Crucial future observations and directions for unveiling magnetopause dynamics and their geospace impacts

Archer, Martin O.; Shi, Xueling; Walach, Maria-Theresia; Hartinger, Michael D.; Gillies, D. Megan; Di Matteo, Simone; Staples, Frances; Nykyri, Katariina

doi:10.3389/fspas.2024.1430099

PERSPECTIVE article

Front. Astron. Space Sci., 05 August 2024

Sec. Space Physics

Volume 11 - 2024 | https://doi.org/10.3389/fspas.2024.1430099

This article is part of the Research Topic Past, Present and Future Of Multispacecraft Measurements For Space Physics View all 9 articles

Crucial future observations and directions for unveiling magnetopause dynamics and their geospace impacts

Martin O. Archer¹*

Xueling Shi^2,3

Maria-Theresia Walach⁴

Michael D. Hartinger^5,6

D. Megan Gillies^7,8

Simone Di Matteo^9,10

Frances Staples¹¹

Katariina Nykyri¹⁰

¹Department of Physics, Imperial College London, London, United Kingdom
²Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, United States
³High Altitude Observatory, National Center for Atmospheric Research, Boulder, CO, United States
⁴Physics Department, Lancaster University, Lancaster, United Kingdom
⁵Space Science Institute, Boulder, CO, United States
⁶Department of Earth, Planetary, and Space Sciences, University of California Los Angeles, Los Angeles, CA, United States
⁷Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada
⁸Department of Chemistry and Physics, Mount Royal University, Calgary, AB, Canada
⁹Physics Department, The Catholic University of America, Washington, DC, United States
¹⁰NASA-Goddard Space Flight Center, Greenbelt, MD, United States
¹¹Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, United States

The dynamics of Earth’s magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts. In-situ multi-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the “mesoscale” coupling across the geospace “system of systems.” Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a “zone of confusion.” Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations.

1 Introduction

Earth’s magnetopause, depicted in Figure 1A, is the interface of the solar–terrestrial interaction, hence mediates the flow of mass, momentum, and energy between the solar wind and geospace. As this interaction is responsible for the myriad of phenomena that can severely impact vital infrastructure, collectively known as space weather, understanding physical processes at the magnetopause and their system-wide effects is of utmost importance. The magnetopause is observed to be in almost continual motion. Alongside magnetic reconnection (Dungey, 1961), the wave-like motion of the magnetopause constitutes one of the major energy transfer mechanisms in the solar–terrestrial interaction (Axford, 1964). These magnetopause motions affect auroral, ionospheric, outer radiation belt, and trapped magnetospheric plasmas — either directly or indirectly through associated ultra-low frequency (ULF) waves (e.g., Sibeck, 1990; Elkington, 2006).

Figure 1

Figure 1. Current and future observational capabilities for studying magnetopause dynamics from space. (A) Visualisation of the magnetosphere from a Gorgon global MHD simulation (e.g., Mejnertsen et al., 2017). Displayed are volumetric current densities throughout the simulation, along with magnetic field lines in the meridional plane. (B) Example of an orbital conjunction from current in-situ missions ideal for investigating magnetopause dynamics. (C) Diagram of HelioSwarm skimming Kelvin-Helmholtz vortices from a local MHD simulation with $100 k m$ velocity shear layer and no magnetic shear (Ma et al., 2017). (D) Simulated SMILE soft X-ray images (top panels) and time evolution along the Sun-Earth line (bottom panels) using data from Samsonov et al. (2024). The counts have been processed using multidimensional kernel density estimation, applying Epanechnikov kernels of optimal bandwidth from Silverman’s rule (Silverman, 1986). A proxy for the magnetopause (black) is identified as the median of the marginal distributions. (E) Orbits of the Starlink, OneWeb, and Iridium NEXT constellations in low Earth orbit along with field-aligned currents associated with magnetopause surface waves from an SWMF global MHD simulation of the magnetospheric response to a solar wind density pulse (Archer et al., 2023).

