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A major risk of geomagnetic disturbances (GMDs) is cascading failure of electrical grids. The modeling of GMD events and cascading outages in power systems is difficult, both independently and jointly, because of the many different mechanisms and physics involved. This paper introduces a relaxation based modeling of GMD-induced cascading failures:~the dc approximation-based DCSIMSEP solver was adapted to simulate cascading as a result of GMDs, the full set of ac power flow equations were relaxed to guarantee optimality, and the reactive power losses were modeled while keeping the problem convex. The developed algorithm was implemented in PowerModelsGMD.jl - an open-source software specifically designed to model and analyze geomagnetic hazards - and demonstrated to work on the RTS-GMLC-GIC-EAST synthetic test network., 7 pages. 5 figures. 3 tables

For many years, it was believed that resonant interactions between electromagnetic ion cyclotron (EMIC) waves and radiation belt electrons were restricted to electron energies > 1 − 2 MeV. In recent years, however, a growing body of experimental evidence has shown that EMIC waves can cause the scattering loss of electrons down to sub‐MeV energies. Using measurements of trapped electron flux from the GPS satellite constellation, we investigate the ability of EMIC waves to cause significant depletions of radiation belt electron populations between 4 ≤ L* ≤ 5. For the first time, we present statistical evidence demonstrating global decreases in sub‐MeV trapped electron flux in response to EMIC wave activity. Although we find that electron losses extend down to sub‐MeV energies, we also show strong statistical support for the ability of EMIC waves to preferentially cause substantial depletions of ultra‐relativistic electrons in the radiation belts.

We use long-term electron and proton in-situ measurements made by the CXD particle instruments, developed by Los Alamos National Laboratory and carried on board GPS satellites, to determine total ionizing dose (TID) values and daily/yearly dose rate (DR) values in medium Earth orbits (MEOs) caused by the natural space radiation environment. Here measurement-based TID and DR values on a simplified sample geometry--a small (with a radius of 0.1 mm) Silicon detector within an Aluminum shielding sphere with a thickness of 100 mil--are compared to those calculated from empirical radiation models. Results over the solar cycle 24 show that electron TID from measurements in GPS orbit is well above the values calculated from the median/mean fluences from AE8 and AE9 models, but close to model fluences at high percentiles. Also, it is confirmed that in MEOs proton contributions to TID are minor and mainly dominated by solar energetic protons. Several factors affecting those dose calculations are discussed and evaluated. Results from this study provide us another out-of-sample test on the reliability of existing empirical space radiation models, and also help estimate the margin factors on calculated dose values in MEOs that pass through the heart of the Earth's outer radiation belt., 10 pages, 11 figures, submitted to 2021 IEEE Aerospace Conference. It has been accepted for final revision. This is not the published version

Geomagnetic activity is often described using summary indices to summarize the likelihood of space weather impacts, as well as when parameterizing space weather models. The geomagnetic indexK(p)in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministicK(p)predictions using a variety of methods - including empirically-derived functions, physics-based models, and neural networks - but do not provide uncertainty estimates associated with the forecast. This paper provides a sample methodology to generate a 3-hour-aheadK(p)prediction with uncertainty bounds and from this provide a probabilistic geomagnetic storm forecast. Specifically, we have used a two-layered architecture to separately predict storm (K-p >= 5(-)) and non-storm cases. As solar wind-driven models are limited in their ability to predict the onset of transient-driven activity we also introduce a model variant using solar X-ray flux to assess whether simple models including proxies for solar activity can improve the predictions of geomagnetic storm activity with lead times longer than the L1-to-Earth propagation time. By comparing the performance of these models we show that including operationally-available information about solar irradiance enhances the ability of predictive models to capture the onset of geomagnetic storms and that this can be achieved while also enabling probabilistic forecasts. Space Science and Applications group; Center for Space and Earth Science (CSES) at Los Alamos National Laboratory; US Department of EnergyUnited States Department of Energy (DOE); Laboratory Directed Research and Development (LDRD) program [20190262ER] SC thanks to the Space Science and Applications group and the Center for Space and Earth Science (CSES) at Los Alamos National Laboratory for organizing and supporting the Los Alamos Space Weather Summer School. Portions of this work by SKM were performed under the auspices of the US Department of Energy and were partially supported by the Laboratory Directed Research and Development (LDRD) program, award number 20190262ER. The authors wish to acknowledge the use of the OMNI solar wind data, available at https://omniweb.gsfc.nasa.gov/ow.html. The Kp index and GOES X-ray datasets were accessed through the GFZ-Potsdam website https://www.gfz-potsdam.de/en/kpindex/ and NOAA FTP server https://satdat.ngdc.noaa.gov/sem/goes/data/, respectively. The majority of analysis and visualization was completed with the help of free, open-source software tools, notably: Keras (Chollet, 2015); matplotlib (Hunter, 2007); IPython (Perez & Granger, 2007); pandas (McKinney, 2010); Spacepy (Morley et al., 2011); PyForecast-Tools (Morley, 2018); and others (see, e.g., Millman & Aivazis, 2011). The code developed during this work is available at https://github.com/shibaji7/Codebase_Kp_Prediction. The editor thanks two anonymous reviewers for their assistance in evaluating this paper.

