RESEARCH ARTICLE The ‐ Electron Precipitation 10.1029/2019JA026589 Dynamics and Their Geospace Consequences Key Points: • Simulated magnetospheric During the 17 March 2013 Storm dynamics depends on the pattern George V. Khazanov1 , Margaret W. Chen2 , Colby L. Lemon2 , and David G. Sibeck1 and intensity of electrons precipitating into the atmosphere 1NASA Goddard Space Flight Center, Greenbelt, MD, USA, 2The Aerospace Corporation, El Segundo, CA, USA • Precipitating electron energy fluxes enhanced by multiple atmospheric reflections affect ionospheric conductance Abstract During geomagnetic storms and substorms, the magnetosphere and ionosphere are strongly • Reduced electric field shielding at coupled by precipitating magnetospheric electrons from the 's plasma sheet and driven by both low L can lead to an increase in magnetospheric and ionospheric processes. Magnetospheric wave activity initiates electron precipitation, modeled energy content and the ionosphere and upper atmosphere further facilitate this process by enhancing the value of precipitated energy fluxes via connection of two magnetically conjugate regions and multiple atmospheric reflections. This paper focuses on the resulting electron energy fluxes and affiliated height‐integrated Correspondence to: fl G. V. Khazanov, Pedersen and Hall conductances in the auroral regions produced by multiple atmospheric re ections during [email protected] the 17 March 2013 and their effects on the inner magnetospheric electric field and ring current. Our study is based on the magnetically and electrically self‐consistent Rice Convection ‐ fi Citation: Model Equilibrium of the inner magnetosphere with SuperThermal Electron Transport modi ed electron Khazanov, G. V., Chen, M. W., Lemon, energy fluxes that take into account the electron energy interplay between the two magnetically conjugate C. L., & Sibeck, D. G. (2019). The . SuperThermal Electron Transport‐modified energy flux in the Rice Convection ‐ magnetosphere ionosphere electron ‐ fi precipitation dynamics and their Model Equilibrium leads to a signi cant difference in the global conductance pattern, ionospheric electric geospace consequences during the 17 field formation, structure, ring current energization and its energy content, subauroral March 2013 storm. Journal of polarization drifts intensifications and their spatial locations, interchange instability redistribution, and Geophysical Research: Space Physics, 124. https://doi.org/10.1029/ overall energy interplay on the global scale. 2019JA026589

Received 1 FEB 2019 1. Introduction Accepted 11 JUN 2019 Accepted article online 26 JUN 2019 The importance of ionospheric conductivity in coupling magnetospheric and ionospheric plasmas has been recognized since the early days of space science. Wolf (1970) and Vasyliunas (1970) used the ionospheric Ohm's law to calculate the electric field distribution governing magnetospheric plasma circulation. The central importance of ionospheric electrodynamics and conductivity in governing magnetosphere‐ ionosphere‐thermosphere dynamics is evident across a broad range of solar terrestrial science topics: for example, thermospheric responses to geomagnetic storms (Wang et al., 2008), conductivity correlations with dayside field‐aligned currents (Ohtani et al., 2005), global magnetosphere configuration (Ridley et al., 2004), substorm dynamics (Raeder et al., 2001), ring current dynamics (Chen et al., 2015; Ebihara et al., 2004), sub- auroral polarization drifts (SAPS; Anderson et. al., 1993; Zheng et al., 2008; Huba et al., 2017; Mishin et al., 2017), and plasma sheet fast‐flow dynamics (Zhang et al., 2012). Ionospheric conductance depends strongly on particle precipitation into the atmosphere. Both and electrons precipitate in the ; however, the average integral number flux of the precipitating auroral ions is typically 1 to 2 orders of magnitude less than that of the precipitating auroral electrons (Hardy et al., 1989). Simulations of Chen et al. (2019) of electron precipitation (due to wave scattering) and precipitation (due to field line curvature) during a large storm showed that precipitating electrons are the dominant contributor to auroral conductance. Therefore, the electron precipitating flux requires careful examination. Chen et al. (2015) noted “The simulated stormtime ring current energization can vary significantly depending on the ionospheric conductance and electron loss model used. Thus, it is important to incorporate realistic descriptions of ionospheric conductance and electron losses in inner magnetospheric models.” Early simulations of diffuse electron auroral precipitation assumed strong pitch angle scattering ©2019. American Geophysical Union. everywhere with perhaps a constant fraction of backscatter (Chen & Schulz, 2001; Fontaine & Blanc, This article has been contributed to by 1983; Wolf et al., 1982). Chen, Lemon, Orlova, et al. (2015) showed that strong pitch angle scattering caused US Government employees and their fl work is in the public domain in the electron losses that were too rapid to account for observed trapped electron uxes at Geosynchronous orbit. USA. Recent models of Chen et al. (2019), Chen, Lemon, Orlova, et al. (2015), and Yu et al. (2016) that include