The boundary location in steady state is dictated by a balance of pressures (thermal, magnetic, and dynamic) on both sides of the magnetopause. Imbalances which lead to magnetopause motion are typically thought of as being externally driven, e.g., by variations in the upstream flow pressure (Potemra et al., 1989; Sibeck et al., 1989; Francia et al., 1999; Viall et al., 2009), the velocity shear as the solar wind flows around the magnetosphere (Kelvin-Helmholtz Instability, KHI; Chandrasekhar, 1961; Faganello and Califano, 2017; Masson and Nykyri, 2018), or reconnection with the interplanetary magnetic field altering the dayside magnetic flux (Hill and Rassbach, 1975; Matlsev and Lyatsky, 1975). However, internal processes such as the drift-mirror instability may also generate pressure changes that drive boundary dynamics (Constantinescu et al., 2009; Nykyri et al., 2021). Several of these driving processes may occur simultaneously and even modify one another, making observations hard to disentangle (e.g., Ma et al., 2014; Di Matteo et al., 2022).

The wave-like motion of the magnetopause is well approximated by magnetohydrodynamic surface wave theory (see recent review of Archer et al., 2024). The interplay of inertial, damping, and restoring forces on the dayside magnetopause predicts a $\sim 5 – 10 m i n$ response to direct driving (Smit, 1968; Freeman et al., 1995; Børve et al., 2011; Horaites et al., 2023) alongside resonant $\sim 10 – 20 m i n$ standing surface waves from ionospheric reflection (Chen and Hasegawa, 1974; Plaschke and Glassmeier, 2011; Archer and Plaschke, 2015). In contrast, on the magnetopause flanks where KH-waves dominate, periodicities are shorter $\sim 1 – 7 m i n$ (Lin et al., 2014; Kavosi and Raeder, 2015). Corresponding wavelengths along the boundary span a wide spatial range, $\sim 1 – 15 R_{E}$ (Lin et al., 2014).

Since magnetopause dynamics couple across many regions of geospace, there are numerous means of directly and indirectly observing the processes occurring and their consequences. In this paper we outline current and future observational capabilities at Earth, grouped by different target regions of geospace. We highlight new/improved directions to the field for unveiling magnetopause dynamics across different modes of observation and how these may aid our understanding of the boundary’s global importance to the geospace energy budget.

2 Solar wind – magnetosphere interface

2.1 Multi-point in-situ measurements

In-situ spacecraft provide measurements of the physical conditions present at their location, such as particle distributions/moments and (DC/AC) electric/magnetic fields. Single spacecraft cannot unambiguously separate variations in space and time. Four spacecraft are the minimum required to uniquely resolve 3D structure (Paschmann and Daly, 1998), methods for which have been applied to the Cluster, MMS, and THEMIS missions. These typically assume first-order derivatives and planar structures over spacecraft separation scales. For studying magnetopause dynamics, the times the boundary passed over each spacecraft allow estimation of its local thickness and motion (Paschmann et al., 2005; Plaschke et al., 2009). Furthermore, simultaneous observations around the moving boundary allow comparison of spatial patterns against theory (e.g., Hasegawa et al., 2004; Plaschke et al., 2013; Archer et al., 2019; 2021).

Multi-spacecraft missions to date have typically focused on one scale at a time (e.g., fluid/ion for Cluster, ion/electron for MMS), achieved through precisely-controlled formations. In contrast, upcoming missions such as HelioSwarm (Klein et al., 2023) and the Plasma Observatory concept (Retinò et al., 2022) instead propose semi-autonomous swarms of 7+ spacecraft broadly separated across a variety of plasma scales. Swarms will allow unprecedented spatiotemporal reconstruction of magnetopause dynamics, e.g., KH roll-up vortices as in Figure 1C, while also probing important cross-scale physics.

While multi-spacecraft missions provide great detail of local structures and physical processes, geospace constitutes a “system of systems” with many different plasma populations that feedback on one another leading to more complex emergent/collective dynamical behaviour (Kepko, 2018; Kepko et al., 2023). This highlights the need for simultaneous observations across multiple spatial scales to understand how collective interactions produce “mesoscale” phenomena ( $\sim 1 – 3 R_{E}$ in the magnetosphere) that mediate the global solar–terrestrial interaction.

Conjunctions between existing missions have revealed some of these feedbacks and mesoscale structuring relevant to magnetopause dynamics. For example, foreshock and magnetosheath transients emerge from interactions of large-scale solar wind structures with the quasi-parallel bow shock and reflected suprathermal foreshock ion populations, leading to many localised disturbances of the boundary and impacts throughout geospace (e.g., Archer et al., 2012; 2013; Nykyri et al., 2019; Wang et al., 2020a; Escoubet et al., 2020). Currently an extraordinary number of spacecraft orbit Earth, meaning many opportunities for multi-mission conjunctions exist. Indeed, Figure 1B highlights how March 2024 regularly offered simultaneous observations upstream of the bow shock, near the magnetopause at different local times, and at different $L$ -shells within the magnetosphere.

