Laser Lightning Rod

H. Karami; A. Mostajabi; M. Azadifar; M. Rubinstein; C. Zhuang et al. “Machine Learning-Based Lightning Localization Algorithm Using Lightning-Induced Voltages on Transmission Lines,” IEEE Transactions on Electromagnetic Compatibility. 2020. Vol. 62, num. 6, p. 2512-2519. https://doi.org/10.1109/TEMC.2020.2978429

In this article, we present a machine learning-based method to locate lightning flashes using calculations of lightning-induced voltages on a transmission line. The proposed approach takes advantage of the preinstalled voltage measurement systems on power transmission lines to get the data. Hence, it does not require the installation of additional sensors such as extremely low frequency, very low frequency, or very high frequency. The proposed model is shown to yield reasonable accuracy in estimating two-dimensional geolocations for lightning strike points for different grid sizes up to 100 × 100 km ² . The algorithm is shown to be robust against the distance between the voltage sensors, lightning peak current, lightning current rise time, and signal to noise ratio of the input signals.

Q. Li; F. Rachidi; M. Rubinstein; J. Wang; L. Cai et al. “Measurement and Modeling of Both Distant and Close Electric Fields of an M-Component in Rocket-Triggered Lightning,” Journal of Geophysical Research: Atmospheres. 2020. Vol. 125, num. 21. https://doi.org/10.1029/2019JD032300

Simultaneous measurements of current and multiple-station electric fields associated with a 5.4-kA-peak M-component in rocket-triggered lightning are presented in this study. A close-range electric field measurement site was located northeast of the triggering site, 195° clockwise from South, at a distance of 78 m, while the distant multiple stations in this study were located southwest of the lightning triggering site (25–48°, clockwise from South) at a distance ranging from 69 to 126 km. Both the fast microsecond-scale and slow millisecond-scale pulses were observed at six distant stations. At the close station, the fast pulse was not noticeable. The magnitude and half-peak width of the fast pulse were in the range of 0.91–1.93 V/m and 2.0–3.0 μs, respectively. The corresponding parameters for the slow pulse were, respectively, in the range of 0.59–1.29 V/m and 20.0–25.1 μs. The time lag between the onset of the channel-base current and the far electric field of the M-component was 18 μs. This time lag was used to deduce the ratio of the M-component channel length and the wave speed. The classical guided wave M-component model proposed by Rakov et al. (1995, https://doi.org/10.1029/95JD01924) to simulate the slow, millisecond-scale field pulse assumes that neither the incident nor the reflected current wave undergoes attenuation even though the wave propagation occurs along a lossy channel. A modified guided wave M-component model is proposed in this study in which the M-component current wave attenuates with an exponential decay. Based on the best agreement achieved between the simulated fields using the modified two-wave M-component model and the observed near and far electric fields, the channel length, the M-component wave speed, and the current attenuation constant were inferred, respectively, as 1.8 km, 1 × 10⁸ m/s, and 3 km. It is shown that the modified guided wave M-component model is able to reproduce reasonably well the electric fields both at close and far distance ranges.

E. W Rosenthal, I. Larkin, A. Goffin, T. Produit, M. C. Schoeder, J.-P. Wolf and H. M. Milchberg, “Dynamics of the femtosecond laser-triggered spark gap,” Optics Express 28, 24599 (2020) https://doi.org/10.1364/OE.398836

We present space and time resolved measurements of the air hydrodynamics induced by femtosecond laser pulse excitation of the air gap between two electrodes at high potential difference. We explore both plasma-based and plasma-free gap excitation. The former uses the plasma left in the wake of femtosecond filamentation, while the latter exploits air heating by multiple-pulse resonant excitation of quantum molecular wavepackets. We find that the cumulative electrode-driven air density depression channel plays the dominant role in the gap evolution leading to breakdown. Femtosecond laser heating serves mainly to initiate the depression channel; the presence of filament plasma only augments the early heating.