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more realistic electron losses of pitch angle scattering with chorus waves have been able to reproduce rea- sonably well observed diffuse precipitating electron energy fluxes near dawn during storm events. However, further work is needed to characterize global patterns of electron precipitation. During geomagnetic storms and substorms, the magnetosphere and ionosphere are strongly coupled by pre- cipitating magnetospheric electrons from the Earth's plasma sheet. As has been shown by Khazanov et al. (2014) about 15–40% of the total aurora energy returns back to the magnetosphere and the conjugate iono- sphere. Collisionless processes dominate in the inner magnetosphere, whereas collisional interactions are important in the ionosphere, and Khazanov et al. (2018) have emphasized that first‐principle simulations of precipitating electron fluxes in both regimes are required to understand spatial and temporal variations of ionospheric conductance and related electric fields. As discussed by Khazanov et al. (2015), Khazanov, Glocer et al. 2016, 2017a), the first step in such simulations is initiation of electron precipitation from the Earth's plasma sheet via wave‐particle interactions (WPIs) into both magnetically conjugate points (e.g., as is simulated by Chen, Lemon, Guild, et al., 2015). The second step is to account for multiple atmospheric reflections of electrons between the ionosphere and magnetosphere at the two magnetically conjugate points, as treated in the SuperThermal Electron Transport (STET) model (Khazanov et al., 2015, 2017a, 2017b, 2018; Khazanov, Glocer, et al., 2016; Khazanov, Himwich, et al., 2016). This paper focuses on the resulting electron energy fluxes and affiliated height‐integrated Pedersen and Hall conductances in the auroral regions produced by multiple atmospheric reflections during the large 17 March 2013 geomagnetic storm and their effects on the inner magnetospheric electric field and ring current. Our study is based on the Aerospace version of the magnetically and electrically self‐consistent Rice Convection Model‐Equilibrium (RCM‐E) of the inner magnetosphere (Chen, Lemon, Guild, et al., 2015), with STET‐modified electron energy fluxes that take into account the electron energy interplay between the two magnetically conjugate ionospheres.

2. Role of MI Coupling in Electron Precipitation Formation In the aurora, precipitating electrons driven by WPI in the Earth's plasma sheet collide with atmospheric molecules, lose energy, and produce secondary electrons (SEs) via impact ionization. The precipitating and SEs can also reflect back into the magnetosphere and then undergo multiple reflections at the magnetic conjugate points. As was shown by Khazanov et al. (2015–2018), these processes greatly influence the total precipitating flux at the upper ionospheric boundary (around about 800 km). The resultant populations of secondary and primary electrons undergo both elastic and inelastic collisions with the neutral atmosphere, cascading toward lower energies and reflecting back to the magnetosphere. Those electrons reflected upward from the ionosphere can be trapped in the magnetosphere if they scatter out of the loss cone via cou- lomb collisions with the cold plasma or through interactions with different kinds of plasma waves. In situ measurements of the precipitating electron energy flux spectra in the ionosphere naturally include all these effects. However, the physics of multiple reflections and scattering has been missing in aurora global mod- eling research, and in this study we add this capability to RCM‐E simulations and examine the effects on inner magnetospheric plasma transport and the electric and magnetic fields. The STET code models all sources and collisional processes of electrons as they travel along a magnetic field line through the magnetosphere and ionosphere (Khazanov et al., 2015; Khazanov, Glocer, et al., 2016; Khazanov, Himwich, et al., 2016; Khazanov et al., 2017b) with participation of both magnetically conjugate regions. It simulates nonsteady formation of electron distribution functions kinetically along 1‐D in space and 2‐D in velocity space (energy and pitch angle). It can be applied for conditions at all latitudes and long- itudes. It also applies equally well to open and closed magnetic field configurations. The STET code takes into account two major electron sources: photoelectrons and precipitating electrons of magnetospheric ori- gin. Photoelectrons are produced as a result of interaction of solar extreme ultraviolet (EUV) and X‐ray radiation with the neutral atmosphere. In the STET code this radiation is driven by the F10.7 index. SEs also included in the STET code and are produced by precipitation of high energy (>500 eV) electrons of magneto- spheric origin that are driven by wave‐particle processes as discussed by Chen et al. (2012) and Khazanov et al. (2015). STET accounts for all elastic and inelastic collisional processes of superthermal electrons with

