The Geospace Environment Modeling (GEM) program regularly issues ”community challenges” in which researchers examine a particular space physics phenomenon or geomagnetic activity event, often running numerical models to assess dominant processes and understand the timing and relationship of observed signatures. The GEM Methods and Validation (M&V) Resource Group helps those GEM leaders running challenges to maximize participation and optimize scientific return from the significant time investment of these endeavors. This article gives a brief history of GEM community challenges and details those best practices that lead to an inclusive and valuable experience.

The inductive component of the magnetospheric electric field, which is associated with the temporal change of magnetic field, provides an additional means of local plasma energization and transport in addition to the electrostatic counterpart. This study examines the detailed response of the inner magnetosphere to inductive electric fields and the associated electric-driven convection corresponding to different solar wind conditions. A novel modeling capability is employed to self-consistently simulate the electromagnetic and plasma environment of the entire magnetospheric cavity. The explicit separation of the electric field by source (inductive vs. electrostatic) and subsequent implementation of inductive effects in the ring current model allow us to investigate, for the first time, the effect of the inductive electric field on the kinetics and evolution of the ring current system. The simulation results presented in this study demonstrate that the inductive component of the electric field is capable of providing an additional source for long-lasting plasma drifts, which in turn significantly alter the trajectories of both thermal and energetic particles. Such changes in the plasma drift, which arise due to the inductive electric fields, further reshape the storm-time ring current morphology and alter the degree of the ring current asymmetry, as well as the timing and the peak of the ion pressure. The total ion energy is increasing at a faster rate than the supply of energetic ions to the ring current, suggesting that the inductive electric field provides effective and accumulative local energization for the trapped ring current population without confining additional particles.

Ionospheric outflow supplies nearly all of the heavy ions observed within the magnetosphere, as well as a significant fraction of the proton density. While much is known about upflow and outflow energization processes, the full global pattern of outflow and its evolution is only known statistically or through numerical modeling. Because of the dominant role of heavy ions in several key physical processes, this unknown nature of the full outflow pattern leads to significant uncertainty in understanding geospace dynamics, especially surrounding storm intervals. That is, global models risk not accurately reproducing the main features of intense space storms because the amount of ionospheric outflow is poorly specified and thus magnetospheric composition and mass loading could be ill-defined. This study defines a potential mission to observe ionospheric outflow from several platforms, allowing for a reasonable and sufficient reconstruction of the full outflow pattern on an orbital cadence. An observing system simulation experiment is conducted, revealing that four well-placed satellites are sufficient for reasonably accurate outflow reconstructions. The science scope of this mission could include the following: reveal the global structure of ionospheric outflow; relate outflow patterns to geomagnetic activity level; and determine the spatial and temporal nature of outflow composition. The science objectives could be focused to be achieved with minimal instrumentation (only a low-energy ion spectrometer to obtain outflow reconstructions) or with a larger scientific scope by including contextual instrumentation. Note that the upcoming Geospace Dynamics Constellation mission will observe upwelling but not ionospheric outflow.

During its ongoing mission, the Cluster II constellation has provided the first small-scale multipoint measurements of the space environment, and dramatically advanced scientific understanding in numerous regimes. One such region is the Earth’s inner magnetospheric ring current, which could now be computed using the curl of the magnetic field over a spacecraft tetrahedron instead of via plasma moments. While this produced the first 3D current estimates, it also produced different results from prior ring current studies with differing magnitudes and correlations with storm indices/local times. In this analysis, we revisit Cluster ring current data via curlometry, and conduct additional quantitative sensitivity simulations using actual spacecraft position data. During the orbits that observed ring current structure, tetrahedron shape and linearity assumptions can create large errors up to 100% of physical current magnitude in curlometer output that contradict accepted estimated quality parameters. These false currents are directly related to the structure of the current environment, and cannot be distinguished from the actual currents without additional limiting assumptions. The trustworthiness of curlometer output in the ring current is therefore dependent on the linearity of the magnetic structure relative to the tetrahedron orientation, which requires additional characterization. The Cluster curlometer output in the ring current is then explored in light of these new uncertainties, with the computed current magnitude and direction both potentially impacted by the production of false currents.