Unfortunately, sparse conjunctions do not provide sufficient measurements to resolve all key processes across the “system of systems”. Furthermore, care must be taken when comparing/combining measurements across different missions/instruments. Mission concepts for $\sim 40$ distributed identical spacecraft separated over “mesoscales” have been suggested to address this (Kepko, 2018; Kepko et al., 2023). These would have clear applications in building a global picture of magnetopause dynamics, revolutionising our understanding of the boundary’s role in controlling mass, momentum, and energy transfer.

2.2 Soft X-rays

Large-scale imaging of the dynamic solar–terrestrial interaction from space is an emerging direction that clearly complements in-situ spacecraft and ground-based measurements. Several upcoming missions aim to image the dayside magnetosphere in soft X-rays from solar wind charge exchange, including the joint ESA-CAS SMILE mission (Branduardi-Raymont and Wang, 2022; Wang and Branduardi-Raymont, 2022), and smallsats Geo-X (Ezoe et al., 2020) and LEXI (Walsh et al., 2024). A heavy solar wind ion in the magnetosheath/cusps gains an electron in a high-energy state from a neutral exospheric atom, subsequently relaxing by emitting an X-ray photon (Cravens et al., 2001; Robertson and Cravens, 2003). Soft X-ray emissivities are predicted to peak at the tangent to the magnetopause (Sibeck et al., 2018), potentially enabling boundary dynamics to be tracked in both space and time.

Methods to determine the location of the magnetopause from X-ray images are not trivial, typically assuming some global shape (Samsonov et al., 2022; Wang and Sun, 2022). Furthermore, under typical to moderate solar wind driving, rather low photon counts are expected. Spatiotemporal binning can help increase signal-to-noise, though bins of scales comparable to typical dayside magnetopause motion $(1 ° \times 1 ° \times 5 m i n)$ still result in very noisy images (e.g., Samsonov et al., 2022; 2024). While this may be mitigated by longer integration times and/or larger pixels, it would render boundary dynamics indeterminable.

More advanced techniques are likely required to improve scientific return. For example, data-driven density estimation techniques little used in our field may help (e.g., Archer et al., 2015; 2017). Instead of sharp fixed pixels, density estimation sums over smooth functions centred on each observation. This has convergence and continuity benefits over binning, and methods for data-driven scaling of bandwidths already exist (Silverman, 1986). Figure 1D shows our application to simulated data from Samsonov et al. (2024), demonstrating clear improvements.

3 Magnetosphere–ionosphere interface

Information about disturbances to the magnetopause are communicated to the auroral ionosphere along magnetic field lines by field-aligned currents (FACs), carried by precipitating magnetospheric electrons (ions) and/or upwelling ionospheric ions (electrons) for upward (downward) currents (Elphic, 1988; Sibeck, 1990). Recent high-resolution global MHD simulations, shown in Figure 1E (Archer et al., 2023), suggest magnetopause surface waves’ FACs have large latitudinal extents $(\sim 10 °)$ via non-resonant coupling between the compressional and Alfvén modes, peaking at the inner edge of the magnetopause transition (typically a few degrees equatorward of the Open–Closed Boundary, OCB; Kozyreva et al., 2019). These FACs open the possibility of remote sensing magnetopause motion at the magnetosphere–ionosphere interface. Current LEO spacecraft (e.g., Swarm, Friis-Christensen et al., 2008; POES; Evans and Greer, 2000; DMSP; Kilcommons et al., 2017; Redmon et al., 2017; and CASSIOPE; Yau and James, 2015) enable observations of magnetic field, electric field, precipitating particle, and/or drift velocity perturbations; all of which may be associated with magnetopause dynamics (e.g., Horvath and Lovell, 2021). However, due to orbital mechanics, single satellites in LEO provide a predominantly spatial cut and cannot capture the $\sim 1 – 20 m i n$ periodicities at a fixed point in space associated with magnetopause motion. GDC’s 6-spacecraft will enable temporal evolution of important magnetosphere–ionosphere–thermosphere coupling processes to be captured (Akbari et al., 2024). In early mission phases when orbital planes at high-latitudes are closest in longitude — best for studying magnetopause-related dynamics — resolvable timescales will be limited by the spacing/time between satellites to $\sim 2 – 4 m i n$ . Mega-constellations with many satellites in the same orbital plane are required to capture the full range of magnetopause periodicities at the magnetosphere–ionosphere interface.

