from November through March. North America, Europe, and Asia have a concentration of lightning in summer, although the annual distribution for Asia is not as distinct since part of the continent extends to the equator. South America and Australia have peak lightning from November through February. Africa shows only minor monthly variations throughout the year since the regions north of the equator have more lightning in the Northern Hemisphere summer, and the reverse in the south. These observations, along with complementary human casualty research, allow for a better understanding of lightning impacts on life and property

WeatherVolume 72, Issue 2 p. 36-40 Special Issue Article Towards a global lightning locating system Ryan Said, Corresponding Author Ryan Said ryan.said@vaisala.com Vaisala Inc, Louisville, CO, USACorrespondence to: Ryan Said, ryan.said@vaisala.comSearch for more papers by this author Ryan Said, Corresponding Author Ryan Said ryan.said@vaisala.com Vaisala Inc, Louisville, CO, USACorrespondence to: Ryan Said, ryan.said@vaisala.comSearch for more papers by this author First published: 03 February 2017 https://doi.org/10.1002/wea.2952Citations: 15Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume72, Issue2Special Issue: Developments in lightning detectionFebruary 2017Pages 36-40 RelatedInformation