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Martin J. Murphy, John A. Cramer, and Ryan K. Said


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-five improvement in the detection efficiency of cloud lightning flashes and about one additional cloud pulse geo-located per flash. However, they also re-aggravated 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 geo-located because the contributing sensor data were either improperly associated or simply under-utilized by the geo-location algorithm. To address these issues, Vaisala developed additional improvements to the central processing system, which became operational on November 7, 2018. This paper describes updates to the NLDN between 2013-2018 and then focuses on the effects of classification algorithm changes and a simple means to normalize classification across upgrades.

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Christina A. Stall, Kenneth L. Cummins, E. Philip Krider, and John A. Cramer


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.

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