[1] The transport and acceleration of low-energy electrons (50-250 keV) from the plasma sheet to the geostationary orbit were investigated. Two moderate storm events, which occurred on 6-7 November 1997 and 12-14 June 2005, were modeled using the Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM) with the boundary set at 10 R E in the plasma sheet. The output of the IMPTAM was compared to the observed electron fluxes in four energy ranges (50-225 keV) measured by the Synchronous Orbit Particle Analyzer instrument onboard the Los Alamos National Laboratory spacecraft. It was found that the large-scale convection in combination with substorm-associated impulsive fields is the drivers of the transport of plasma sheet electrons from 10 R E to geostationary orbit at 6.6 R E during storm times. The addition of radial diffusion had no significant influence on the modeled electron fluxes. At the same time, the modeled electron fluxes are one (two) order (s) smaller than the observed ones for 50-150 keV (150-225 keV) electrons, respectively, most likely due to inaccuracy of electron boundary conditions. The loss processes due to wave-particle interactions were not considered. The choice of the large-scale convection electric field model used in simulations did not have a significant influence on the modeled electron fluxes, since there is not much difference between the equipotential contours given by the Volland-Stern and the Boyle et al. (1997) models at distances from 10 to 6.6 R E in the plasma sheet. Using the TS05 model for the background magnetic field instead of the T96 model resulted in larger deviations of the modeled electron fluxes from the observed ones due to specific features of the TS05 model. The increase in the modeled electron fluxes can be as large as two orders of magnitude when substorm-associated electromagnetic fields were taken into account. The obtained model distribution of low-energy electron fluxes can be used as an input to the radiation belt models. This seed population for radiation belts will affect the local acceleration up to relativistic energies.

[1] The methodology based on the Error Reduction Ratio (ERR) determines the causal relationship between the input and output for a wide class of nonlinear systems. In the present study, ERR is used to identify the most important solar wind parameters, which control the fluxes of energetic electrons at geosynchronous orbit. The results show that for lower energies, the fluxes are indeed controlled by the solar wind velocity, as was assumed before. For the lowest energy range studied here (24.1 keV), the solar wind velocity of the current day is the most important control parameter for the current day's electron flux. As the energy increases, the solar wind velocity of the previous day becomes the most important factor. For the higher energy electrons (around 1 MeV), the solar wind velocity registered 2 days in the past is the most important controlling parameter. Such a dependence can, perhaps, be explained by either local acceleration processes due to the interaction with plasma waves or by radial diffusion if lower energy electrons possess higher mobility. However, in the case of even higher energies (2.0 MeV), the solar wind density replaces the velocity as the key control parameter. Such a dependence could be a result of solar wind density influence on the dynamics of various waves and pulsations that affect acceleration and loss of relativistic electrons. The study also shows that statistically the variations of daily high energy electron fluxes show little dependence on the daily averaged B z , daily time duration of the southward IMF, and daily integral R B s dt (where B s is the southward component of IMF).

Abstract. Electric currents flowing through near-Earth space (R ≤ 12 R E ) can support a highly distorted magnetic field topology, changing particle drift paths and therefore having a nonlinear feedback on the currents themselves. A number of current systems exist in the magnetosphere, most commonly defined as (1) the dayside magnetopause Chapman-Ferraro currents, (2) the Birkeland field-aligned currents with highlatitude "region 1" and lower-latitude "region 2" currents connected to the partial ring current, (3) the magnetotail currents, and (4) the symmetric ring current. In the near-Earth nightside region, however, several of these current systems flow in close proximity to each other. Moreover, the existence of other temporal current systems, such as the substorm current wedge or "banana" current, has been reported. It is very difficult to identify a local measurement as belonging to a specific system. Such identification is important, however, because how the current closes and how these loops change in space and time governs the magnetic topology of the magnetosphere and therefore controls the physical processes of geospace. Furthermore, many methods exist for identifying the regions of near-Earth space carrying each type of current. This study presents a robust collection of these definitions of current systems in geospace, particularly in the nearEarth nightside magnetosphere, as viewed from a variety of observational and computational analysis techniques. The influence of definitional choice on the resulting interpretation of physical processes governing geospace dynamics is presented and discussed.

Abstract. The NARMAX OLS-ERR methodology is applied to identify a mathematical model for the dynamics of the Dst index. The NARMAX OLS-ERR algorithm, which is widely used in the field of system identification, is able to identify a mathematical model for a wide class of nonlinear systems using input and output data. Solar windmagnetosphere coupling functions, derived from analytical or data based methods, are employed as the inputs to such models and the outputs are geomagnetic indices. The newly deduced coupling function, p 1/2 V 4/3 B T sin 6 (θ/2), has been implemented as an input to model the Dst dynamics. It was shown that the identified model has a very good forecasting ability, especially with the geomagnetic storms.

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[1] Transport and acceleration of the 5-50 keV electrons from the plasma sheet to geostationary orbit were investigated. These electrons constitute the low-energy part of the seed population for the high-energy MeV particles in the radiation belts and are responsible for surface charging. We modeled one nonstorm event on 24-30 November 2011, when the presence of isolated substorms was seen in the AE index. We used the Inner Magnetosphere Particle Transport and Acceleration Model (IMPTAM) with the boundary at 10 R E with moment values for the electrons in the plasma sheet. The output of the IMPTAM modeling was compared to the observed electron fluxes in 10 energy channels (from 5 to 50 keV) measured on board the AMC 12 geostationary spacecraft by the Compact Environmental Anomaly Sensor II with electrostatic analyzer instrument. The behavior of the fluxes depends on the electron energy. The IMPTAM model, driven by the observed parameters such as Interplanetary Magnetic Field (IMF) B y and B z , solar wind velocity, number density, dynamic pressure, and the Dst index, was not able to reproduce the observed peaks in the electron fluxes when no significant variations are present in those parameters. We launched several substorm-associated electromagnetic pulses at the substorm onsets during the modeled period. The observed increases in the fluxes can be captured by IMPTAM when substorm-associated electromagnetic fields are taken into account. Modifications of the pulse front velocity and arrival time are needed to exactly match the observed enhancements.

At geosynchronous Earth orbit, the radiation belt/ring current electron fluxes with energies up to several hundred kiloelectron volts can vary widely in magnetic local time (MLT). This study aims to develop Nonlinear AutoRegressive eXogenous models using system science techniques, which account for the spatial variation in MLT. This is difficult for system science techniques, since there is sparse data availability of the electron fluxes at different MLT. To solve this problem, the data are binned from Geostationary Operational Environmental Satellites (GOES) 13, 14, and 15 by MLT, and a separate Nonlinear AutoRegressive eXogenous model is deduced for each bin using solar wind variables as the inputs to the model. These models are then conjugated into one spatiotemporal forecast. The model performance statistics for each model varies in MLT with a prediction efficiency between 47% and 75% and a correlation coefficient between 51.3% and 78.9% for the period from 1 March 2013 to 31 December 2017.

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