The intensity of first positive return strokes (RSs) is positively correlated with rise time and pulse width of E-change waveforms of the RSs • The intensity of first positive RSs is related with the preliminary breakdown and preceding leader processes • Strongest positive RSs usually occur in a short time (<10 ms) after lightning initiation, preceded by a fast (∼10 6 m/s) positive leader

A machine-learning classifier for radiation waveforms of negative return strokes (RSs) is built and tested based on the Random Forest classifier using a large dataset consisting of 14,898 negative RSs and 159,277 intracloud (IC) pulses with 3-D location information. Eleven simple parameters including three parameters related with pulse characteristics and eight parameters related with the relative strength of pulses are defined to build the classifier. Two parameters for the evaluation of the classifier performance are also defined, including the classification accuracy, which is the percentage of true RSs in all classified RSs, and the identification efficiency, which is the percentage of correctly classified RSs in all true RSs. The tradeoff between the accuracy and the efficiency is examined and simple methods to tune the tradeoff are developed. The classifier achieved the best overall performance with an accuracy of 98.84% and an efficiency of 98.81%. With the same technique, the classifier for positive RSs is also built and tested using a dataset consisting of 8,700 positive RSs. The classifier has an accuracy of 99.04% and an efficiency of 98.37%. We also demonstrate that our classifiers can be readily used in various lightning location systems. By examining misclassified waveforms, we show evidence that some RSs and IC discharges produce special radiation waveforms that are almost impossible to correctly classify without 3-D location information, resulting in a fundamental difficulty to achieve very high accuracy and efficiency in the classification of lightning radiation waveforms.

A gamma‐ray glow, a minute‐lasting burst of high‐energy photons from a thundercloud, was detected by ground‐based apparatus at Kanazawa University, Japan, in a winter thunderstorm on 18 December 2018. The gamma‐ray glow was quenched by a lightning flash within a brief time window of 40 ms. The lightning flash produced several low‐frequency (LF) E‐change pulses that were temporally coincident with the termination of the gamma‐ray glow, and that were located within 0.5 km from the observation site by the Fast Antenna Lightning Mapping Array. The LF pulses had the same polarity as a positive cloud‐to‐ground current and a normal‐polarity in‐cloud current. Since this polarity is against the upward electric field for producing the gamma‐ray glow (accelerating electrons to the ground), we infer that the glow was terminated by a normal‐polarity in‐cloud discharge activity between a middle negative layer and an upper positive layer.

Ground-based lightning location systems (LLSs) are widely used to monitor lightning activities. A prominent feature of ground-based LLSs is that lightning activities in a wide area can be monitored in real time with only a limited number of sensors. Some famous national and continental LLSs include the National Lightning Detection Network (NLDN) covering the continental United States (e.g., Cummins & Murphy, 2009), the European Cooperation for Lightning Detection network (EUCLID) covering the European continent (e.g., Schulz et al., 2016), and the Earth Networks Total Lightning Network (ENTLN) (e.g., Zhu et al., 2022) with the aim of a global coverage.It is a basic requirement for LLSs to automatically and efficiently classify cloud-to-ground (CG) lightning flashes from intracloud (IC) flashes as the former consist of discharges with direct connections to the ground and thus pose a much larger threat to the human society. The fundamental difference between a CG flash and an IC flash is that a CG flash contains one or more return strokes (RSs), so the classification of CG flashes is basically realized by classifying RSs. Further, it is well known that RSs produce characteristic electric field radiation waveforms that are largely different from those of IC discharges (e.g., Lin et al., 1979), so most LLSs classify RSs based on their waveform characteristics.

Gamma rays from thunderclouds are direct evidence of ∼ 30 MeV electron acceleration by static electric field in the sky. On 2021/12/30, five consecutive Terrestrial Gamma-ray Flashes (TGFs) were detected by our gamma-ray detectors placed on Kanazawa City, Japan. Although analog signals of our gamma-ray detectors were severely saturated, timing of the five TGFs were well constrained and compared with radio observations. We detected four slow radio pulses associated with the first four TGFs, which were located ∼ 3 km south from the on-going upward negative lightning discharge. Our results suggests that the TGF's acceleration location can be a few km apart from the leader development of the main discharge activity.