One of the outstanding questions in lightning research is how dart leaders (also called recoil leaders or K-leaders) initiate and develop during a lightning flash. Dart leaders travel quickly (106-107 m/s) along previously ionized channels and occur intermittently in the later stage of a flash. We have recently reported some insights into dart leader initiation and development based on our BIMAP-3D observations. In this presentation we will expand on that work by combining observations and modeling to try to understand the observed dart leader behaviors. BIMAP-3D consists of two broadband interferometric mapping and polarization (BIMAP) systems that are separated by 11.5km at Los Alamos National Laboratory. Each station maps the lightning VHF sources in a 2D space, and the combination of the 2-station measurements provides a detailed 3D source map. A fast antenna is also included at each station for electric field change measurements. Our previously reported observations suggest dart leaders commonly exhibit an initial acceleration, followed by a more gradual deceleration to a stop. We also modeled the dart leader electric field change with a simple configuration of two point-charges, finding that the modeled tip charge increased in magnitude during the initial acceleration in some simple cases. We now employ a more sophisticated model to better understand the distribution of charge along the dart leader channel, and the background electric field in which the dart leader develops.Presented at the AGU 2023 Fall Meeting

In this paper, a numerical dart leader model has been implemented to understand the leader’s development and the corresponding electric field changes observed by the 3D Broadband Mapping And Polarization (BIMAP-3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre-dart-leader channel has a significant temperature of ~3000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well-defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

During the 2022 New Mexico monsoon season, we deployed two X-ray scintillation detectors, coupled with a 180 MHz data acquisition system to detect X-rays from natural lightning at the Langmuir Lab mountain-top facility, located at 3.3 km above mean sea level. Data acquisition was triggered by an electric field antenna calibrated to pick up lightning within a few km of the X-ray detectors. We report the energies of over 240 individual photons, ranging between 13 keV and 3.8 MeV, as registered by the LaBr3(Ce) scintillation detector. These detections were associated with four lightning flashes. Particularly, four stepped leaders and seven dart leaders produced energetic radiation. The reported photon energies allowed us to confirm that the X-ray energy distribution of natural stepped and dart leaders follows a power-law distribution with exponent ranging between 1.09 and 1.96, with stepped leaders having a harder spectrum. Characterization of the associated leaders and return strokes was done with four different electric field sensing antennas, which can measure a wide-range of time scales, from the static storm field to the fast change associated with dart leaders.

A document by Daniel Jensen. Click on the document to view its contents.

(Revised) The streamer to leader transition defines much of the physics of long sparks near atmospheric pressures. Streamer length is an important parameter in understanding lightning protection because of its link to step length and striking distance. While streamers are routinely observed in the lab, there have been only a few observations in the field. Fewer still are of natural flashes, and almost none have been observed much above sea-level.

Simultaneous data from two interferometers separated by 16 km and synchronized within 100 ns was collected for a thunderstorm near Langmuir Lab on October 23, 2018. Analysis via triangulation followed by a least-squares fit to time of arrival across all six antennae produced a three-dimensional interferometer data set (3DINTF). Simultaneous Lightning Mapping Array (LMA) data enabled an independent calculation of 3DINTF accuracy, yielding a median location uncertainty of 200 m. This is the most accurate verified result to date for a two-station interferometer. The 3D data allowed profiling the velocity of multiple dart leaders and K leaders that followed the same channel. 3D velocities calculated from the in-cloud initiation site to ground ranged from 3x10^6 m/s to 20x10^6 m/s. Average velocity generally increased with subsequent leaders, consistent with increased conditioning of the channel. Also, all leaders showed a factor of two to three decrease in velocity as they proceeded over 15 km of channel. We speculate that the velocity decrease is consistent with energy lost in the reionization of the channel at the leader tip. This paper includes an appendix providing details of the triangulation technique used.