In recent years, commercial mega-constellations with 10’s–1000s of satellites have been launched into LEO. Figure 1E shows orbits of the three largest to date: Iridium, OneWeb, and Starlink. The AMPERE project has successfully demonstrated engineering magnetometers aboard the polar-orbiting Iridium constellation (orange) can provide FAC observations across the polar cap through spherical fits to measured perturbations (Anderson et al., 2000; Waters et al., 2019). This has provided great insight into the variability of Region-1 and -2 FACs (Milan et al., 2017), though the $30 °$ spacecraft separation within each of the 6 orbital planes means only periodicities $> 16 m i n$ are resolvable. Larger mega-constellations might be leveraged in a similar way, enabling FACs from magnetopause dynamics to be captured. OneWeb (purple) also has polar orbits, but twice as many orbital planes as Iridium and only $\sim 7 °$ separation within these. Thus OneWeb might provide $\sim 2 m i n$ resolution polar maps with double the azimuthal fidelity. Starlink (green) occupy mostly $\sim 50 °$ inclined orbits, but a minority of orbits do cross the polar cap. The sheer number of Starlink satellites means it could still yield improved coverage/resolution to Iridium. Of course these possibilities would involve significant technical challenges and further developed processing methods, but could significantly advance our global monitoring of the dynamic solar–terrestrial interaction from space.

4 Ionosphere

4.1 Auroral imaging

Magnetopause disturbances can, through the precipitating magnetospheric particles carrying their FACs, lead to production/modulation of auroral emission in the ionosphere (e.g., Craven et al., 1986; Sibeck et al., 1999; Kozyreva et al., 2019). Aurorae are monitored from both ground and space, providing yet further means of remote sensing magnetopause dynamics.

This is a historic era for ground-based auroral science, with unprecedented all-sky imager (ASI) coverage operating coast-to-coast across the high latitude North American landscape, as shown in Figure 2A (orange/yellow circles). The THEMIS-ASI network of 21 imagers (Donovan et al., 2006; 2008; Mende et al., 2008) has provided comprehensive panchromatic “white light” imaging since 2008, capturing qualitative images of auroral morphology from local to continent-wide scales (quantitative data can be derived by combining with meridian scanning photometers; Gabrielse et al., 2021). Since particle species cannot be differentiated in panchromatic data, aurorae are assumed caused by precipitating electrons. At 9 THEMIS-ASI sites are the REGO red-line imagers, which observe a key oxygen auroral emission (Liang et al., 2016). TREx, another continent-wide network across 6 locations (Gillies et al., 2019), instead features co-located monochromatic ASIs at major auroral emissions (blue-line, near-infrared, and RGB “true colour”). This enables electron flux and mean precipitation energy to be derived, yielding vital information on particle sources and their connection to the magnetosphere (Liang et al., 2022; 2024; Gillies et al., 2023). The THEMIS-ASIs are being replaced with RGB imagers to complement the SMILE mission, with the 19 new SMILE-ASIs completing by summer 2025 (Carter et al., 2024). Of course, ground-based auroral imagery is only possible during clear night skies, which for dayside magnetopause signatures limits studies to winter seasons.

Figure 2

Figure 2. Current observational capabilities for remote sensing magnetopause dynamics and their impacts from the ground. (A) Orthographic map showing ground-based instruments in the high-latitude northern hemisphere in geographic coordinates ( $20 °$ latitudinal spacing). These include SuperDARN radars (red/blue fans), SuperMAG ground magnetometers (green triangles), All Sky Imagers (orange/yellow circles), Incoherent Scatter Radar (cyan stars), spectrograph fields (purple lines), and Chain GNSS receivers (magenta dots). The Open–Closed Boundary (OCB) from the Tsyganenko (1995) model under median conditions is shown as the thick black line. Panels (B–D) Potential dayside ground-based signatures of magnetopause surface waves from the same global MHD simulation as in Figure 1E. Displayed are magnetic latitude–time plots (keograms) of perturbations in upwards field-aligned currents (B), North–South ionospheric velocity (C), and East–West ground magnetic field (D) near the noon sector. The OCB (dashed grey lines) and projected extent of the magnetopause (double-headed arrows) from the simulation are also displayed (note global simulation numerics lead to more smeared out boundary layers than in reality).

