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Abstract Extreme (>20 nT/s) geomagnetic disturbances (GMDs, also denoted as MPEs—magnetic perturbation events)—impulsive nighttime disturbances with time scale ∼5–10 min, have sufficient amplitude to cause bursts of geomagnetically induced currents (GICs) that can damage technical infrastructure. In this study, we present occurrence statistics for extreme GMD events from five stations in the MACCS and AUTUMNX magnetometer arrays in Arctic Canada at magnetic latitudes ranging from 65° to 75°. We report all large (≥6 nT/s) and extreme GMDs from these stations from 2011 through 2022 to analyze variations of GMD activity over a full solar cycle and compare them to those found in three earlier studies. GMD activity between 2011 and 2022 did not closely follow the sunspot cycle, but instead was lowest during its rising phase and maximum (2011–2014) and highest during the early declining phase (2015–2017). Most of these GMDs, especially the most extreme, were associated with high‐speed solar wind streams (Vsw >600 km/s) and steady solar wind pressure. All extreme GMDs occurred within 80 min after substorm onsets, but few within 5 min. Multistation data often revealed a poleward progression of GMDs, consistent with a tailward retreat of the magnetotail reconnection region. These observations indicate that extreme GIC hazard conditions can occur for a variety of solar wind drivers and geomagnetic conditions, not only for fast‐coronal mass ejection driven storms. 

Abstract We explore the characteristics of EMIC waves generated in a non‐dipole, compressed magnetic field at the minimum of the magnetic field. We conducted 2D full‐wave simulations using the Petra‐M code, focusing on a compressed magnetic field in the outer dayside magnetosphere for a range ofLvalues . By comparing the simulation results with MMS observations, we aim to understand how the observed wave characteristics are affected by a shifting source region across different L‐shells. Our findings indicate that the direction of the Poynting vector systematically changes depending on the local source location of the wave, which is consistent with the observations. EMIC waves propagate along the magnetic field line and reach both the northern and southern hemispheres; however, there is a notable difference in the power of EMIC waves between the two hemispheres, indicating seasonal asymmetries in their occurrence. 

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. 

Magnetometers are a key component of heliophysics research providing valuable insight into the dynamics of electromagnetic field regimes and their coupling throughout the solar system. On satellites, magnetometers provide detailed observations of the extension of the solar magnetic field into interplanetary space and of planetary environments. At Earth, magnetometers are deployed on the ground in extensive arrays spanning the polar cap, auroral and sub-auroral zone, mid- and low-latitudes and equatorial electrojet with nearly global coverage in azimuth (longitude or magnetic local time—MLT). These multipoint observations are used to diagnose both ionospheric and magnetospheric processes as well as the coupling between the solar wind and these two regimes at a fraction of the cost of in-situ instruments. Despite their utility in research, ground-based magnetometer data can be difficult to use due to a variety of file formats, multiple points of access for the data, and limited software. In this short article we review the Open-Source Python library GMAG which provides rapid access to ground-based magnetometer data from a number of arrays in a Pandas DataFrame, a common data format used throughout scientific research. 

Abstract We present a comprehensive statistical analysis of high‐frequency transient‐large‐amplitude (TLA) magnetic perturbation events that occurred at 12 high‐latitude ground magnetometer stations throughout Solar Cycle 24 from 2009 to 2019. TLA signatures are defined as one or more second‐timescale dB/dtinterval with magnitude ≥6 nT/s within an hour event window. This study characterizes high‐frequency TLA events based on their spatial and temporal behavior, relation to ring current activity, auroral substorms, and nighttime geomagnetic disturbance (GMD) events. We show that TLA events occur primarily at night, solely in the high‐latitude region above 60° geomagnetic latitude, and commonly within 30 min of substorm onsets. The largest TLA events occurred more often in the declining phase of the solar cycle when ring current activity was lower and solar wind velocity was higher, suggesting association to high‐speed streams caused by coronal holes and subsequent corotating interaction regions reaching Earth. TLA perturbations often occurred preceding or within the most extreme nighttime GMD events that have 5–10 min timescales, but the TLA intervals were often even more localized than the ∼300 km effective scale size of GMDs. We provide evidence that shows TLA‐related GMD events are associated with dipolarization fronts in the magnetotail and fast flows toward Earth and are closely temporally associated with poleward boundary intensifications (PBIs) and auroral streamers. The highly localized behavior and connection to the most extreme GMD events suggests that TLA intervals are a ground manifestation of features within rapid and complex ionospheric structures that can drive geomagnetically induced currents. 

Abstract We present an automated method to identify high‐frequency geomagnetic disturbances in ground magnetometer data and classify the events by the source of the perturbations. We developed an algorithm to search for and identify changes in the surface magnetic field, dB/dt, with user‐specified amplitude and timescale. We used this algorithm to identify transient‐large‐amplitude (TLA) dB/dtevents that have timescale less than 60 s and amplitude >6 nT/s. Because these magnetic variations have similar amplitude and time characteristics to instrumental or man‐made noise, the algorithm identified a large number of noise‐type signatures as well as geophysical signatures. We manually classified these events by their sources (noise‐type or geophysical) and statistically characterized each type of event; the insights gained were used to more specifically define a TLA geophysical event and greatly reduce the number of noise‐type dB/dtidentified. Next, we implemented a support vector machine classification algorithm to classify the remaining events in order to further reduce the number of noise‐type dB/dtin the final data set. We examine the performance of our complete dB/dtsearch algorithm in widely used magnetometer databases and the effect of a common data processing technique on the results. The automated algorithm is a new technique to identify geomagnetic disturbances and instrumental or man‐made noise, enabling systematic identification and analysis of space weather related dB/dtevents and automated detection of magnetometer noise intervals in magnetic field databases. 

Abstract We present a characterization of transient‐large‐amplitude (TLA) geomagnetic disturbances that are relevant to geomagnetically induced currents (GIC). TLA events are defined as one or more short‐timescale (<60 s) dB/dt signature with magnitude ≥6 nT/s. The TLA events occurred at six stations of the Magnetometer Array for Cusp and Cleft Studies throughout 2015. A semi‐automated dB/dt search algorithm was developed to identify 38 TLA events in the ground magnetometer data. While TLA dB/dts do not drive GICs directly, we show that second‐timescale dB/dts often occur in relation to or within larger impulsive geomagnetic disturbances. Sudden commencements are not the main driver, rather the events are more likely to occur 30 min after a substorm onset or within a nighttime magnetic perturbation event. The characteristics of TLA events suggest localized ionospheric source currents that may play a key role in generating some extreme geomagnetic impulses that can lead to GICs.