major neutral atmospheric components (N2,O2, and O) in the energy range of 1 eV to 50 keV. To perform the calculations, we used the following inputs for the STET model. The neutral thermospheric densities and temperatures were given by MSIS‐90 (Hedin, 1991). The electron profile in the ionosphere

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was calculated based on the International Reference Ionosphere model (Bilitza et al., 2017) and extended in the plasmasphere region using the assumption that the electron thermal density distribution in the 2 plasmasphere is proportional to the geomagnetic field as ne ~ B . This case indicates some intermediate step occurring during plasmaspheric refilling (Khazanov et al., 1984) and corresponds to the large L‐shells where electron diffuse aurora is taken place. Cross sections for elastic collisions, state‐specific excitation, and ionization were taken from Solomon et al. (1988).

3. Modifications of SE Energy Flux and Mean Energy via MI Coupling The STET code is a well‐established code developed and improved in the past few decades. Khazanov (2011) and Khazanov et al. (2014, 2015, 2017b); Khazanov, Glocer, et al., (2016); Khazanov, Himwich, et al., (2016) provide extensive details on the current version of the Figure 1. Energy distributions of precipitating electrons obtained at 850‐km altitude at local midnight at L = 7.0 with and without multiple atmospheric STET code. Figure 1 shows the STET calculation for downward energy reflections in the magnetically conjugate points. fluxes at an ionospheric altitude of 850 km that approximately corre- sponds to the boundary between the ionosphere and magnetosphere and also corresponds to the mapping ionospheric altitude that is used in the RCM‐E model. Here we have chosen the Maxwellian spectra for the electron fluxes initially injected from the magnetosphere:

− = ΦðÞ¼E CEe E E0; (1)

where C is the normalization factor and E0 is the characteristic energy of precipitated magnetospheric elec- − − trons. The constant C is normalized for a total energy flux of 1 erg·cm 2·s 1, with an assumption that the pitch angle distribution is isotropic in the earthward direction. This figure shows a comparison of the down- ward electron fluxes with and without multiple reflections for four different characteristic energies of 1 keV (red), 5 keV (green), 10 keV (dark blue), and 15 keV (light blue). The choice of the Maxwellian distribution (1) presented in the current study is also consistent with the con- clusion of Chen, Lemon, Orlova, et al. (2015) that “most of the simulated differential electron flux spectra could be fit fairly well by a Maxwellian distribution.” It also corresponds with the choice of the distribution function in Robinson et al. (1987) that will be used in this study. Observations by McIntosh and Anderson (2014), however, have shown that the electron distribution function in the aurora has more complicated morphology that accounts for only 47% of distribution presented by (1). This issue will be addressed in more detail in future RCM‐E and STET coupling studies. In order to demonstrate the importance of SE Magnetosphere‐Ionosphere (MI) coupling elements in the cal- culation of ionospheric conductance driven by RCM‐E precipitation, we use simple analytical formulae developed by Robinson et al. (1987) that represent height‐integrated conductance:

ÀÁ 40E = Σ 0:85 Σ ¼ Φ1 2; H ¼ 0:45 E ; (2) P 2 E Σ 16 þ E P

where ΣP and ΣH are the Pedersen and Hall conductances, E is the electron mean energy, and ΦE is the elec- tron energy flux. These empirical conductance formulae are widely used in the space science community in global models for magnetosphere‐ionosphere processes (see, e.g., recent papers by Wolf et al., 2016, Wiltberger et al., 2016, and Perlongo et al., 2017), and we modify equation (2) here by taking into account SE MI coupling processes that redistribute energy fluxes and mean energies as shown in Figure 2. Because the Robinson et al. formulae are widely used in the community, Khazanov et al. (2018) used STET to provide a simple modification to the Robinson et al. formulae for precipitating electron energy flux spectra that do not take into account the multiple reflection process (e.g., from magnetospheric models). However, it is preferable to modify the simulated precipitating electron energy spectra directly, as this would produce a

