William. R. Paterson

During fast mode intervals the Magnetospheric Multi‐Scale (MMS) Fast Plasma Investigation (FPI) operates continuously in ion burst capacity at 150 msec cadence. From the burst data and at the same cadence, FPI computes four ion moments (ion density, ion flux) termed trigger data. Only a few percent of the full burst data are downloaded, but trigger data are downloaded over the entire fast mode interval. The trigger data were not envisioned as a science product, so the sign bits of the 3 ion flux components were dropped, and only absolute values were telemetered to the ground. Using 4.5 s FAST mode data and minimization techniques, we reconstruct the ion flux sign bits and computed ion velocity, validating the methodology through comparisons with burst mode velocity for 103 burst mode intervals. We demonstrate that calibrated FPI “trigger” data are scientifically valid in the magnetosheath and its boundary layer, and particularly useful for wave studies whose frequency is greater than 0.1 and less than 3 Hz. As an example of the use of the trigger data, we present an analysis of ion cyclotron waves (ICW) observed by the MMS constellation on 7 October 2015, in the afternoon magnetosheath.

During Galileo's closest (“E12”) flyby of Europa, a brief burst of wave activity was recorded by the plasma wave instrumentation, PWS. This was speculatively interpreted by Jia et al. (2018, https://doi.org/10.1038/s41550‐018‐0450‐z ) as a 2,100 cm ⁻³ spike in plasma densities from a water plume encounter. While the plasma instrument, PLS, could have provided an independent density measurement and resolved ambiguity in the PWS analysis, calibrated PLS data were never published from E12. Here we present high‐resolution (∼18 s) PLS moments and velocity distributions from E12. Plasma densities near closest approach were between (assuming ) and (assuming ), in agreement with the original interpretation of PWS densities by Kurth et al. (2001, https://doi.org/10.1016/s0032‐0633(00)00156‐2 ). We thus discount a plume encounter. PLS measurements near Europa imply a highly asymmetrical and inhomogeneous ionosphere (as expected). Europa's Alfvén Wings were more compact than expected, implying stronger electrical currents than predicted by existing models.

Both ground based magnetometers and ionospheric radars at Earth have frequently detected Ultra Low Frequency (ULF) fluctuations at discrete frequencies extending below one mHz‐range. Many dayside solar wind drivers have been convincingly demonstrated as driver mechanisms. In this paper we investigate and propose an additional, nightside generation mechanism of a low frequency magnetic field fluctuation. We propose that the Moon may excite a magnetic field perturbation of the order of 1 nT at discrete frequencies when it travels through the Earth's magnetotail 4–5 days every month. Our theoretical prediction is supported by a case study of ARTEMIS magnetic field measurements at the lunar orbit in the Earth's magnetotail. ARTEMIS detects statistically significant peaks in magnetic field fluctuation power at frequencies of 0.37–0.47 mHz that are not present in the solar wind.

In situ spacecraft observations are critical to our study and understanding of the various phenomena that couple mass, momentum, and energy throughout near‐Earth space and beyond. However, on‐orbit telemetry constraints can severely limit the capability of spacecraft to transmit high‐cadence data, and missions are often only able to telemeter a small percentage of their captured data at full rate. This presents a programmatic need to prioritize intervals with the highest probability of enabling the mission's science goals. Larger missions such as the Magnetospheric Multiscale mission (MMS) aim to solve this problem with a Scientist‐In‐The‐Loop (SITL), where a domain expert flags intervals of time with potentially interesting data for high‐cadence data downlink and subsequent study. Although suitable for some missions, the SITL solution is not always feasible, especially for low‐cost missions such as CubeSats and NanoSats. This manuscript presents a generalizable method for the detection of anomalous data points in spacecraft observations, enabling rapid data prioritization without substantial computational overhead or the need for additional infrastructure on the ground. Specifically, Principal Components Analysis and One‐Class Support Vector Machines are used to generate an alternative representation of the data and provide an indication, for each point, of the data's potential for scientific utility. The technique's performance and generalizability is demonstrated through application to intervals of observations, including magnetic field data and plasma moments, from the CASSIOPE e‐POP/Swarm‐Echo and MMS missions.

Interplanetary (IP) shocks are perturbations observed in the solar wind. IP shocks correlate well with solar activity, being more numerous during times of high sunspot numbers. Earth‐bound IP shocks cause many space weather effects that are promptly observed in geospace and on the ground. Such effects can pose considerable threats to human assets in space and on the ground, including satellites in the upper atmosphere and power infrastructure. Thus, it is of great interest to the space weather community to (a) keep an accurate catalog of shocks observed near Earth, and (b) be able to forecast shock occurrence as a function of the solar cycle (SC). In this work, we use a supervised machine learning regression model to predict the number of shocks expected in SC25 using three previously published sunspot predictions for the same cycle. We predict shock counts to be around 275 ± 10, which is ∼47% higher than the shock occurrence in SC24 (187 ± 8), but still smaller than the shock occurrence in SC23 (343 ± 12). With the perspective of having more IP shocks on the horizon for SC25, we briefly discuss many opportunities in space weather research for the remainder years of SC25. The next decade or so will bring unprecedented opportunities for research and forecasting effects in the solar wind, magnetosphere, ionosphere, and on the ground. As a result, we predict SC25 will offer excellent opportunities for shock occurrences and data availability for conducting space weather research and forecasting.