A new model validation and performance assessment tool is introduced, the sliding threshold of observation for numeric evaluation (STONE) curve. It is based on the relative operating characteristic (ROC) curve technique, but instead of sorting all observations in a categorical classification, the STONE tool uses the continuous nature of the observations. Rather than defining events in the observations and then sliding the threshold only in the classifier/model data set, the threshold is changed simultaneously for both the observational and model values, with the same threshold value for both data and model. This is only possible if the observations are continuous and the model output is in the same units and scale as the observations; the model is trying to exactly reproduce the data. The STONE curve has several similarities with the ROC curve – plotting probability of detection against probability of false detection, ranging from the (1,1) corner for low thresholds to the (0,0) corner for high thresholds, and values above the zero-intercept unity-slope line indicating better than random predictive ability. The main difference is that the STONE curve can be nonmonotonic, doubling back in both the x and y directions. These ripples reveal asymmetries in the data-model value pairs. This new technique is applied to modeling output of a common geomagnetic activity index as well as energetic electron fluxes in the Earth’s inner magnetosphere. It is not limited to space physics applications but can be used for any scientific or engineering field where numerical models are used to reproduce observations.

Journals occasionally solicit manuscripts for special collections, in which all papers are focused on a particular topic within the journal’s scope. For the Journal of Geophysical Research: Space Physics, there have been 51 special collections from 2005 through 2018, with a total of 1009 papers out of the 8881 total papers in the journal over those years (11%). Taken together, the citations to special collection papers, as well as other metrics, are essentially the same as the non-special-collection papers. Several paper characteristics were examined to assess whether they could explain the higher citation and download values for SC papers, but they cannot. In addition, indirect methods were conducted for assessing self-citations as an explanation for the increased citations, but no evidence was found to support this hypothesis. It was found that some paper types, notably Commentaries and Technical Reports, have lower average citations but higher average downloads than Research Articles (the most common type of paper in this journal). This implies that such paper types have a different kind of impact than “regular” science-result-focused papers. In addition to having higher average citations and downloads, special collections focus community attention on that particular research topic, providing a deadline for manuscript submissions and a single webpage at which many related papers are listed. It is concluded that special collections are worth the extra community effort in organization, writing, and reviewing these papers.

Ionospheric conductance is a crucial factor in regulating the closure of magnetospheric field-aligned currents through the ionosphere as Hall and Pedersen currents. Despite its importance in predictive investigations of the magnetosphere - ionosphere coupling, the estimation of ionospheric conductance in the auroral region is precarious in most global first-principles based models. This impreciseness in estimating the auroral conductance impedes both our understanding and predictive capabilities of the magnetosphere-ionosphere system during extreme space weather events. In this article, we address this concern, with the development of an advanced Conductance Model for Extreme Events (CMEE) that estimates the auroral conductance from field aligned current values. CMEE has been developed using nonlinear regression over a year’s worth of one-minute resolution output from assimilative maps, specifically including times of extreme driving of the solar wind-magnetosphere-ionosphere system. The model also includes provisions to enhance the conductance in the aurora using additional adjustments to refine the auroral oval. CMEE has been incorporated within the Ridley Ionosphere Model (RIM) of the Space Weather Modeling Framework (SWMF) for usage in space weather simulations. This paper compares performance of CMEE against the existing conductance model in RIM, through a validation process for six space weather events. The performance analysis indicates overall improvement in the ionospheric feedback to ground-based space weather forecasts. Specifically, the model is able to improve the prediction of ionospheric currents which impact the simulated dB/dt and ΔB, resulting in substantial improvements in dB/dt predictive skill.