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more realistic description of the precipitating electron distribution and account for precipitated electron energy deposition to the neutral atmo- sphere and ionospheric plasma components. Such distributions could then be applied as upper boundary inputs to first‐principles auroral iono- spheric particle transport and energy deposition codes (Solomon, 2001; Strickland et al., 1993), as well as to the Robinson et al. formulae. The methodology of modifying the energy fluxes in (2) is quite similar to that discussed by Khazanov et al. (2018) for the modification of Pedersen and Hall conductances by accounting for the SE MI coupling processes. First, we run two cases of the STET code as presented in Figure 1. One of these cases solves the STET kinetic equation along the magnetic field line with- out taking into account multiple reflection processes in both magneti- cally conjugate atmospheres (solid line in Figure 1), while the other fi fi ¼ caseÀÁ (dashed lines) includesÀÁ them. We nd the modi cation factors, Kc ¼ fl Φ Kc E and KE KE E , to the integrated energy uxes, E, and mean energies, E, predicted by RCM‐E simulations to be ÀÁ ÀÁ ΦWMR ¼ Φ ; WMR ¼ E Kc E E E KE E (3)

ΦWMR WMR fl where E and E are the new total energy ux and mean energy that are modified by MI coupling SE processes and replace the corresponding values in the calculation of integrated ionospheric conduc- tances (2). These parameters are defined in accordance to Robinson et al. (1987) as

E ∫ max ΦWMRðÞ ; Emax WMR E E dE ΦWMR ¼ ∫ EΦWMRðÞE dE; E ¼ Emin (4) E Emin Emax ∫ ΦWMRðÞE dE; Emin

with the same limits of integrations, Emin = 500 eV and Emax = 30 keV, and the WMR index refers to calculations that took into account the con- jugate ionospheric region and multiple atmospheric reflections. For the results that are presented below, we use the approach developed Figure 2. The ratios K (see (3) and (5)) for modified integrated energy fluxes by Khazanov et al. (2018). As in the prior study, we introduce the bound- (a) and mean energies (b) as functions of the mean E energies that are ary conditions for precipitating magnetospheric electron fluxes at 850 km, ‐ ‐ provided by the RCM E = Rice Convection Model Equilibrium code. NMR to be consistent with RCM‐E model. We calculate the differential electron = no multiple reflections and WMR = with multiple reflections. energy fluxes from 500 eV to 30 keV, assuming their distribution function is isotropic in pitch angle at the upper ionospheric boundary and that they represent the magnetospheric contribution of precipitated electrons driven by electron scattering from whis- tler chorus waves (in the plasma sheet) and hiss (in the plasmasphere) as modeled by the RCM‐E. To be con- sistent with Robinson et al. (1987; see equation (2)), we have assumed that precipitating plasma sheet

electrons have Maxwellian distribution functions given by equation (1) with the 15 different values of Eo selected between 400 eV and 30 keV. Figure 2 presents the ratios K for modified integrated energy fluxes, and mean energies as functions of the mean E energies that are provided by the RCM‐E code. The ratios that are presented in Figure 2 have simple analytical fits as functions of mean energies. These analytical functions are as follows:

 2 Kc ¼ 3:36− exp 0:597−0:37*E þ 0:00794*E (5) 2 Ec ¼ 0:073 þ 0:933*E−0:0092*E

and used in the relations of (3) in order to modify the conductance calculation in formula (2) as

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Σ ÀÁ Σ ¼ 40Ec Φ1=2WMR; H ¼ : 0:85 P 2 E 0 45 Ec (6) þ ΣP 16 Ec

In these formulas, as well as in Figure 2, the mean energy E corresponds to ENMR, that is, the mean energy of precipitated electrons that is calculated without multiple atmospheric reflections by the RCM‐E. To include the effect of multiple atmospheric reflections for simulating storm time variations of ionospheric conduc- tance and electric fields, the RCM‐E calculates conductances using relation (6) with corresponding modifi- cation factors from equations (3) and (5).

