Editorial: Past, present and future of multispacecraft measurements for space physics
Bibliographic record
Abstract
The curlometer and spatial gradient based methods are comprehensively reviewed by Dunlop et al. (2024).These techniques are adaptable to a range of multi-point and multi-scale arrays, originally developed for ESA's Cluster mission, but later adapted for Swarm and MMS. The authors note that "multi-spacecraft estimates of current density and spatial gradients have provided key information on large and small magnetospheric current systems and related transient structures, resolving 3-D currents for a range of conditions in widely different geospace regions. The curlometer technique, in particular, has proved to be reliable and robust. The applicability of the method is limited by certain constraints, particularly those for relatively small structures compared to the spacecraft separation distances." The authors discuss the further adaptations of these techniques for future constellation missions such as Helioswarm and Plasma Observatory.A thorough review of solar energetic particle measurements both from historical and current missions, together with the outlook for future missions are given by Reames (2023). The author recommends that physics of SEPs may require a return to the closer spacing of the Helios era with coverage 27 mapped by a half-dozen spacecraft to help disentangle the distribution of the SEPs from the underlying 28 structure of the magnetic field and the accelerating shock".The Kelvin-Helmholtz Instability (KHI), arising from a velocity shear across a plasma boundary, plays a 30 crucial role in plasma, momentum, and energy transfer, e.g., from the shocked solar wind into the planetary 31 magnetospheres and at the boundaries of Coronal Mass Ejections (see e.g., Nykyri et al. (2021); Nykyri 32 (2024) and references therein). a robust vortex detection method by spacecraft has been missing.Here, Kelly et al. (2024) develop and validate a novel vortex identification method for ideal MHD, based 2024) present a gradient calculation method for the upcoming, six-spacecraft Geospace 59 Dynamics Constellation (GDC) mission, which will investigate dynamical processes in Earth's upper 60 atmosphere. Achieving this goal will involve resolving and distinguishing spatial and temporal variability 61 of ionospheric and thermospheric structures in a quantitative manner. Specifically, this paper implements 62 the least-squares gradient calculation approach previously developed by J. De Keyser. The authors conclude 63 that: "1) computation of the temporal gradients of neutral and plasma variables, while sensitive to the 64 measurement noise level, are possible with GDC measurements; 2) The spatial gradients of the equatorial 65 ionization anomaly can be reasonably resolved during phase 1 of the mission, while at the later phases 66 the gradients are likely to be underestimated. On the other hand, in the presence of measurement noise, al.computing the gradients of the neutral temperature would likely be more difficult in the earliest phases of 68 the mission due to the small gradients and large homogeneity lengths involved; 3) Gradients of the neutral 69 wind can be well determined in the earliest phases of the mission even at the highest latitudes where the 70 constellation skews in longitude." 71 Oberheide et al. (2023) discuss how the GDC mission can be used to resolve tidal weather. The GDC 72 mission measures neutral temperatures and winds and thus likely enable significant progress towards 73 resolving the tidal weather of the thermosphere and how it is driven by meteorological processes near the 74 surface and in situ forcing in the ionosphere-thermosphere system. The authors demonstrate that GDC can 75 resolve the day-to-day tidal variability (mean, diurnal and semidiurnal, migrating and nonmigrating) at 76 orbit height during the mission. They note that the "mean state of thermosphere can also be recovered on a 77 day-to-day basis throughout mission phases 3 and 4, including the mean meridional circulation".In an opinion article, Weimer (2024) argue that the significance of the small-scale electric fields in 79 the polar ionosphere may be overestimated. This somewhat contradicts earlier studies that highlight the 80 importance of correctly capturing the variability of the electric fields in the models to accurately account 81 for the total amount of Joule heating. The authors conclude that future multi-spacecraft measurements 82 in the polar ionosphere, such as the future GDC mission, will be able to address this issue, "with some 83 limitations due to missing double-probes". The extent, to which these can be accomplished in the next decade depends on the funding level of the 96 associated agencies: NASA, NSF and NOAA as well as their international counterparts, and on the state of 97 a healthy and educated workforce.KN wrote the initial draft of the editorial, all authors helped in commenting and editing of the editorial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.023 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".