Rakov and Uman pointed out (Lightning: Physics and Effects, 2003) that despite 5000 published reports of ball lightning (BL) and a scientific literature comparable in volume to the literature on conventional lightning, we still have no idea of what mechanisms create or power BL. Lightning characterization technology advances can and should be applied to BL studies. Keul and Diendorfer (2018) have correlated BL reports with European lightning-detection network data, but no such attempt has been made for US BL reports up to now. Using 31 BL reports from a now-defunct US website, we have attempted correlations with National Lightning Detection Network (NLDN) and radar data archived at the National Climactic Data Center. Of the 31 reports, 5 objects were indoors and 25 were reported to coincide with thunderstorms. Time information accurate to 30 minutes (1 sigma) and location information accurate within one to ten km was available from nine of the reports, and for these we obtained both NLDN and composite radar data covering the time frames indicated by the reports. For three of the nine reports, we found NLDN located strikes plausibly within the distance and time frames of the observer reports – thus qualifying as nearby (possibly causal) lightning. However, for the report for which the location of the ball was known within meters, the nearest lightning was 2.3 km away. 23 reports only associate BL with a storm within 25 km. Should it continue to hold in the face of more evidence, the relative lack of correlation of BL and nearby lightning suggests that the production of BL is associated more with static or changing electric fields in the vicinity of thunderstorms, than with the lightning plasma channel itself. While these results by themselves are limited, we are optimistic that one can learn more about the link between natural and ball lightning by fusing more precise eyewitness reports with lightning location and other archival meteorological data. To this end, we have launched a website to guide citizen scientists in future ball lightning reports. The site may be reached via https://tinyurl.com/BLReport.

On June 2nd and 3rd, 2019, 65 sprites were captured with a Phantom V2010 camera recording at 100,000 frames per second from Langmuir Laboratory (LL) in New Mexico. An extra sensitive slow-antenna known as LEFA, located 25 km east of LL, measured E-fields simultaneous with the video observations. Data from the Earth Networks Total Lightning Network (ENTLN) was used to locate their parent flash. By correlating all these datasets, we found the largest fraction of sprites with current signatures (45%) observed to date. These measured sprites have strong electromagnetic signatures comparable in magnitude to the largest current moments previously reported in the peer-reviewed literature, with range-normalized electric field changes of half the amplitude of their parent flashes, and current moments of up to 2742 kA km, as derived from a new computationally-efficient technique introduced here. Comparison to high-speed optical recordings shows also that optically-large sprites tend to have larger electrical currents.

The Earth Networks Total Lightning Network (ENTLN) is a global lighting detection network that has been operational since 2009. The ENTLN sensors are broadband electric field sensors that detect both intra-cloud (IC) and cloud-to-ground (CG) flashes and provide timing, location, classification, and peak current measurements. ENTLN consists of roughly 1600 wideband sensors deployed globally. Since its initial deployment, several improvements were made over the years to enhance its performance and usability. Notable ones are the addition of many new sensors each year to improve detection efficiency and extend global coverage. Firmware improvements have also been made to further increase sensitivity. A multi-parameter algorithm was incorporated to enhance IC and CG classification. To validate these improvements, Earth Networks has sponsored several studies to provide valuable feedback on performance improvements. This presentation will highlight two such studies. The first was performed at the Lightning Observatory in Gainesville (LOG), Florida using a combination of high-speed cameras and electric field sensors. For the 608 flashes in this study, a flash detection efficiency (DE) of 99% was found. Also, 97% of the flashes classified as CG by ENTLN algorithms were confirmed as CG via the measurements at LOG. The second study was performed at Langmuir Laboratory in New Mexico. In this study, 546 flashes were analyzed from three separate storms and ENTLN data was compared to simultaneously acquired interferometer (INTF) and electric field change array data (LEFA). Results show a total DE of 97.5%. Ninety one percent of flashes categorized at CG by EN were suggested to be CG by correlation of the LEFA+INTF data. Where EN determined the flash to be IC, LEFA+INTF agreed in 84% of cases.