In addition to ground-based imagers, space-based ones such as on IMAGE (Mende et al., 2000b; a,c), Polar (Torr et al., 1995), DMSP (Paxton et al., 2002), the upcoming SMILE (Branduardi-Raymont and Wang, 2022) and proposed MAAX (Halford et al., 2024) have the benefit of observing large areas and at wavelengths (e.g., UV-band) not observable from the ground. Furthermore, UV auroral observations are possible at all times, independent of light pollution. However, space-based auroral images are less detailed, due to trade-offs between spatial coverage and integration times, as well as orbital configuration. While DMSP auroral images build up over $\sim 25 m i n$ polar crossings, meaning spatiotemporal ambiguity affects potential magnetopause signatures, both Polar and IMAGE were spinning allowing $\sim 1 – 2 m i n$ cadence images, suitable for resolving auroral impacts of long-period magnetopause waves (e.g., Liou et al., 2008). SMILE’s UVI will cover the entire auroral oval for the first time since 2005, allowing global auroral dynamics to be captured at $1 m i n$ and $\sim 50 – 150 k m$ resolution, augmented by more detailed imagery from the ground.

Figure 2B shows simulated FACs associated with magnetopause surface waves which may lead to auroral signatures (Archer et al., 2023). While auroral bright spots have been linked to the magnetopause (Lundin and Evans, 1985; Kozyreva et al., 2019) and recently plasmapause (He et al., 2020; Horvath and Lovell, 2021), it is not clear if surface waves’ FACs are sufficient to generate emission or simply modulate existing aurorae. Insight might be gained through comparison with field line resonances, whose similar periodic FACs do produce aurorae (Samson et al., 1996; Milan et al., 2001; Gillies et al., 2018).

4.2 Radar

Closure of magnetopause disturbances’ FACs through ionospheric Pedersen currents are associated with electric field oscillations and $E \times B$ plasma drifts, resulting in so-called Travelling Convection Vortices (TCVs, Friis-Christensen et al., 1988; Bristow et al., 1995) which may be detected by radar observations (e.g., Walsh et al., 2015; Shi et al., 2020).

SuperDARN (e.g., Ruohoniemi et al., 1989; Ruohoniemi and Greenwald, 1996; Chisham et al., 2007; Nishitani et al., 2019, etc.) consists of ground-based high-frequency coherent scatter radars which measure line-of-sight Doppler shifts of ionospheric irregularities. The network has expanded over the past 2 decades/solar cycles across high- (blue/red fans in Figure 2A) and mid-latitudes, enabling coverage for typical but also disturbed geomagnetic conditions (Nishitani et al., 2019; Walach and Grocott, 2019; Walach et al., 2021). Historically, ULF waves have been studied at individual radars, where comparing measurements across multiple beams (see Figure 2C for simulated single-beam observations) can track 2-D wave propagation providing insights into drivers (Fenrich et al., 1995; James et al., 2013). Because a full scan of the SuperDARN field-of-view took $\sim 1 – 2 m i n$ though, signatures due to faster magnetopause dynamics (e.g., KH-waves) could not be fully captured over large-scales. However, exciting upgrades to digital radar systems (e.g., McWilliams et al., 2023) are enabling imaging at $3.5 s$ resolution. As these improvements roll out, the overlapping fields-of-view might allow unprecedented large-scale observations of TCVs due magnetopause dynamics through high-order spherical fits to velocity measurements (Ruohoniemi et al., 1989).

In addition to coherent scatter radars, Incoherent Scatter Radar (ISR, cyan stars in Figure 2A), e.g., EISCAT (Rietveld et al., 2019; Stamm et al., 2021), PFISR (Nicolla and Heinselman, 2007), and RISR, (Gillies et al., 2016), is another valuable tool for remote sensing magnetopause dynamics from the ionosphere. Buchert et al. (1999) and Wang et al. (2020b) used ISR measurements showing ULF waves with periods from $1 – 10 m i n$ significantly modulate the ionospheric electron density at a range of altitudes, ultimately affecting ionospheric conductance. While ISR’s spatial coverage is limited for resolving the spatial scales and propagation of magnetopause dynamics, its ability to offer insights into altitude profiles of multiple ionospheric parameters becomes invaluable. These are aspects poorly explored both in magnetopause dynamical theory/simulations and observations at present.

