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

As part of an ongoing collaboration between Tohoku Electric Power Company, Vaisala, Sankosha, and the University of Arizona, propagation corrections have been implemented in Tohoku's two overlapping LLS networks: a 6-sensor LS700x research LLS and the operational 9-sensor IMPACT (141T) LLS. In addition, new arrival-time onset-corrections have been implemented in the six LS700x sensors. Sensor arrival-time consistency was improved by (roughly) a factor of two in the older IMPACT LLS (as a result of propagation corrections), and more than a factor of three in the new LS700x LLS (propagation and onset corrections). Estimates of “relative” location accuracy (LA) improvements, based on an analysis of location differences for return strokes that shared the same ground strike point, indicate that the IMPACT LLS median LA improved from ∼400m to ∼270m using propagation corrections, and that the LA for the LS network is ∼100m using both propagation and onset corrections. Analysis of return stroke locations produced by the LS network that were associated with four transmission line faults showed locations that were between 60m and 390m from the verified fault location. The actual line-attachment locations cannot be determined, so these errors are likely an upper-bound on the actual location error.

The demand for both data quality and the range of Cloud-to-Ground (CG) lightning parameters is highest for forensic applications within the electric utility industry. For years, the research and operational communities within this industry in Japan have pointed out a limitation of these LLS networks in the detection and location of damaging (high-current and/or large charge transfer) lightning flashes during the winter months (so-called “Winter Lightning”). Most of these flashes appear to be upward-connecting discharges, frequently referred to as “Ground-to-Cloud” (GC) flashes. The basic architecture and design of Vaisala’s new LS700x lightning sensor was developed in-part to improve detection of these unusual and complex flashes. This paper presents our progress-to-date on this effort. We include a review of the winter lightning detection problem, an overview of the LS700x architecture, a discussion of how this architecture was exploited to evaluate and improve performance for winter lightning, and a presentation of results-to-date on performance improvement. A comparison of GC detection performance between Tohoku’s operational 9-sensor IMPACT (ALDF 141-T) LLS and its 6-sensor LS700x research network indicates roughly a factor-of-two improvement for this class of discharges, with an overall detection of 23/24 (96%) of GC flashes.