4. RCM‐E Description In addition to the direct effect of the “STET modification” equations (5) on the precipitating fluxes and con- ductance, the feedback between conductance and electric potential would modify the magnetospheric plasma transport and further couple into the magnetic field. Changes to the hot electron drift paths will alter the trapped electron fluxes, while changes in the cold plasma evolution will alter the rate at which the trapped electron fluxes are converted into precipitating fluxes via pitch angle scattering by chorus and hiss waves. In order to test the impact of the STET modification, we apply it to the precipitating elec- tron fluxes computed by the RCM‐E, which includes these coupled processes. The RCM‐E is a model of magnetospheric plasma drift, electrodynamic coupling with the ionosphere (Harel, 1981; Sazykin et al., 2002, 2005), and coupling between the plasma and magnetic field (Lemon, 2003, Lemon et al., 2004). The RCM‐E combines the Rice Convection Model (Harel et al., 1981; Toffoletto et al., 2003) with a with a magnetic field solver [Lemon, 2003] that ensures force equilibrium (self‐consistency) between the plasma pressure gradient (∇P) and magnetic force (J × B). The version used at The Aerospace Corporation (Chen et al., 2012, Chen, Lemon, Orlova, et al., 2015, Chen, Lemon, Guild, et al., 2015, Chen et al., 2019, 2018) is different than the version used at Rice University (Yang et al., 2014, 2016), but the fundamental physics and much of the central code is the same. For the purpose of this paper, the most noteworthy difference is that the Aerospace version includes a more comprehensive treatment of electron and ion precipitation (Chen et al., 2019). The model computes the bounce‐averaged guiding center drift trajectories of electrons, protons, and O+ ions in the closed field line region of the magnetosphere. To reduce the dimensionality of the calculation, it com- putes drift paths under the simplifying assumption that particles are undergoing continuous elastic pitch angle scattering; this eliminates drift shell splitting, and all particles of a given energy and species follow the same drift trajectory. Because the drift paths are bounce‐averaged and isotropized, the phase space den- sity (η) is a function of two spatial dimensions and one velocity dimension. The two spatial dimensions are represented on a low‐altitude spherical grid that is mapped along the self‐consistent magnetic field to con- jugate points in the magnetic equatorial plane, and the velocity dimension is represented by an isotropized adiabatic energy invariant λ. Because drifting particles carry current across magnetic field lines, gradient/curvature drift can lead to an imbalance in the flow of charge into or out of a given flux tube; this is rectified by enforcing current conti- nuity (∇ · J = 0), and the RCM computes the Birkeland currents under the assumption that the magneto- spheric drift currents drive charge into and through the ionosphere. Given the ionospheric conductance (field‐line‐integrated conductivity), Ohm's law is then used to compute the electric potential across the ionosphere:

J∥ ¼ ∇⊥·ðÞΣ·ðÞ−∇⊥V (7)

where Σ is the conductance tensor, ∇⊥is the two‐dimensional divergence/gradient operator perpendicular to the magnetic field, and V is the electric potential to be solved for. Ionospheric conductance Σ is repre- sented by a combination of quiet time EUV‐driven ionization, based on the International Reference Ionosphere model (Bilitza & Reinisch, 2008) and a magnetospheric contribution due to precipitating elec- trons and ions computed using the empirical relation of Robinson et al. (1987) and Galand and Richmond (2001), respectively. Electron precipitation in the RCM‐E (Chen, Lemon, Guild, et al., 2015) is driven by a parameterized model of electron lifetimes due to plasmaspheric hiss (Orlova et al., 2014) and chorus

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(Orlova & Shprits, 2014). Proton and O+ ion precipitation is driven by field line curvature scattering based on field line tracing in the RCM‐E's self‐consistently computed magnetic field (Chen et al., 2019). According to previous studies (e.g., Fu et al., 2001), the contribution of outflow oxygen ions from ionosphere to ring current formation becomes significantly more important when magnetic storms are more intense. The RCM‐E includes the effects of ion composition in the plasma sheet through the specification of dynamic + + plasma boundary conditions at 10 RE with the O /H density ratio specified by the Kp and F10.7 dependent relation of Young et al. (1982). RCM‐E simulations have been able to account simultaneously for variations in observed magnetic intensity and trapped ion [Chen et al., 2012] and electron (Chen, Lemon, Guild, et al., 2015) fluxes.