Predicting variations in the near-Earth space environment that can lead to spacecraft damage and failure is one example of “space weather” and a big space physics challenge. A project recently funded through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program aims at developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to understand the dynamics of the surface charging environment (SCE), the hot (keV) electrons representing the source and seed populations for the radiation belts, on both macro- and micro-scale. Important physics questions related to particle injection and acceleration associated with magnetospheric storms and substorms, as well as plasma waves, are investigated. These challenging problems are addressed using a team of world-class experts in the fields of space science and computational plasma physics, and state-of-the-art models and computational facilities. A full two-way coupling of physics-based models across multiple scales, including a global MHD (BATS-R-US) embedding a particle-in-cell (iPIC3D) and an inner magnetosphere (RAM-SCB) codes, is achieved. New data assimilation techniques employing in situ satellite data are developed; these provide an order of magnitude improvement in the accuracy in the simulation of the SCE. SHIELDS also includes a post-processing tool designed to calculate the surface charging for specific spacecraft geometry using the Curvilinear Particle-In-Cell (CPIC) code that can be used for reanalysis of satellite failures or for satellite design.

A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented. The optimization method minimizes a cost function-tau-that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performed in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in vertical bar B vertical bar was reduced from 4.54% to 3.84%. The difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization. Plain Language Summary We present a method for comparing and optimizing the accuracy of commonly used empirical models that reproduce the Earth's magnetic field for altitudes ranging from a thousand to hundreds of thousands of kilometers. This method uses magnetic field data from satellites orbiting the planet to create a "penalty function" and uses an optimization algorithm to minimize this function and find the model input parameters that produce the best results for a given date and time. Our results show that these models can be improved by the use of satellite data. The model known as TS04 produced the best results after the optimization procedure generating a smaller error in 57.3% of the points in our data set when compared to the standard (unoptimized) inputs. The optimized TS04 also outperformed the best unoptimized model by 56.2%. The differences among all the models analyzed are usually not very large; however, the unoptimized models can have very large errors, which are much reduced by the optimization.

Energetic radiation belt electron fluxes can undergo sudden dropouts in response to different solar wind drivers. Many physical processes contribute to the electron flux dropout, but their respective roles in the net electron depletion remain a fundamental puzzle. Some previous studies have qualitatively examined the importance of magnetopause shadowing in the sudden dropouts either from observations or from simulations. While it is difficult to directly measure the electron flux loss into the solar wind, radial diffusion codes with a fixed boundary location (commonly utilized in the literature) are not able to explicitly account for magnetopause shadowing. The exact percentage of its contribution has therefore not yet been resolved. To overcome these limitations and to determine the exact contribution in percentage, we carry out radial diffusion simulations with the magnetopause shadowing effect explicitly accounted for during a superposed solar wind stream interface passage, and quantify the relative contribution of the magnetopause shadowing coupled with outward radial diffusion by comparing with GPS-observed total flux dropout. Results indicate that during high-speed solar wind stream events, which are typically preceded by enhanced dynamic pressure and hence a compressed magnetosphere, magnetopause shadowing coupled with the outward radial diffusion can explain about 60–99% of the main-phase radiation belt electron depletion near the geosynchronous orbit. While the outer region (L* > 5) can nearly be explained by the above coupled mechanism, additional loss mechanisms are needed to fully explain the energetic electron loss for the inner region (L* ≤ 5). While this conclusion confirms earlier studies, our quantification study demonstrates its relative importance with respect to other mechanisms at different locations.

