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Abstract High‐intensity long‐duration continuous auroral electrojet (AE) activity (HILDCAA) events are associated with intensification of relativistic electron fluxes in the inner magnetosphere. The physical mechanisms of this intensification are not well established yet. We study observations by the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft in the near earth plasma sheet at radial distances of 10 Earth radii, at the transition region between tail and dipole‐like magnetic configurations, referred to as the nightside transition region (NTR), during a HILDCAA event. The observations revealed recurrent dipolarizations accompanied by plasma flow vortices, impulsive electric field enhancements, and increases in electron fluxes at energies of 100 keV up to 1 MeV. Electron pitch angle (PA) distributions at THEMIS showed field‐aligned flux enhancements at energies of 100 keV. This indicates a Fermi‐type energization. Arguably, electrons gain energy up to MeV via repetitive bouncing through the acceleration region. Energization of ions was insignificant which led to 1. We suggest that the increased ratio leads to a local increase of the Hall conductivity in the conjugate ionosphere, which causes ionospheric current intensification and strong , consistent with observations. 

Ground-based magnetometers used to measure magnetic fields on the Earth’s surface (B) have played a central role in the development of Heliophysics research for more than a century. These versatile instruments have been adapted to study everything from polar cap dynamics to the equatorial electrojet, from solar wind-magnetosphere-ionosphere coupling to real-time monitoring of space weather impacts on power grids. Due to their low costs and relatively straightforward operational procedures, these instruments have been deployed in large numbers in support of Heliophysics education and citizen science activities. They are also widely used in Heliophysics research internationally and more broadly in the geosciences, lending themselves to international and interdisciplinary collaborations; for example, ground-based electrometers collocated with magnetometers provide important information on the inductive coupling of external magnetic fields to the Earth’s interior through the induced electric field (E). The purpose of this white paper is to (1) summarize present ground-based magnetometer infrastructure, with a focus on US-based activities, (2) summarize research that is needed to improve our understanding of the causes and consequences of B variations, (3) describe the infrastructure and policies needed to support this research and improve space weather models and nowcasts/forecasts. We emphasize a strategic shift to proactively identify operational efficiencies and engage all stakeholders who need B and E to work together to intelligently design new coverage and instrumentation requirements. 

Abstract Although lagged correlations have suggested influences of solar wind velocity (V) and number density (N), Bz, ultralow frequency (ULF) wave power, and substorms (as measured by the auroral electrojet (AE) index) on MeV electron flux at geosynchronous orbit over an impressive number of hours and days, a satellite's diurnal cycle can inflate correlations, associations between drivers may produce spurious effects, and correlations between all previous time steps may create an appearance of additive influence over many hours. Autoregressive‐moving average transfer function (ARMAX) multiple regressions incorporating previous hours simultaneously can eliminate cycles and assess the impact of parameters, at each hour, while others are controlled. ARMAX influences are an order of magnitude lower than correlations uncorrected for time behavior. Most influence occurs within a few hours, not the many hours suggested by correlation. A log transformation accounts for nonlinearities. Over all hours, solar wind velocity (V) and number density (N) show an initial negative impact, with longer term positive influences over the 9 (V) or 27 (N) hr. Bz is initially a positive influence, with a longer term (6 hr) negative effect. ULF waves impact flux in the first (positive) and second (negative) hour before the flux measurement, with further negative influences in the 12–24 hr before. AE (representing electron injection by substorms) shows only a short term (1 hr) positive influence. However, when only recovery and after‐recovery storm periods are considered (using stepwise regression), there are positive influences of ULF waves, AE, andV, with negative influences ofNand Bz. 

A circuit analogy for magnetosphere-ionosphere current systems has two extremes for drivers of ionospheric currents: the “voltage generator” (ionospheric electric fields/voltages are constant, while current varies) and the “current generator” (current is constant, while the electric field varies). Here we indicate another aspect of the magnetosphere-ionosphere interaction, which should be taken into account when considering the current/voltage dichotomy. We show that nonsteady field-aligned currents interact with the ionosphere in a different way depending on a forced driving or resonant excitation. A quasi-DC driving of field-aligned current corresponds to a voltage generator, when the ground magnetic response is proportional to the ionospheric Hall conductance. The excitation of resonant field line oscillations corresponds to the current generator, when the ground magnetic response only weakly depends on the ionospheric conductance. According to the suggested conception, quasi-DC nonresonant disturbances correspond to a voltage generator. Such ultralow frequency (ULF) phenomena as traveling convection vortices and Pc5 waves should be considered as the resonant response of magnetospheric field lines, and they correspond to a current generator. However, there are quite a few factors that may obscure the determination of the current/voltage dichotomy. 

This paper presents observations of electromagnetic ion cyclotron (EMIC) waves from multiple data sources during the four Geospace Environment Modeling challenge events in 2013 selected by the Geospace Environment Modeling Quantitative Assessment of Radiation Belt Modeling focus group: 17 and 18 March (stormtime enhancement), 31 May to 2 June (stormtime dropout), 19 and 20 September (nonstorm enhancement), and 23–25 September (nonstorm dropout). Observations include EMIC wave data from the Van Allen Probes, Geostationary Operational Environmental Satellite, and Time History of Events and Macroscale Interactions during Substorms spacecraft in the near-equatorial magnetosphere and from several arrays of ground-based search coil magnetometers worldwide, as well as localized ring current proton precipitation data from low-altitude Polar Operational Environmental Satellite spacecraft. Each of these data sets provides only limited spatial coverage, but their combination shows consistent occurrence patterns and reveals some events that would not be identified as significant using near-equatorial spacecraft alone. Relativistic and ultrarelativistic electron flux observations, phase space density data, and pitch angle distributions based on data from the Relativistic Electron-Proton Telescope and Magnetic Electron Ion Spectrometer instruments on the Van Allen Probes during these events show two cases during which EMIC waves are likely to have played an important role in causing major flux dropouts of ultrarelativistic electrons, particularly near L* ~4.0. In three other cases, identifiable smaller and more short-lived dropouts appeared, and in five other cases, these waves evidently had little or no effect. 

Abstract Many factors influence relativistic outer radiation belt electron fluxes, such as waves in the ultralow frequency (ULF) Pc5, very low frequency (VLF), and electromagnetic ion cyclotron (EMIC) frequency bands, seed electron flux, Dst disturbance levels, substorm occurrence, and solar wind inputs. In this work we compared relativistic electron flux poststorm versus prestorm using three methods of analysis: (1) multiple regression to predict flux values following storms, (2) multiple regression to predict the size and direction of the change in electron flux, and (3) multiple logistic regression to predict only the probability of the flux rising or falling. We determined which is the most predictive model and which factors are most influential. We found that a linear regression predicting the difference in prestorm and poststorm flux (Model 2) results in the highest validation correlations. The logistic regression used in Model 3 had slightly weaker predictive abilities than the other two models but had the most value in providing a prediction of the probability of the electron flux increasing after a storm. Of the variables used (ULF Pc5 and VLF, seed electrons, substorm activity, and EMIC waves), the most influential in the final model were ULF Pc5 waves and the seed electrons. IMF Bz, Dst, and solar wind number density, velocity, and pressure did not improve any of the models, and were deemed unnecessary for effective predictions.