5. Global Response To understand the global response of MI SE coupling processes on the results presented below, we emphasize that an increase of the energy fluxes at the boundary between the ionosphere and magnetosphere (850 km) is the result of the two interconnected magnetically conjugate ionospheric regions and corresponding multiple atmospheric reflections between them. As we demonstrated above, this leads to an enhancement of the total energy flux forming at the upper ionospheric boundary of 850 km. Previous global kinetic (e.g., Chen et al., 2019; Chen, Lemon, Orlova, et al., 2015) and magnetohydrodynamic (e.g., Wiltberger et al., 2016) models did not take these processes into account, and only used the magnetospheric contribution of energy flux to calculate ionospheric conductances. This led to underestimation of the total ionospheric energy input and corresponding electric conductances. As we mentioned in the previous section, the RCM‐E is a highly nonlinear self‐consistent model that is magnetically and electrically coupled with ion and electron inner magnetospheric dynamics. Therefore, an enhancement of the total simulated electron energy fluxes will not simply lead to an increase of ionospheric conductances on the global scale everywhere. This is because ionospheric conductance has a strong influence on the electric field calculated in the ionosphere and mapped back to the magnetospheric altitudes, redistributing electron and ion magnetospheric dynamics and affiliated Birkeland currents. Such nonlinear feedback complicates the interpretation of MI coupling dynamics that we present in this section. To demonstrate the global consequences of conductance changes via SE MI coupling processes, we simu- late the large geomagnetic storm (minimum Dst of −131 nT) that occurred on 17 March 2013 using the RCM‐E with the Robinson et al. formulae (6) and the STET‐modified precipitating electron energy flux (3) and mean energy (5). The simulation results are compared with RCM‐E results for a run using the Robinson et al. relations (2) and simulated precipitating electron energy flux distributions without any STET modification (i.e., using only electron energy fluxes generated by magnetospheric WPI processes as discussed by Chen, Lemon, Guild, et al., 2015). For simplicity, we hereafter refer to these two runs as “with STET modification” and “without STET modification.” Each of these simulation runs uses the same time‐ dependent event‐specific RCM‐E boundary conditions that are described in detail in Chen et al. (2019).

Figure 3a shows the SYM‐H index (black curve) of the 17 March 2013 storm and the SYM‐HRCME index for RCM‐E runs with (red curve) and without (blue curve) STET modifications. The simulated

SYM‐HRCME index, calculated from the Dessler‐Parker Sckopke relation (Dessler & Parker, 1959; Sckopke, 1966) with a solar wind pressure correction, is arguably too simplistic to be compared directly with the observed SYM‐H that includes the effect of all currents including the tail current (Turner et al., 2000), especially so during the recovery phase when the ring current is weakened. However, the

SYM‐HRCME index is proportional to the total energy content of the simulated plasma, and the results shown in Figure 3 indicate that the overall simulated ring current energy content is significantly enhanced when multiple atmospheric electron reflections are taken into account. The enhancement of global ring current energy begins after the sudden commencement at early storm main phase, about 1.5 hr into the 17 March 2013 storm, and persists through the end of 18 March 2013. Ring current energization results from the inward transport of plasma sheet ions (see Chen et al., 1995, and references therein) and electrons during storm‐associated enhancements in the inner magnetospheric elec- tric field, with electrons contributing up to 10–20% of the total energy content (Liu et al., 2005; Chen et al., 2005; Jordanova & Miyoshi, 2005; Zhao et al., 2015). Associated with the formation of the ring current,

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Figure 3. From 17 to 18 March 2013: (a) SYM‐H (black curve) and the SYM‐HRCME without (red curve) and with (blue curve) STET modifications. Equatorial radial profiles of the simulated (b, c) total pressure and (d, e) magnetic field per- turbation. R is the equatorial geocentric radial distance normalized by the Earth radius. MLT = magnetic local time; RCM‐ E = Rice Convection Model‐Equilibrium; STET = SuperThermal Electron Transport.