The images taken by the Heliospheric Imagers (HIs), part of the SECCHI imaging package onboard the pair of STEREO spacecraft, provide information on the radial and latitudinal evolution of the plasma compressed inside corotating interaction regions (CIRs). A plasma density wave imaged by the HI instrument onboard STEREO-B was found to propagate towards STEREO-A, enabling a comparison between simultaneous remote-sensing and in situ observations of its structure to be performed. In situ measurements made by STEREO-A show that the plasma density wave is associated with the passage of a CIR. The magnetic field compressed after the CIR stream interface (SI) is found to have a planar distribution. Minimum variance analysis of the magnetic field vectors shows that the SI is inclined at 54° to the orbital plane of the STEREO-A spacecraft. This inclination of the CIR SI is comparable to the inclination of the associated plasma density wave observed by HI. A small-scale magnetic cloud with a flux rope topology and radial extent of 0.08 AU is also embedded prior to the SI. The pitch-angle distribution of suprathermal electrons measured by the STEREO-A SWEA instrument shows that an open magnetic field topology in the cloud replaced the heliospheric current sheet locally. These observations confirm that HI observes CIRs in difference images when a small-scale transient is caught up in the compression region.

We compare the probability distributions of substorm magnetic bay magnitudes from observations and a minimal substorm model. The observed distribution was derived previously and independently using the IL index from the IMAGE magnetometer network. The model distribution is derived from a synthetic AL index time series created using real solar wind data and a minimal substorm model, which was previously shown to reproduce observed substorm waiting times. There are two free parameters in the model which scale the contributions to AL from the directly-driven DP2 electrojet and loading-unloading DP1 electrojet, respectively. In a limited region of the 2-D parameter space of the model, the probability distribution of modelled substorm bay magnitudes is not significantly different to the observed distribution. The ranges of the two parameters giving acceptable (95% confidence level) agreement are consistent with expectations using results from other studies. The approximately linear relationship between the two free parameters over these ranges implies that the substorm magnitude simply scales linearly with the solar wind power input at the time of substorm onset.

Using a numerical implementation of the cowlock92 model of flow excitation in the magnetosphere-ionosphere (MI) system, we show that both an expanding (on a ~12-min timescale) and a quasi-instantaneous response in ionospheric convection to the onset of magnetopause reconnection can be accommodated by the Cowley-Lockwood conceptual framework. This model has a key feature of time dependence, necessarily considering the history of the coupled MI system. We show that a residual flow, driven by prior magnetopause reconnection, can produce a quasi-instantaneous global ionospheric convection response; perturbations from an equilibrium state may also be present from tail reconnection, which will superpose constructively to give a similar effect. On the other hand, when the MI system is relatively free of pre-existing flow, we can most clearly see the expanding nature of the response. As the open-closed field line boundary will frequently be in motion from such prior reconnection (both at the dayside magnetopause and in the cross-tail current sheet), it is expected that there will usually be some level of combined response to dayside reconnection.

A numerical model embodying the concepts of the Cowley-Lockwood (Cowley and Lockwood, 1992, 1997) paradigm has been used to produce a simple Cowley-Lockwood type expanding flow pattern and to calculate the resulting change in ion temperature. Cross-correlation, fixed threshold analysis and threshold relative to peak are used to determine the phase speed of the change in convection pattern, in response to a change in applied reconnection. Each of these methods fails to fully recover the expansion of the onset of the convection response that is inherent in the simulations. The results of this study indicate that any expansion of the convection pattern will be best observed in time-series data using a threshold which is a fixed fraction of the peak response. We show that these methods used to determine the expansion velocity can be used to discriminate between the two main models for the convection response to a change in reconnection. Keywords. Magnetospheric physics (Magnetosphereionosphere interactions) – Ionosphere (Plasma convection; Modeling and forecasting)