4.3 Global navigation satellite systems (GNSS)

Ionospheric total electron content (TEC), the columnar number density, is most widely obtained using remote-sensing techniques between GNSS satellites and ground-receivers (magenta dots in Figure 2A). Observed TEC fluctuations with periods $10 – 1000 s$ have been linked to ULF waves in the polar cap (e.g., Watson et al., 2016), auroral zone (e.g., Pilipenko et al., 2014), and mid-/low-latitude regions (e.g., Yizengaw et al., 2018). These have amplitudes as large as $7 T E C U$ (Watson et al., 2015). Pilipenko et al. (2014) explored several possible mechanisms of higher latitude ULF wave driven TEC fluctuations, two of which may be related to magnetopause surface waves and have been invoked in other studies. These are wave-modulated precipitation of energetic electrons affecting ionospheric conductivities (Buchert et al., 1999; Wang et al., 2020b), and periodic vertical plasma flows due to waves’ FACs (Belakhovsky et al., 2016; Kozyreva et al., 2020). TEC observations are complicated by satellite orbits and line-of-sight, with standard conversions from “slant” to “vertical” TEC (e.g., Kozyreva et al., 2020) assuming homogeneity over $\sim 10 °$ — invalid for even large-scale surface waves (Archer et al., 2023). Further modelling to better understand the physical processes behind TEC fluctuations and any observational biases are needed for GNSS to become a valuable remote-sensing tool for magnetopause dynamics.

5 Ground magnetic field

The magnetic field at Earth’s surface includes contributions from magnetosphere–ionosphere currents. Global networks of ground-based magnetometers of varying spatial separations ( $> 200 k m$ , green triangles in Figure 2A) have been some of the earliest and most widely used tools for understanding how magnetopause disturbances lead to FACs/waves (Friis-Christensen et al., 1988; Sibeck, 1990; Araki, 1994; Motoba et al., 2007), ultimately impacting the global magnetosphere–ionosphere–thermosphere system (e.g., Shi et al., 2022). While unable to detect phenomena < 100 km (Hughes and Southwood, 1976), they have a few important advantages over other instruments. They can operate continuously without concern for sunlight, cloud cover, and ionospheric backscatter. Closely spaced magnetometers can also resolve important mesoscales from the ground (Engebretson and Zesta, 2017). Furthermore, ground magnetometers do not move in the geocentric frame, thus the interpretation of their data is less complicated than satellites (e.g., Anderson et al., 1989).

Studies of high-latitude ULF waves have been described as a “zone of confusion” with structuring whose relation out to the magnetosphere is ambiguous (Pilipenko et al., 2015; 2018; see also Figure 2D). Unambiguously linking wave power enhancements with magnetopause surface waves (e.g., Glassmeier, 1992), or other wave activity (e.g., Araki and Nagano, 1988; Lyatsky and Sibeck, 1997), may require closely spaced networks of magnetometers to identify the polarization changes and wave power variations predicted by simulations (Archer et al., 2023). 2D networks in both hemispheres spanning the cusp and auroral zones would further help discriminate wave modes; e.g., enabling natural experiments for isolating surface wave signatures from telluric currents (Weygand et al., 2023), variations in ionospheric conductance (e.g., Hartinger et al., 2017), and asymmetries in upstream driving conditions (e.g., Oliveira et al., 2020; Shi et al., 2020; Di Matteo and Sivadas, 2022; Villante et al., 2022).

Finally, magnetotelluric survey networks (e.g., USArray’s EarthScope sites; Schultz, 2010) consist of small arrays taking simultaneous geoelectric and geomagnetic field measurements temporarily (typically $\sim 3$ weeks, but variable), subsequently moving locations. They have a few unique capabilities relevant for surface wave diagnostics (Hartinger et al., 2020; Shi et al., 2022). They are typically deployed in more spatially dense networks than typical magnetometer networks $(< 70 k m)$ thus capture finer-scale features. They provide information about ground conductivity, which can be used to discriminate magnetosphere–ionosphere currents from telluric currents. They also yield additional geoelectric field measurements, enabling the waves’ hazard to power systems to be considered. However, their spatial coverage at any given time is much more limited and site locations may not always be optimal for studying the magnetopause’s effects on the ground.

