Modes and manifestations of the explosive activity in the Earth’s magnetotail, as well as its onset mechanisms and key pre-onset conditions are reviewed. Two mechanisms for the generation of the pre-onset current sheet are discussed, namely magnetic flux addition to the tail lobes, or other high-latitude perturbations, and magnetic flux evacuation from the near-Earth tail associated with dayside reconnection. Reconnection onset may require stretching and thinning of the sheet down to electron scales. It may also start in thicker sheets in regions with a tailward gradient of the equatorial magnetic field ; in this case it begins as an ideal-MHD instability followed by the generation of bursty bulk flows and dipolarization fronts. Indeed, remote sensing and global MHD modeling show the formation of tail regions with increased , prone to magnetic reconnection, ballooning/interchange and flapping instabilities. While interchange instability may also develop in such thicker sheets, it may grow more slowly compared to tearing and cause secondary reconnection locally in the dawn-dusk direction. Post-onset transients include bursty flows and dipolarization fronts, micro-instabilities of lower-hybrid-drift and whistler waves, as well as damped global flux tube oscillations in the near-Earth region. They convert the stretched tail magnetic field energy into bulk plasma acceleration and collisionless heating, excitation of a broad spectrum of plasma waves, and collisional dissipation in the ionosphere. Collisionless heating involves ion reflection from fronts, Fermi, betatron as well as other, non-adiabatic, mechanisms. Ionospheric manifestations of some of these magnetotail phenomena are discussed. Explosive plasma phenomena observed in the laboratory, the solar corona and solar wind are also discussed.

Subauroral Polarization Streams (SAPS) are associated with closure of region 2 field-aligned current (R2 FAC) through the low conductivity region. Although SAPS have often been studied from a magnetosphere-ionosphere coupling perspective, recent observations suggest strong interaction also exists between SAPS and the thermosphere. Our study focuses on thermospheric wind driving and its impact on SAPS and R2 FAC during the 17 March 2013 geomagnetic storm using both observations and the physics-based Rice Convection Model-Coupled Thermosphere, Ionosphere, Plasmasphere, electrodynamics (RCM-CTIPe) model that self-consistently couples the magnetosphere-ionosphere-thermosphere system. Defense Meteorological Satellite Program (DMSP)-18 and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite observations show that, as the storm progresses, sunward ion flows intensify and expand equatorward and are accompanied by strengthening of subauroral neutral winds with some delay. Our model successfully reproduces time evolution and overall structure of the sunward ion drift and neutral wind. A force term analysis is performed to investigate the momentum transfer to the neutrals from the ions. Contrary to previous studies showing that Coriolis force is the main driver of neutrals during storm time, we find that the ion drag is the largest force driving westward neutral wind in the SAPS region where the ion density is low in the trough region. Furthermore, simulations with and without the neutral wind dynamo effect are compared to quantify the effect of the neutral to plasma flow. The comparison shows that the self-consistent active ionosphere thermosphere coupling increases the R2 FAC and the westward ion drift equatorward of the SAPS region by 20% and 40% by the flywheel effect, respectively.

Distinguishing the processes that occur during the first 2 min of a substorm depends critically on the correct timing of different signals between the plasma sheet and the ionosphere. To investigate signal propagation paths and signal travel times, we use a magnetohydrodynamic global simulation model of the Earth magnetosphere and ionosphere, OpenGGCM‐CTIM model. By creating single impulse or sinusoidal pulsations in various locations in the magnetotail, the waves are launched, and we investigate the paths taken by the waves and the time that different waves take to reach the ionosphere. We find that it takes approximately about 27, 36, 45, 60, and 72 s for waves to travel from the tail plasma sheet at x =− 10,−15,−20,−25, and −30RE, respectively, to the ionosphere, contrary to previous reports. We also find that waves originating in the plasma sheet generally travel faster through the lobes than through the plasma sheet.

Forecasting geomagnetically induced currents (GICs) remains a difficult challenge, and open questions hindering our understanding include when and where GICs become large and what magnetospheric and ionospheric processes are responsible. This paper addresses these questions by determining the auroral drivers of large dB∕dt (>100 nT/min, a proxy for GICs) on the ground during geomagnetic storms. We study auroras because, although the current system driving dB∕dt is at times challenging to reconstruct, the accompanying auroras are routinely measured in high resolution. For various types of auroras, our community has already acquired a deep understanding of the driving mechanisms and spatiotemporal characteristics. Using coordinated observations from THEMIS and Geophysical Institute Magnetometer Array magnetometers and THEMIS all‐sky imagers, we statistically examine large dB∕dt intervals during storms from 2015 to 2016. A variety of auroral drivers have been identified, including poleward expanding auroral bulges, auroral streamers, poleward boundary intensifications, omega bands, pulsating auroras, etc. The onset, spatial variability, and duration of large dB/dt are well explained by those of the auroras. For example, poleward expanding auroral bulges drive large dB/dt that spread progressively poleward, and periodic injections of streamers drive large dB/dt that occur in periodic bursts. By referring to the magnetospheric source of the auroras, the magnetospheric source of large dB/dt can be inferred, whether it be dipolarization of the tail magnetic field, bursty bulk flows, instability, or wave‐particle interaction. Our results suggest that auroras can exert significant leverage on GIC research and forecast.