which is often asymmetric, are magnetic field depressions (Le et al., 2004). Thus, radial distributions of the equatorial total particle pressure (electrons, protons, and O+ ions) and magnetic field depressions reveal the spatial extent of ring current energization and intensity. Examples of the simulated equatorial radial profile of the total particle pressure and magnetic field perturbations, the difference between the RCM‐E and dipole magnetic intensity, at 21:00 magnetic local time (MLT) without and with STET corrections during 17–18 March 2013 are shown in Figures 3b–3e, respectively. The equatorial geocentric distance normalized by the Earth radius is denoted by R. Throughout the main and recovery phases of the storm, the total particle pressure is enhanced above ~10 nPa to lower geocentric radial distances with the STET modifications at 21:00 MLT. Similarly, the simulated ring current magnetic depressions are larger closer to the Earth during the storm main phase with the STET modifications than without. To understand why the inclusion of the multiple electron atmospheric reflections in the precipitating elec- tron energy flux distribution has a significant impact on ring current formation, we first examine the simu- lated equatorial particle transport from sudden commencement to the early main phase. Figure 4 shows a series of RCM‐E equatorial electron pressure plots from 06:00 to 9:00 UT of 17 March 2013 without and with STET modifications. In these plots the blue curve is the dayside magnetopause, the white contour is the RCM‐E plasmapause, and the gray contours are equipotentials without the corotation potential. At

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Figure 4. A series of simulated equatorial electron pressure (b, d, f, h, and j) with and (a, c, e, g, and i) without SuperThermal Electron Transport (STET) modifications from 06:00 to 09:00 UT on 17 March 2013. The blue and white curves correspond to the Rice Convection Model‐Equilibrium dayside magnetopause and plasmapause, respectively.

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06:00 UT, the equatorial equipotentials and spatial extent of the electron pressure look roughly similar without (Figure 4a) and with (Figure 4b) the STET modifications. At 06:20 and 06:40 UT, the simulated equipotentials with the STET modification (Figures 4d and 4f) are less dense on the dawnside outside of the plasmapause than those without the STET modifications (Figures 4c and 4e). This indicates a weaker electric field on the dawnside and is consistent with a larger conductance associated with the enhanced electron precipitating electron fluxes that have been corrected to include the effect of multiple electron atmospheric reflections (to be shown a little later in this section). On the duskside outside of the plasma- pause, the simulated equipotentials with the STET modification tend to be more concentrated where the electron pressure is very weak, as compared to the run without the STET modification. This increase in the electric field occurs in regions of low conductivity where there are no or weak precipitating electron energy fluxes. These trends continue as convection is enhanced during the early main phase. At 8:00 UT (Figures 4g and 4h) and 9:00 UT (Figures 4i and 4j), it is apparent that with STET modifications that (1) the simulated electron pressure is enhanced at lower geocentric radial distances from premidnight to late morning as electrons drift eastward and (2) the simulated electron pressure is diminished from dusk to pre- midnight as it is more difficult for electrons to be transported toward dusk because they are precipitated as their drift speed slows down near kinks in the equipotentials, where the spatial gradient is nearly zero; this can be understood from bounce‐averaged guiding center drifts derived from Hamiltonian equations of motion (see equations (10) and (11) of Schulz, 1998). Figure 5 shows the simulated equatorial total ion (H+ and O+) pressure in a format similar to Figure 4. Unlike the electrons, the ions tend to gradient‐ curvature drift westward. The simulated ion precipitation due to field line curvature is relatively weak com- pared to electron precipitation (Chen et al., 2019) and H+‐H charge exchange lifetimes are much longer than the electron lifetimes that are used in our model (Chen et al., 2019). Thus, with the STET modifica- tions, by 08:00 UT the simulated ion pressure is enhanced at lower geocentric distance from dusk through midnight to dawn (Figure 5h). While ions are the main contributor to the overall energization of the ring current during storms, the dif- fuse precipitating electrons and field‐aligned or Birkeland currents play important roles in the formation of the electric field. Examples of the simulated integrated precipitating electron energy flux at 850 km mapped to the equatorial plane at times during the early (08:00 UT) and late (20:00 UT) main phase of the 17 March 2013 storm are shown in Figures 6a–6d. At 08:00 UT, the simulated precipitating electron energy flux with STET modifications (Figure 6b) is significantly enhanced from premidnight through dawn to late morning but also reduced in some regions on the duskside outside the plasmapause where not many electrons were transported (see Figure 5h). Later at 20:00 UT, the precipitating electron energy flux with STET modifications is larger almost everywhere outside the plasmapause proper and even in the plasmaspheric plume on the duskside. Examples of the evolution of RCM‐E precipitating electron flux at 850 km in magnetic latitude (MLAT) in the auroral region for the storm event are shown in Figures 6e– 6h. The white vertical lines demarcate a period during the early main phase to facilitate visual inspection. At midnight (Figures 6e and 6f) and during the early main phase, the simulated precipitating electron energy flux with STET modifications are enhanced to lower latitudes. During recovery phase, the electron energy fluxes weaken and there is a paucity of fluxes in the plasmaspheric plume, that differ slightly between the cases with or without the STET modifications. At 21:00 MLT (Figures 6g and 6h) and during the early main phase, the precipitating electron energy flux with STET modifications are enhanced but occur at higher latitudes from about 07:00 to 10:00 UT. This is due to electrons not being able to be trans- ported farther inward due to a redistribution of the electric and magnetic field (see Figure 6b) as discussed earlier. The simulated Hall and Pedersen conductance at midnight and 21:00 MLT, in the same format as Figures 6e–6h, are displayed in Figure 7. In the auroral region, the Hall conductance is generally larger than the Pedersen conductance. As expected, the temporal evolution of the auroral conductance is very similar to that of the precipitating electron energy flux, showing significant differences in the magnitude of the simu- lated conductance without and with STET modifications during the storm. From equatorial views of the Hall and Pedersen conductance at 850 km (Figure 8), one can see the contribution of the model conductance from solar EUV, which is kept static in the RCM‐E, and the auroral conductance contributions. Where the con- ductance is enhanced with the STET modifications (see Figures 8b and 8f), the electric field intensity tends to be reduced and vice versa (see Figures 9b and 9d). With the STET modifications, a strong increase in the

