One of the prominent effects of space weather is the variation of electric currents in the magnetosphere and ionosphere, which give rise to rapid geomagnetic field variations on the surface of the Earth. These Geomagnetic Disturbances (GMDs) can be highly localized and large amplitude. Because the causes of localized GMDs are unresolved, we seek to identify the physical drivers of these localized dB/dt spikes measured by ground magnetometers. We use the Space Weather Modeling Framework (SWMF) models to simulate the magnetosphere and reproduce these small-scale spikes. We use the operational Geospace configuration, which couples a global magnetohydrodynamic model to a height-integrated ionospheric electrodynamics solver and a kinetic ring current model. We run a series of simulations with increasingly higher spatial resolution to resolve small scale dB/dt dynamics. We quantify the success of the model against observation using Regional Station Difference (RSD), a metric calculated using dB/dt or geoelectric field to pinpoint when a single magnetometer station records a significantly different value than others within a given radius. We discuss future work to improve the model’s accuracy and our understanding of these small-scale structures.

We present a methodology to define strong, moderate, and intense space weather events based on probability distributions. We have illustrated this methodology using a long-duration, uniform data set of 1.8-3.5 MeV electron fluxes from multiple LANL geosynchronous satellite instruments but a strength of this methodology is that it can be applied uniformly to heterogeneous data sets. It allows quantitative comparison of data sets with different energies, units, orbits, etc. The methodology identifies a range of times, “events”, using variable flux thresholds to determine average event occurrence in arbitrary 11-year intervals (“cycles”). We define strong, moderate, and intense events as those that occur 100, 10, and 1 time per cycle and identify the flux thresholds that produce those occurrence frequencies. The methodology does not depend on any ancillary data set (e.g. solar wind or geomagnetic conditions). We show event probabilities using GOES > 2 MeV fluxes and compare them against event probabilities using LANL 1.8-3.5 MeV fluxes. We present some examples of how the methodology picks out strong, moderate, and intense events and how those events are distributed in time: 1989 through 2018, which includes the declining phases of solar cycles 22, 23, and 24. We also provide an illustrative comparison of moderate and strong events identified in the geosynchronous data with Van Allen Probes observations across all L-shells. We also provide a catalog of start and stop times of strong, moderate, and intense events that can be used for future studies.

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.