In-situ spacecraft observations are critical to our study and understanding of the various phenomena that couple mass, momentum, and energy throughout near-Earth space and beyond. However, on-orbit telemetry constraints can severely limit the capability of spacecraft to transmit high-cadence data, and missions are often only able to telemeter a small percentage of their captured data at full rate. This presents a programmatic need to prioritize intervals with the highest probability of enabling the mission’s science goals. Larger missions such as the Magnetospheric Multiscale mission (MMS) aim to solve this problem with a Scientist-In-The-Loop (SITL), where a domain expert flags intervals of time with potentially interesting data for high-cadence data downlink and subsequent study. Although suitable for some missions, the SITL solution is not always feasible, especially for low-cost missions such as CubeSats and NanoSats. This manuscript presents a generalizable method for the detection of anomalous data points in spacecraft observations, enabling rapid data prioritization without substantial computational overhead or the need for additional infrastructure on the ground. Specifically, Principal Components Analysis and One-Class Support Vector Machines are used to generate an alternative representation of the data and provide an indication, for each point, of the data’s potential for scientific utility. The technique’s performance and generalizability is demonstrated through application to intervals of observations, including magnetic field data and plasma moments, from the CASSIOPE e-POP/Swarm-Echo and MMS missions.

In 1995, the Galileo spacecraft traversed the wake of Io at ∼900 km altitude. The instruments onboard detected intense bi‐directional field‐aligned electron beams (∼140 eV–150 keV), embedded in a dense, cold and slow plasma wake (N_el ∼ 35,000 cm⁻³, T_i < 10 eV, V < 3 km/s). Similar electron beams were also detected along subsequent Galileo flybys. Using numerical simulations, we show that these electron beams are responsible for the formation of Io's dense plasma wake. We prescribe the composition of Io's atmosphere in S, O, SO and SO₂, compute the atmospheric ionization by the beams with a parameterization adapted from study of auroral electrons at Earth, the plasma flow into Io's atmosphere with a Magneto‐Hydro‐Dynamic code, and the ion composition and temperature with a multi‐species physical chemistry code. Results reveal contrasting chemistries between the upstream and wake regions, leading to different ion compositions. The upstream chemistry is driven by the torus thermal electrons at 5 eV with SO₂⁺ becoming the dominant ion because of electron‐impact ionization of the SO₂ atmosphere. The wake chemistry is driven by the high‐energy electrons in the beams with S⁺ and SO⁺ becoming the dominant ions produced by dissociative‐ionization of SO₂. We show that the wake ion composition is highly sensitive to the atmospheric composition. Juno, in its extended mission, will traverse Io's wake and determine its ion composition, which, compared with our numerical simulations will enable us to infer the detailed composition of the atmosphere.

Recent observations and simulations have revealed a wide variety of plasma processes and multiscale structures at the dayside magnetopause. In this presentation, we focus on the origins and evolution of the plasma populations observed in the magnetopause boundary layers. We present the results of Particle-In-Cell (PIC) simulations encompassing large volumes of the dayside magnetosphere. The implicit PIC code used in the study was initialized from a global MHD state of the magnetosphere for southward interplanetary field conditions. Three-dimensional plots of the perpendicular slippage indicates that reconnection occurs over most of the dayside magnetopause. However, the simulation reveals that the reconnection region has a much more filamentary structure than the X-line expected from the extrapolation of 2D models and that multiscale structures thread the reconnection outflow. In particular, the simulation indicates the formation of multiple layers of electrons with significant field-aligned velocities within the main magnetopause current layer. We use velocity distribution functions at different locations in the reconnection outflow to characterize the origins and evolution of the electron and ion populations of the magnetosheath and magnetospheric boundary layers.

In this study, the ion composition of flux transfer events (FTEs) observed within the magnetosheath proper is examined. These FTEs were observed just upstream of the Earth's postnoon magnetopause by the National Aeronautics and Space Administration (NASA) Magnetospheric Multiscale (MMS) spacecraft constellation. The minor ion characteristics are described using energy spectrograms, flux distributions, and ion moments as the constellation encountered each FTE. In conjunction with electron data and magnetic field observations, such observations provide important contextual information on the formation, topologies, and evolution of FTEs. In particular, minor ions, when combined with the field‐aligned streaming of electrons, are reliable indicators of FTE topology. The observations are also placed (i) in context of the solar wind magnetic field configuration, (ii) the connection of the sampled flux tube to the ionosphere, and (iii) the location relative to the modeled reconnection line at the magnetopause. While protons and alpha particles were often depleted within the FTEs relative to the surrounding magnetosheath plasma, the He⁺ and O⁺ populations showed clear enhancements either near the center or near the edges of the FTE, and the bulk plasma flow directions are consistent with magnetic reconnection northward of the spacecraft and convection from the dayside toward the flank magnetopause.