This paper presents a numerical model for predicting the evolution of the pattern of ionospheric convection in response to general time-dependent magnetic reconnection at the dayside magnetopause and in the cross-tail current sheet of the geomagnetic tail. The model quantifies the concepts of ionospheric flow excitation by Cowley and Lockwood (1992), assuming a uniform spatial distribution of ionospheric conductivity. The model is demonstrated using an example in which travelling reconnection pulses commence near noon and then move across the dayside magnetopause towards both dawn and dusk. Two such pulses, 8min apart, are used and each causes the reconnection to be active for 1min at every MLT that they pass over. This example demonstrates how the convection response to a given change in the interplanetary magnetic field (via the reconnection rate) depends on the previous reconnection history. The causes of this effect are explained. The inherent assumptions and the potential applications of the model are discussed. Key words. Ionosphere (ionosphere-magnetosphere interactions; plasma convection) – Magnetospheric physics (magnetosphere-ionosphere interactions; solar wind-magnetosphere interactions)

The interpretation of structure in cusp ion dispersions is important for helping to understand the temporal and spatial structure of magnetopause reconnection. "Stepped" and "sawtooth" signatures have been shown to be caused by temporal variations in the reconnection rate under the same physical conditions for different satellite trajectories. The present paper shows that even for a single satellite path, a change in the amplitude of any reconnection pulses can alter the observed signature and even turn sawtooth into stepped forms and vice versa. On 20 August 1998, the Defense Meteorological Satellite Program (DMSP) craft F-14 crossed the cusp just to the south of Longyearbyen, returning on the following orbit. The two passes by the DMSP F-14 satellites have very similar trajectories and the open-closed field line boundary (OCB) crossings, as estimated from the SSJ/4 precipitating particle data and Polar UVI images, imply a similarly-shaped polar cap, yet the cusp ion dispersion signatures differ substantially. The cusp crossing at 08:54 UT displays a stepped ion dispersion previously considered to be typical of a meridional pass, whereas the crossing at 10:38 UT is a sawtooth form ion dispersion, previously considered typical of a satellite travelling longitudinally with respect to the OCB. It is shown that this change in dispersed ion signature is likely to be due to a change in the amplitude of the pulses in the reconnection rate, causing the stepped signature. Modelling of the low-energy ion cutoff under different conditions has reproduced the forms of signature observed.Key words. Ionosphere (particle precipitation) Magnetospheric physics (energetic particles, precipitating, magnetopause, cusp and boundary layers)

We study a brightening of the Lyman-a emission in the cusp which occurred in response to a short-lived south-ward turning of the interplanetary magnetic field (IMF) during a period of strongly enhanced solar wind plasma concentration. The cusp proton emission is detected using the SI-12 channel of the FUV imager on the IMAGE spacecraft. Analysis of the IMF observations recorded by the ACE and Wind spacecraft reveals that the assumption of a constant propagation lag from the upstream spacecraft to the Earth is not adequate for these high time-resolution studies. The variations of the southward IMF component observed by ACE and Wind allow for the calculation of the ACE-to-Earth lag as a function of time. Application of the derived propagation delays reveals that the intensity of the cusp emission varied systematically with the IMF clock angle, the relationship being particularly striking when the intensity is normalised to allow for the variation in the upstream solar wind proton concentration. The latitude of the cusp migrated equatorward while the lagged IMF pointed southward, confirming the lag calculation and indicating ongoing magnetopause reconnection. Dayside convection, as monitored by the SuperDARN network of radars, responded rapidly to the IMF changes but lagged behind the cusp proton emission response: this is shown to be as predicted by the model of flow excitation by Cowley and Lockwood (1992). We use the numerical cusp ion precipitation model of Lockwood and Davis (1996), along with modelled Lyman-a emission efficiency and the SI-12 instrument response, to investigate the effect of the sheath field clock angle on the acceleration of ions on crossing the dayside magnetopause. This modelling reveals that the emission commences on each reconnected field line 2–2.5 min after it is opened and peaks 3–5 min after it is opened. We discuss how comparison of the Lyman-a intensities with oxygen emissions observed simultaneously by the SI-13 channel of the FUV instrument offers an opportunity to test whether or not the clock angle dependence is consistent with the "component" or the "anti-parallel" reconnection hypothesis.Key words. Magnetospheric physics (magnetopause, cusp and boundary layers; solar wind-magnetosphere interactions) – Space plasma physics (magnetic reconnection)