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Intriguing phenomena have been recently observed in gaseous discharges which involve dust particles, and discharges which are produced in the ionosphere involving formation of upward-directed lightning.
Lightning in the protoplanetary nebula has been proposed as a mechanism for creating meteoritic chondrules: enigmatic mm-sized silicate spheres formed in the nebula by the brief melting of cold precursors.
Two overlapping efforts help to characterize the GLM performance, the Post Launch Test (PLT) phase to validate the predicted pre-launch instrument performance and the Post Launch Product Test (PLPT) phase to validate the lightning detection product used in forecast and warning decision-making. This paper documents the calibration and validation plans and activities for the first 6 months of GLM on-orbit testing and validation commencing with first light on 4 January 2017. The PLT phase addresses image quality, on-orbit calibration, RTEP threshold tuning, image navigation, noise filtering, and solar intrusion assessment, resulting in a GLM calibration parameter file. The PLPT includes four main activities, the Reference Data Comparisons (RDC), Algorithm Testing (AT), Instrument Navigation and Registration Testing (INRT), and Long Term Baseline Testing (LTBT). Field campaigns are also designed to contribute valuable insights into the GLM performance capabilities. The PLPT tests each contribute to the beta, provisional, and fully validated GLM data.
Video and still frame images from cameras aboard the International Space Station (ISS) are used to inspire, educate, and provide a unique vantage point from low-Earth orbit that is second to none; however, these cameras have overlooked capabilities for contributing to scientific analysis of the Earth and near-space environment. The goal of this project is to study how geo referenced video/images from available ISS camera systems can be useful for scientific analysis, using lightning properties as a demonstration.
CubeSpark is a project under development to make 3-D observations of lightning with CubeSats using combined RF and optical measurements.
Computational models of the Earth System are critical tools for modern scientific inquiry. Effortstoward evaluating and improving errors in representations of physical and chemical processes inthese large computational systems are commonly stymied by highly nonlinear and complexerror behavior. Recent work has shown that these errors can be effectively predicted usingmodern Artificial Intelligence (A.I.) techniques. In this work, we go beyond these previousstudies to apply an interpretable A.I. technique to not only predict model errors but also movetoward understanding the underlying reasons for successful error prediction. We use XGBoostclassification trees and SHapley Additive exPlanations (SHAP) analysis to explore the errors inthe prediction of lightning occurrence in the NASA GEOS model, a widely used Earth SystemModel. This explainable error prediction system can effectively predict the model error andindicates that the errors are strongly related to convective processes and the characteristics ofthe land surface.
A high level description of the lightning sensors provided by MSFC for the 2023 ALOFT campaign.
NASA operates a high-speed camera (a MIRO M310 manufactured by Vision Research) on the fourth floor of the Operations and Checkout Building pointed at the communications tower that is in the Industrial Area of Kennedy Space Center. Figure 1 shows the location of the camera and tower. Figure 2 shows the camera view during daylight. On 7 August 2023 between 11 pm and 12 am eastern standard time, three lightning flashes to the tower were recorded.
The fundamental electromagnetic equations used by lightning researchers were introduced in a seminal paper by Uman, McLain, and Krider in 1975. However, these equations were derived for an infinitely thin, one-dimensional source current, and not for a general three-dimensional current distribution. In this paper, we introduce a corresponding pair of generalized equations that are determined from a three-dimensional, time-dependent current density distribution based on Jefimenko's original electric and magnetic equations. To do this, we derive the Jefimenko electric field equation into a new form that depends only on the time-dependent current density similar to that of Uman, McLain, and Krider, rather than on both the charge and current densities in its original form. The original Jefimenko magnetic field equation depends only on current, so no further derivation is needed. We show that the equations of Uman, McLain, and Krider can be readily obtained from the generalized equations if a one-dimensional source current is considered. For the purpose of practical applications, we discuss computational implementation of the new equations and present electric field calculations for a three-dimensional, conical-shape discharge.