W. Hou; M. Azadifar; M. Rubinstein; F. Rachidi; Q. Zhang, “The Polarity Reversal of Lightning- Generated Sky Wave,” Journal of Geophysical Research: Atmospheres. 2020. Vol. 125, num. 17, p. 1-17, e2020JD032448. https://doi.org/10.1029/2020JD032448

The polarity reversal of the lightning-generated first sky wave as a function of the observation distance is studied using a novel approach combining the finite-difference time domain (FDTD) method and the superposition principle of electromagnetic waves. In this method, the sky wave is generated by radiation from the induced current produced by the motion of charged particles driven by the lightning-radiated electromagnetic waves in the ionosphere. The horizontal and vertical components of the induced current density under the daytime and nighttime ionospheric conditions are evaluated. Their different contributions to the sky wave at different observation distances are analyzed in detail. Furthermore, a physical explanation for the polarity reversal in the time domain is proposed. It is found that, for relatively short observation distances (within ~200 km), the first sky wave is dominated by the component generated by the horizontal equivalent current in the Fresnel zone, while for longer observation distances (larger than ~300 km), the first sky wave is dominated by the component generated by the vertical equivalent current in the Fresnel zone. Since the polarities of the sky wave components generated by the vertical current source and horizontal current source are opposite, the polarity of the sky wave will reverse when increasing the observation distance.

A. Mostajabi, D. L. Finney, M. Rubinstein, F. Rachidi, npj Climate and Atmospheric Science 2, 41 (2019)
Link

Abstract: Lightning discharges in the atmosphere owe their existence to the combination of complex dynamic and microphysical processes. Knowledge discovery and data mining methods can be used for seeking characteristics of data and their teleconnections in complex data clusters. We have used machine learning techniques to successfully hindcast nearby and distant lightning hazards by looking at single-site observations of meteorological parameters. We developed a four-parameter model based on four commonly available surface weather variables (air pressure at station level (QFE), air temperature, relative humidity, and wind speed). The produced warnings are validated using the data from lightning location systems. Evaluation results show that the model has statistically considerable predictive skill for lead times up to 30 min. Furthermore, the importance of the input parameters fits with the broad physical understanding of surface processes driving thunderstorms (e.g., the surface temperature and the relative humidity will be important factors for the instability and moisture availability of the thunderstorm environment). The model also improves upon three competitive baselines for generating lightning warnings: (i) a simple but objective baseline forecast, based on the persistence method, (ii) the widely-used method based on a threshold of the vertical electrostatic field magnitude at ground level, and, finally (iii) a scheme based on CAPE threshold. Apart from discussing the prediction skill of the model, data mining techniques are also used to compare the patterns of data distribution, both spatially and temporally among the stations. The results encourage further analysis on how mining techniques could contribute to further our understanding of lightning dependencies on atmospheric parameters.

M. C. Schroeder, I. Larkin, T. Produit, E. W. Rosenthal, H. Milchberg and J.-P. Wolf, “Molecular quantum wakes for clearing fog”, Optics Express 28, 11463 (2020) https://doi.org/10.1364/OE.389393

High intensity laser filamentation in air has recently demonstrated that, through plasma generation and its associated shockwave, fog can be cleared around the beam, leaving an optically transparent path to transmit light. However, for practical applications like free-space optical communication (FSO), channels of multi-centimeter diameters over kilometer ranges are required, which is extremely challenging for a plasma based method. Here we report a radically different approach, based on quantum control. We demonstrate that fog clearing can also be achieved by producing molecular quantum wakes in air, and that neither plasma generation nor filamentation are required. The effect is clearly associated with the rephasing time of the rotational wave packet in N₂.Pump excitation provided in the form of resonant trains of 8 pulses separated by the revival time are able to transmit optical data through fog with initial extinction as much as −6 dB.

H. Karami; M. Azadifar; A. Mostajabi; M. Rubinstein; F. Rachidi, “Numerical and Experimental Validation of Electromagnetic Time Reversal for Geolocation of Lightning Strikes,” IEEE Transactions on Electromagnetic Compatibility. 2020. Vol. 62, num. 5, p. 2156-2163. https://doi.org/10.1109/TEMC.2019.2957531

We implement an electromagnetic time reversal technique (EMTR) to locate lightning return strokes. The two-dimensional finite difference time domain is employed to simulate the EMTR process in both, the forward-time and the backward-time phases. Scatterers are included in the computational domain to emulate the presence of objects. Three possible criteria to find the optimum time slice of the EMTR process that includes the maximum peak field, maximum peak energy, and last local minimum of entropy are tested and it is found that only the entropy criterion can successfully locate the lightning discharge. Our analysis shows that the EMTR process in both, using an unchanged and a simplified medium for the backward time works reasonably well even with only two sensors. Furthermore, we validated the proposed method via experimental results using waveforms recorded at two sensors at distances of 14.7 and 380 km from the Säntis Tower. The results demonstrate that the EMTR back-propagation process leads to a refocusing of the radiated energy at the location of the Säntis Tower. The ambiguity in the obtained location when only two sensors are used can be resolved either by using an additional sensor or through a more accurate modeling of the terrain.