6 Discussion

This is an exciting time for studying magnetopause dynamics, with many new/emerging observational capabilities in both in-situ and remote sensing measurements. Each of these enables us to probe the physical processes occurring at the boundary and their impacts upon geospace. While each observational method has its own unique benefits and drawbacks, bringing them together simultaneously will start to provide a holistic view of the magnetopause’s controlling role in mediating the solar–terrestrial interaction — from local physics, through to emergent mesoscale features, and ultimately the collective global response/impact. It is crucial this unprecedented observational coverage be maintained through sustained funding for extended mission/instrumentation operations.

Along with this unprecedented diversity and coverage of measurements, data processing methods will become more important than ever. Inversion techniques applied to multi-point measurements offer unique opportunities to resolve the temporal evolution and spatial structure of different wave modes, which may otherwise be convolved in original datasets complicating their physical interpretation (Archer et al., 2023). For example, distributed 2D networks of ground-based magnetometers have long been used to obtain magnetospheric field-aligned, ionospheric Pedersen and Hall, and now even telluric currents via the Spherical Elementary Current System technique (e.g., Shi et al., 2022; Weygand et al., 2023). Similar methods are now also being applied to SuperDARN observations (e.g., Fenrich et al., 2019). These approaches may further be boosted through machine learning capabilities (Camporeale, 2019; Nguyen et al., 2022; Grimmich et al., 2023), allowing more sophisticated data analysis across “big data” for the identification of signals related to magnetopause surface waves and dynamics (e.g., Cicone et al., 2016; Murphy et al., 2020; Di Matteo et al., 2021), especially in nonlinear and nonstationary contexts (Piersanti et al., 2018; Stallone et al., 2020). Finally, data mining and assimilation (Tsyganenko and Sitnov, 2007; Merkin et al., 2016; Alzate et al., 2023) into maturing “system of systems” models (e.g., Zhang et al., 2019; Sorathia et al., 2020; 2023; Gombosi et al., 2021) can aid the interpretation of this unprecedented, but still scattered, data collection enabling the global context to be inferred.

The techniques and physical insights gained from studying Earth’s magnetopause might also translate to different space plasma environments where fewer observational methods are possible, such as the other planetary magnetopauses (e.g., Masters et al., 2009; Boardsen et al., 2010; Montgomery et al., 2023) or solar coronal structures like loops (Nakariakov et al., 2016). Here similar dynamical processes are thought to occur but over vastly different scales, morphologies, and/or plasma conditions.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

MA: Conceptualization, Funding acquisition, Visualization, Writing–original draft, Writing–review and editing. XS: Conceptualization, Visualization, Writing–original draft, Writing–review and editing. M-TW: Conceptualization, Writing–original draft, Writing–review and editing. MH: Conceptualization, Writing–original draft, Writing–review and editing. DG: Conceptualization, Writing–original draft, Writing–review and editing. SD: Conceptualization, Writing–original draft, Writing–review and editing. FS: Conceptualization, Writing–review and editing. KN: Funding acquisition, Writing–review and editing.

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by the International Space Science Institute (ISSI) in Bern, through ISSI International Team project #546 “Magnetohydrodynamic Surface Waves at Earth’s Magnetosphere (and Beyond).” MA was supported by UKRI (STFC/EPSRC) Stephen Hawking Fellowship EP/T01735X/1 and UKRI Future Leaders Fellowship MR/X034704/1. XS was supported by National Aeronautics and Space Administration (NASA) awards 80NSSC21K1677 and 80NSSC21K1683, National Science Foundation (NSF) awards AGS-1935110, AGS-2025570, and AGS-2307205. M-TW was supported by UKRI (STFC) Ernest Rutherford Fellowship ST/X003663/1. MH was supported by NASA awards 80NSSC21K1683 and 80NSSC23K0903, and NSF awards AGS-2307204 and AGS-2027210. SD was supported by NASA award 80NSSC21K0459. FS was supported by NASA award 80NSSC21K0448.

Acknowledgments

We acknowledge the 3DView online tool (Génot et al., 2018) used to create Figure 1B. We acknowledge the pyDARN package (Shi et al., 2022) used to create Figure 2A. For the purpose of open access, the author(s) has applied a Creative Commons attribution (CC BY) licence to any Author Accepted Manuscript version arising.

Conflict of interest

The authors declare the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

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