Magnetometers are essential instruments in space physics, but their measurements are often contaminated by various external interference sources. In this work, we present a comprehensive review of existing magnetometer interference removal methods and introduce MAGPRIME (MAGnetic signal PRocessing, Interference Mitigation, and Enhancement), an open‐source Python library featuring a collection of state‐of‐the‐art interference removal algorithms. MAGPRIME streamlines the process of interference removal in magnetic field data by providing researchers with an integrated, easy‐to‐use platform. We detail the design, structure, and functionality of the library, as well as its potential to facilitate future research by enabling rapid testing and customization of interference removal methods. Using the MAGPRIME Library, we present two Monte Carlo benchmark results to compare the efficacy of interference removal algorithms in different magnetometer configurations. In Benchmark A, the Underdetermined Blind Source Separation (UBSS) and traditional gradiometry algorithms surpass the uncleaned boom‐mounted magnetometers, achieving improved correlation and reducing median error in each simulation. Benchmark B tests the efficacy of the suite of MAGPRIME algorithms in a boomless magnetometer configuration. In this configuration, the UBSS algorithm proves to significantly reduce median error, along with improvements in median correlation and signal to noise ratio. This study highlights MAGPRIME's potential in enhancing magnetic field measurement accuracy in various spacecraft designs, from traditional gradiometry setups to compact, cost‐effective alternatives like bus‐mounted CubeSat magnetometers, thus establishing it as a valuable tool for researchers and engineers in space exploration and magnetism studies.
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Abstract Free, publicly-accessible full text available June 1, 2025 -
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.
Free, publicly-accessible full text available January 1, 2025 -
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, d
B /dt , with user‐specified amplitude and timescale. We used this algorithm to identify transient‐large‐amplitude (TLA) dB /dt events 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 /dt identified. 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 /dt in the final data set. We examine the performance of our complete dB /dt search 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 /dt events and automated detection of magnetometer noise intervals in magnetic field databases. -
Abstract We analyzed the magnetospheric global response to dynamic pressure pulses (DPPs) using the Heliophysics System Observatory (HSO) and ground magnetometers. During northward Interplanetary Magnetic Field (IMF) Bz conditions, the magnetosphere acts as a closed “cavity” and reacts to solar wind DPPs more simply than during southward IMF. In this study we use solar wind data collected by ACE and WIND together with magnetic field observations of Geotail, Cluster, Time History of Events and Macroscale Interactions during Substorms (THEMIS), Magnetospheric Multiscale Mission (MMS), Van Allen Probes, GOES missions, and ground magnetometer arrays to observe the magnetosphere (dayside, nightside, inner magnetosphere, magnetotail, magnetosheath, etc.) and ionosphere response simultaneously in several local time sectors and regions. A total of 37 events were selected during the period between February 2007 to December 2017. We examine the global response of each event and identify systematic behavior of the magnetosphere due to DPPs' compression, such as MHD wave propagation, sudden impulses, and Ultra Low Frequency waves (ULF) in the Pc5 range. Our results confirm statistical studies with a more limited coverage that have been performed at different sectors and/or regions of the magnetosphere. We present observations of the different signatures generated in different regions that propagate through the magnetosphere. The signature of the tailward traveling DPP is observed to move at the same solar wind speed, and in superposition of other known magnetospheric perturbations. It is observed that the DPP also generates or increases the amplitude of Pc4‐5 waves observed in the inner magnetosphere, while similar waves are observed on the ground.
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In this paper, for the first time, simultaneous atmospheric temperature perturbation profiles obtained from the TIMED/SABER satellite and equatorial ion density and vertical plasma drift velocity observations with and without ESF activity obtained from the C/NOFS satellite are used to investigate the effect of gravity waves (GW) on ESF. The horizontal and vertical wavelengths of ionospheric oscillations and GWs are estimated by applying wavelet analysis techniques. In addition, vertically propagating GWs that dissipate energy in the ionosphere-thermosphere system are investigated using the spectral analysis technique. We find that the vertical wavelength of GW, corresponding to dominant wavelet power, ranges from 12 to 31 km regardless of the conditions of the ionosphere; however, GWs with vertical wavelengths between about 1 to 13 km are found every day, saturated between 90 and 110 km at different longitudinal sectors. Filtering out vertical wavelengths above 13 km from temperature perturbations, ranges of zonal wavelengths of GW (i.e., from about 290 to 950 km) are found corresponding to irregular and non-irregular ionosphere. Similarly, corresponding to dominant oscillations, the zonal wavelength of ion density perturbations is found within 16 to 1520 km. Moreover, we find an excellent agreement among the median zonal wavelengths of GW for the cases of irregular and non-irregular ionosphere and ion density perturbations that are 518, 495, and 491 km, respectively. The results imply that seed perturbations due to GW with a vertical wavelength from about 1 to 13 km evolve to ion density irregularity and may be amplified due to post-sunset vertical upward drift velocity.more » « less