Both in situ measurements and numerical simulations show that the charge exchange collisions between energetic ring current ions (>10keV) and cold ambient neutral atoms of the upper atmosphere and exosphere (<1eV) can be a major loss process of the ring current ions. Owing to the high volume of energetic ion source injected from the ion plasma sheet during storm time under strong convection strength, there can be a significant rate of occurrence of charge exchange collision in the inner magnetosphere, therefore contributing a significant amount of inner magnetospheric cold proton populations. Due to the different charge exchange cross sections among different reactions, cold protons are generated at different rates from different energetic ion species. In this study, both qualitative and quantitative assessments on the production and evolution of charge-exchange byproduct cold protons are performed via numerical simulations, showing that the production and evolution of the cold H+ populations can be primarily driven by the plasma sheet conditions combined with the magnetospheric convection, while having the potential to affect the dynamics of the plasmasphere and facilitate the early-stage local plasmaspheric refilling. Furthermore, the energetic heavy ions composition plays an important role determining the cold H+ contribution structure from the energetic ring current ions.

41 thousand years ago, the Laschamps geomagnetic excursion caused Earth’s geomagnetic field to drastically diminish to ~4% of modern values and modified the geomagnetic dipole axis. While the impact of this geomagnetic event on environmental factors and human lifestyle has been contemplated to be linked with modifications in the geospace environment, no concerted investigation has been conducted to study this until recently. We present an initial investigation of the global space environment and related plasma environments during the several phases of the Lachamps event using an advanced multi-model approach. We use recent paleomagnetic field models of this event to study the paleomagnetosphere with help of the global magnetohydrodynamic model BATS-R-US. Here we go beyond a simple dipole approximation but consider a realistic geomagnetic field configuration. The field is used within BATS-R-US to generate the magnetosphere during discrete epochs spanning the peak of the event. Since solar conditions have remained fairly constant over the last ~100k years, modern estimates of the solar wind were used to drive the model. Finally, plasma pressure and currents generated by BATS-R-US at their inner boundary are used to compute auroral fluxes using a stand-alone version of the MAGNIT model, an adiabatic kinetic model of the aurora. Our results show that changes in the geomagnetic field, both in strength and the dipole tilt angle, have profound effects on the space environment and the ensuing auroral pattern. Magnetopause distances during the deepest phase of the excursion match previous predictions by studies like Cooper et al. (2021), while high-resolution mapping of magnetic fields allow close examination of magnetospheric structure for non-dipolar configurations. Temporal progression of the event also exhibits rapid locomotion of the auroral region over ~250 years along with the movement of the geomagnetic poles. Our estimates suggest that the aurora extended further down, with the center of the oval located at near-equatorial latitudes during the peak of the event. While the study does not find evidence of any link between geomagnetic variability and habitability conditions, geographic locations of the auroral oval coincide with early human activity in the Iberian peninsula and South China Sea.

Despite significant developments in global modeling, the determination of ionospheric conductance in the auroral region remains a challenge in the space science community. With advances in adiabatic kinetic theory and numerical couplings between global magnetohydrodynamic models and ring current models, the dynamic prediction of individual sources of auroral conductance have improved significantly. However, the individual impact of these sources on the total conductance and ionospheric electrodynamics remains understudied. In this study, we have investigated individual contributions from four types of auroral precipitation - electron & ion diffuse, monoenergetic & Alfven wave-driven - on ionospheric electrodynamics using a novel modeling setup. The setup encompasses recent developments within the University of Michigan’s Space Weather Modeling Framework (SWMF), specifically through the use of the MAGNetosphere - Ionosphere - Thermosphere auroral precipitation model and dynamic two-way coupling with the Global Ionosphere-Thermosphere Model. This modeling setup replaces the empirical idealizations traditionally used to estimate conductance in SWMF, with a physics-based approach capable of resolving 3-D high-resolution mesoscale features in the ionosphere-thermosphere system. Using this setup, we have simulated an idealized case of southward Bz 5nT & the April 5-7 “Galaxy15” Event. Contributions from each source of precipitation are compared against the OVATION Prime Model, while auroral patterns and hemispheric power during Galaxy15 are compared against observations from DMSP SSUSI and the AE-based FTA model. Additionally, comparison of field aligned currents (FACs) and potential patterns are also conducted against AMPERE, SuperDARN & AMIE estimations. Progressively applying conductance sources, we find that diffuse contributions from ions and electrons provide ~75% of the total energy flux and Hall conductance in the auroral region. Despite this, we find that Region 2 FACs increase by ~11% & cross-polar potential reduces by ~8.5% with the addition of monoenergetic and broadband sources, compared to <1% change in potential for diffuse additions to the conductance. Results also indicate a dominant impact of ring current on the strength and morphology of the precipitation pattern.