Abstract. In magnetospheric missions, burst-mode data sampling should be triggered in the presence of processes of scientific or operational interest. We present an unsupervised classification method for magnetospheric regions that could constitute the first step of a multistep method for the automatic identification of magnetospheric processes of interest. Our method is based on self-organizing maps (SOMs), and we test it preliminarily on data points from global magnetospheric simulations obtained with the OpenGGCM-CTIM-RCM code. The dimensionality of the data is reduced with principal component analysis before classification. The classification relies exclusively on local plasma properties at the selected data points, without information on their neighborhood or on their temporal evolution. We classify the SOM nodes into an automatically selected number of classes, and we obtain clusters that map to well-defined magnetospheric regions. We validate our classification results by plotting the classified data in the simulated space and by comparing with k-means classification. For the sake of result interpretability, we examine the SOM feature maps (magnetospheric variables are called features in the context of classification), and we use them to unlock information on the clusters. We repeat the classification experiments using different sets of features, we quantitatively compare different classification results, and we obtain insights on which magnetospheric variables make more effective features for unsupervised classification.

Abstract. In magnetospheric missions, burst mode data sampling should be triggered in the presence of processes of scientific or opera- tional interest. We present an unsupervised classification method for magnetospheric regions, that could constitute the first-step of a multi-step method for the automatic identification of magnetospheric processes of interest. Our method is based on Self Organizing Maps (SOMs), and we test it preliminarily on data points from global magnetospheric simulations obtained with the OpenGGCM-CTIM-RCM code. The classification relies exclusively on local plasma properties at the selected data points, without information on their neighborhood or on their temporal evolution. We classify the SOM nodes into an automatically selected number of classes, and we obtain clusters that map to well defined magnetospheric regions. For the sake of result interpretability, we examine the SOM feature maps (magnetospheric variables are called features in the context of classification), and we use them to unlock information on the clusters. We repeat the classification experiments using different sets of features, and we obtain insights on which magnetospheric variables make more effective features for unsupervised classification.

Abstract. It is well known that the polar cap, delineated by the open–closed field line boundary (OCB), responds to changes in the interplanetary magnetic field (IMF). In general, the boundary moves equatorward when the IMF turns southward and contracts poleward when the IMF turns northward. However, observations of the OCB are spotty and limited in local time, making more detailed studies of its IMF dependence difficult. Here, we simulate five solar storm periods with the coupled model consisting of the Open Geospace General Circulation Model (OpenGGCM) coupled with the Coupled Thermosphere Ionosphere Model (CTIM) and the Rice Convection Model (RCM), i.e., the OpenGGCM-CTIM-RCM, to estimate the location and dynamics of the OCB. For these events, polar cap boundary location observations are also obtained from Defense Meteorological Satellite Program (DMSP) precipitation spectrograms and compared with the model output. There is a large scatter in the DMSP observations and in the model output. Although the model does not predict the OCB with high fidelity for every observation, it does reproduce the general trend as a function of IMF clock angle. On average, the model overestimates the latitude of the open–closed field line boundary by 1.61∘. Additional analysis of the simulated polar cap boundary dynamics across all local times shows that the MLT of the largest polar cap expansion closely correlates with the IMF clock angle, that the strongest correlation occurs when the IMF is southward, that during strong southward IMF the polar cap shifts sunward, and that the polar cap rapidly contracts at all local times when the IMF turns northward.

In‐situ measurements in the magnetotail are sparse and limited to single points. On the other hand, there is a broad range of observations, including magnetometers, aurora imagers, and radars, in the ionosphere. Since the nightside ionosphere resembles the magnetotail plasma sheet dynamics projection, it can be used to monitor the tail's dynamics. A proper interpretation of the ionosphere and ground observations necessitates understanding the coupling processes between the ionosphere and the magnetosphere. Here, we use the global magnetohydrodynamic simulation model, OpenGGCM‐CTIM‐RCM, to investigate these coupling processes during periods when the magnetic flux is transported through the tail via narrow fast flow channels, typically called bursty bulk flows (BBFs). We consider three relevant states of the magnetotail: immediately before the substorm's onset, during the expansion of the substorm, and during a steady magnetic convection (SMC) event. The number of flow channels increases, and they penetrate closer to the Earth during SMC. The IMF By direction influences fast flows' location but not their orientation in the plasma sheet during this event. However, the dimension of fast flows and streamers do not depend on the IMF conditions and state of the magnetosphere.