Abstract Computational models of the Earth System are critical tools for modern scientific inquiry. Efforts toward evaluating and improving errors in representations of physical and chemical processes in these large computational systems are commonly stymied by highly nonlinear and complex error behavior. Recent work has shown that these errors can be effectively predicted using modern Artificial Intelligence (A.I.) techniques. In this work, we go beyond these previous studies to apply an explainable A.I. technique to not only predict model errors but also move toward understanding the underlying reasons for successful error prediction. We use XGBoost classification trees and SHapley Additive exPlanations analysis to explore the errors in the prediction of lightning occurrence in the NASA Goddard Earth Observing System model, a widely used Earth System Model. This explainable error prediction system can effectively predict the model error and indicates that the errors are strongly related to convective processes and the characteristics of the land surface.
A model of electric energization of the solar wind and corona is developed, including electro-magnetic particle effects precluded by traditional magneto-hydro (MHD) assumptions. Using standard 1D radial solar models for particle density and temperature, the core gravito-electric field is calculated; and the range of possible photospheric photo-electric fields is estimated. The extant DC field apparently arises from about 460 C of charge displacement, mainly caused by the immense solar energy flux pushing electrons outward. Energetically, this electric field can accelerate surface protons out of the 2 keV gravity well and up to the 4 keV energies observed in the fast solar wind. The electrical energy is released in pervasive, persistent “proton lightning jets,” which are proton beams, charge-neutralized by co-propagating electrons. The jets are formed by pinched “avalanche breakdown” of the weakly ionized photosphere, probably initiated on the down-welling edges of solar surface granulations. These energetic jets will glow as discrete filamentary surface spicules and will be observed in reflected solar light as the diffuse K-corona. Significantly, the total charge displacement and observed fast wind speed are quantitatively predicted by a novel “virial limit”: the (positive) electrical potential energy at r = 0 is limited in magnitude to the 10 keV gravitational well at r = 0.
This article proposes a multiport modular single-stage current-source solid-state transformer (SST) for applications like photovoltaic, energy storage integration, electric vehicle fast charging, data center, etc. The 7.2 kV 50 kVA current-source SST consists of five input-series output-parallel modules, each based on 3.3 kV SiC reverse-blocking MOSFET-plus-diode modules. The proposed SST has some unique features. First, compared to the voltage-source or matrix converter-based SSTs, the current-source SST has a unique advantage of single-stage isolated AC/DC or AC/AC conversion with an inductive DC link, but no medium-voltage (MV) AC experiments have been reported. This article for the first time demonstrates MV AC current-source SST up to 7.5 kV peak. Second, the multiport SST has a buffer port for active power decoupling (APD) or energy storage integration. The double-line-frequency power ripple from single-phase AC grid normally results in a large capacitor size in MV SSTs. The APD scheme is proposed in MV applications for the first time to enable a reduced DC link and the electrolytic capacitor-less SST with high reliability. Third, as a direct grid-connected converter without line-frequency transformer, insulation and protection are critical. A medium-frequency transformer design passes 55 kV basic-insulation level (BIL) and 60 kV high potential dielectrics withstand test with only 0.09% leakage inductance. Importantly, a lightning protection scheme is presented to protect the SST itself from 90 kV BIL impulse. Fourth, the proposed current-source SST topology is a modular soft-switching solid-state transformer (M-S4T) with full-range zero-voltage switching and controlled dv/dt for low electromagnetic interference. Furthermore, these concepts are verified in a three-port M-S4T prototype with forced oil cooling under single-module, stacked-module, steady-state, and dynamic operations.
These are the slides for all of the 2016 T Division lightning talks. There are 350 pages worth of slides from different presentations, all of which cover different topics within the theoretical division at Los Alamos National Laboratory (LANL).
All members of the T Division Community, students, staff members, group leaders, division management, and other interested individuals are invited to come and support the following student(s) as they present their Lightning Talks.
Interior Electromagnetic Fields of Buildings Struck by Lightning
Research done at Pantex in 2020 of 20 different storms from February through November showed an average lead time of around 20 minutes from when “source densities” were detected inside developing thunderstorms over the Texas Panhandle to when the first cloud-to-cloud or cloud-to-ground lightning strike occurred.
We assemble bounding formulas for the interior fields and pin voltages inside a cylindrical coaxial Faraday cage which has been struck by lightning. Approximate formulas for penetrations through a circumferential door slot with subsequent coupling to the interior center conductor structure. Fields at the opposite open end are estimated and used to drive a capped connector and estimate interior pin voltages. Finally, penetrations through small circular holes and direct diffusion through the barrier are also addressed.
Sferics from lightning from warm cloud, noting microsecond pulse-train format and temporal duration