The performance of three global magnetohydrodynamic (MHD) models in estimating the Earth’s magnetopause location and ionospheric cross polar cap potential (CPCP) have been presented. Using the Community Coordinated Modeling Center’s Run-on-Request system and extensive database on results of various magnetospheric scenarios simulated for a variety of solar weather patterns, the aforementioned model predictions have been compared with magnetopause standoff distance estimations obtained from six empirical models, and with cross polar cap potential estimations obtained from the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) Model and the Super Dual Auroral Radar Network (SuperDARN) observations. We have considered a range of events spanning different space weather activity to analyze the performance of these models. Using a fit performance metric analysis for each event, the models’ reproducibility of magnetopause standoff distances and CPCP against empirically-predicted observations were quantified, and salient features that govern the performance characteristics of the modeled magnetospheric and ionospheric quantities were identified. Results indicate mixed outcomes for different models during different events, with almost all models underperforming during the extreme-most events. The quantification also indicates a tendency to underpredict magnetopause distances in the absence of an inner magnetospheric model, and an inclination toward over predicting CPCP values under general conditions.

Conductivity of the ionosphere allows the complex system of magnetospheric currents to flow through. Conductivity is governed by several factors including electron density and temperature, whose influence is highly dynamic during geomagnetic storm events. Thus, it is a crucial parameter that must be determined for space weather modeling to specify the coupling between the magnetosphere, ionosphere and thermosphere systems. Major sources of ionospheric conductivity are solar EUV and particle precipitation which includes Diffuse (Diff.), Monoenergetic (ME) and Broadband (BB) precipitations. Conductance Σ is the height integrated version of conductivity. Empirically, total ionospheric conductance (Hall and Pedersen) is known to be the root sum square of individual conductance terms [Wallis and Budzinski, 1981], considering that conductivity resulting from different processes are not linearly additive and corresponding ionization rates shall be added at each altitude and then integrated over the desired altitude range. With the inclusion of the less energetic broadband precipitation that was found to cause ionization in the bottom-side F region, the expression for the total ionospheric conductance was modified by the linear addition of the contribution of the broadband precipitation to the total Hall and Pedersen conductance[Zhang et al., 2015].In this study, using a 3-dimensional global physics based model GITM (Global Ionosphere Thermosphere Model), the validity of this combination of vector and linear addition of individual source terms to the total ionospheric conductance is examined and the more accurate expression for the summation of sources contributing to the total conductance is quantified. GITM is employed to calculate the Hall and Pedersen conductance using the average energy, potential and energy flux for each of the sources of conductance. Several scenarios are simulated where the different sources of precipitation are paired with solar EUV radiation, and the total conductance is obtained. Linear and vector summation of conductance resulting from combinations of sources and individual sources indicate that the contribution of broadband precipitation to the total conductance also follows vector addition. To quantify the result that the total conductance is the vector sum of individual sources, error histograms are plotted and a set of metrics including RMSE, mean error, standard deviation, correlation coefficient and fractional error are enumerated for both linear and vector summation of individual sources to produce the total conductance.