We have developed a new procedure for combining lists of substorm onset times from multiple sources. We apply this procedure to observational data and to magnetohydrodynamic (MHD) model output from 1-31 January, 2005. We show that this procedure is capable of rejecting false positive identifications and filling data gaps that appear in individual lists. The resulting combined onset lists produce a waiting time distribution that is comparable to previously published results, and superposed epoch analyses of the solar wind driving conditions and magnetospheric response during the resulting onset times are also comparable to previous results. Comparison of the substorm onset list from the MHD model to that obtained from observational data reveals that the MHD model reproduces many of the characteristic features of the observed substorms, in terms of solar wind driving, magnetospheric response, and waiting time distribution. Heidke skill scores show that the MHD model has statistically significant skill in predicting substorm onset times.

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.

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.

Magnetohydrodynamic (MHD) models have been used for nearly four decades to study the dynamics of magnetospheric substorms. However, until recently no demonstration has been made that MHD models can consistently reproduce substorm onset times in a statistical sense. To test whether MHD can reproduce observed substorm onset times, we developed a procedure for identifying substorm onsets that can be applied both to observational data and to MHD output. Our substorm identification procedure aims to improve upon existing methods of substorm identification by using multiple types of observations to corroborate each identified substorm. Using this procedure, we identified over 100 substorms from the period 1-31 January 2005. Using this list of substorm onset times, we show that the MHD model has weak, but statistically significant skill in predicting substorm onset times. We explore paths to improving the ability of the MHD model to predict substorm dynamics by testing different configurations of the MHD model.

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.

Estimation of the ionospheric conductance is a crucial step in coupling the magnetosphere & ionosphere (MI). Since the high-latitude ionosphere closes magnetospheric currents, conductance in this region is pivotal to examine & predict MI coupling dynamics, especially during extreme events. In spite of its importance, only recently have impacts of key magnetospheric & ionospheric contributors affecting auroral conductance (e.g., particle distribution, ring current, anomalous heating, etc.) been explored using global models. Addressing these uncertainties require new capabilities in global magnetosphere - ionosphere - thermosphere models, in order to self-consistently obtain the multi-scale, dynamic sources of conductance. This work presents the new MAGNetosphere - Ionosphere - Thermosphere (MAGNIT) auroral conductance model, which delivers the requisite capabilities to fully explore the sources of conductance & their impacts. MAGNIT has been integrated into the Space Weather Modeling Framework to couple dynamically with the BATSRUS magnetohydrodynamic (MHD) model, the Rice Convection Model (RCM) of the ring current, the Ridley Ionosphere Model (RIM) & the Global Ionosphere Thermosphere Model (GITM). This new model is used to address the precise impact of diverse conductance contributors during geomagnetic events. First, the coupled MHD-RIM-MAGNIT model is used to establish diffuse & discrete precipitation using kinetic theory. The key innovation is to include the capability of using distinct particle distribution functions (PDF) in a global model: in this study, we explore precipitation fluxes estimated using isotropic Maxwellian & Kappa PDFs. RCM is then included to investigate the effect of the ring current. Precipitating flux computed on closed field lines by RCM is compared against MAGNIT results, to show that expected results are alike. Lastly, GITM is coupled to study the impact of the ionosphere thermosphere system. Using the MAGNIT model, aforementioned conductance sources are progressively applied in idealized simulations & compared against the OVATION Prime Model. Finally, data-model comparisons against SSUSI, AMPERE & SuperMAG measurements during the March 17, 2013 Storm are shown. Results show remarkable progress of conductance modeling & MI coupling layouts in global models.

The accurate determination of auroral precipitation in global models has remained a daunting and rather inexplicable obstacle. Understanding the calculation and balance of multiple sources that constitute the aurora, and their eventual conversion into ionospheric electrical conductance, is critical for improved prediction of space weather events. In this study, we present a semi-physical global modeling approach that characterizes contributions by four types of precipitation - monoenergetic, broadband, electron and ion diffuse - to ionospheric electrodynamics. The model uses a combination of adiabatic kinetic theory and loss parameters derived from historical energy flux patterns to estimate auroral precipitation from magnetohydrodynamic (MHD) quantities. It then converts them into ionospheric conductance that is used to compute the ionospheric feedback to the magnetosphere. The model has been employed to simulate the April 5 - 7, 2010 “Galaxy15” space weather event. Comparison of auroral fluxes show good agreement with observational datasets like NOAA-DMSP and OVATION Prime. The study shows a dominant contribution by electron diffuse precipitation, accounting for ~74% of the auroral energy flux. However, contributions by monoenergetic and broadband sources dominate during times of active upstream conditions, providing for up to 61% of the total hemispheric power. The study also indicates a dominant role played by broadband precipitation in ionospheric electrodynamics which accounts for ~31% of the Pedersen conductance.

One of the prominent effects of space weather is the variation of electric currents in the magnetosphere and ionosphere, which can cause localized, high amplitude Geomagnetic Disturbances (GMDs) that disrupt ground conducting systems. Because the source of localized GMDs is unresolved, we are prompted to model these effects, identify the physical drivers through examination of the model we use, and improve our prediction of these phenomena. We run a high-resolution configuration of the Space Weather Modeling Framework (SWMF) to model the September 7, 2017 event, combining three physical models: Block Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US), an ideal magnetohydrodynamic model of the magnetosphere; the Ridley Ionosphere Model (RIM), a shell ionosphere calculated by solving 2-D Ohm’s Law; and the Rice Convection Model (RCM), a kinetic drift model of the inner magnetosphere. The configuration mirrors that which is used in Space Weather Prediction Center (SWPC) operations; however, the higher grid resolution can reproduce mesoscale structure in the tail and ionosphere. We use two metrics to quantify the success of the model against observation. Regional Station Difference (RSD) is a metric that uses dB/dt or geoelectric field to pinpoint when a single magnetometer station records a significantly different value than others within a given radius, indicating a localized GMD. Regional Tail Difference (RTD) performs the same calculation using relevant variables in the magnetosphere at points that map down along field lines to the magnetometer station locations on the ground. We theorize two distinct causes of RSD, the first being small-scale structure in the tail and the second being station field lines mapping to spatially separated locations in the tail. We examine the differences between RSD spikes that we can reproduce in the model and those that we cannot. We categorize spikes by cause of localized GMDs to examine model capability for each theorized cause. We investigate the improvements in our model when we switch from empirical specification of ionosphere conductance to a physics-based one, MAGNetosphere-Ionosphere-Thermosphere (MAGNIT) Auroral Conductance Model. For small-scale effects we cannot reproduce, we explore the deficiencies in our model.