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Figure 5. Similar format as Figure 4 except for ion pressure.

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Figure 6. The simulated precipitating electron energy flux at 850 km mapped to the equatorial plane at 08:00 UT (a, b) and 20:00 UT (c, d) on 17 March 2013 without and with STET modifications. The simulated electron energy flux as a function of MLAT during 17 to 18 March 2013 at (e, f) 00:00 MLT and (g, h) 21:00 MLT without and with STET modifications. MLAT = magnetic latitude; STET = SuperThermal Electron Transport; MLT = magnetic local time.

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Figure 7. Simulated Hall and Pedersen conductance at 850 km (a, c, e, and g) without and (b, s, f, and h) with STET mod- ifications as a function of MLAT during 17 to 18 March 2013 at 00:00 and 21:00 MLT. MLAT = magnetic latitude; STET = SuperThermal Electron Transport; MLT = magnetic local time.

electric field intensity develops in the region of low conductivity between dusk and premidnight (see Figures 9b and 9d). The simulated equatorial radial profile of the electric field intensity at 850 km at 21:00 MLT shown in Figures 9e and 9f show that with STET modifications that the electric field from R ~ 4 to 6 can be significantly enhanced.

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Figure 8. Simulated Hall and Pedersen conductance at 850 km mapped to the equatorial plane (a, c, e, and g) without and (b, d, f, and h) with STET modifications at 08:00 UT and 21:00 magnetic local time on 17 March 2013. STET = SuperThermal Electron Transport.

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Figure 9. Simulated electric field intensity at 850 km (a–d) mapped to the equatorial plane without and with STET modifications at 08:00 UT and 21:00 MLT on 17 March 2013. Radial profiles of the electric field intensity at 850 km during 17 to 18 March 2013 at 21:00 MLT (e, f) without, with STET modifications. MLT = magnetic local time; STET = SuperThermal Electron Transport.

The field‐aligned or Birkeland currents are also important for the redistribution of the electric field through the MI coupling process (see equation (7)). Examples of simulated Birkeland current density at 850 km mapped to the equatorial plane are shown in Figure 10. In these plots blue/red correspond to currents going into/out of the ionosphere. The Birkeland currents depend on the gradient of particle pressure. In all the examples shown in Figure 10, the strong downward current from the dayside to premidnight correspond to strong gradients in the partial ring current pressure. At subauroral MLATs from dusk to midnight, SAPS can occur when Birkeland currents form in the low conductance region equatorward of the precipita- tion boundary. Figure 11 shows the simulated precipitating electron energy flux, Hall conductance, Birkeland current density, and E × B drift speed at 8:00 UT on 17 March 2013 without and with STET mod- ifications. The gray solid contour corresponds to a representative low conductance of 2.5 S that demarcates the low conductance region. Without the STET modifications, one can see signs of interchange instability

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Figure 10. Simulated Birkeland current density at 850 km mapped to the equatorial plane (a, c) without and (b, d) with SuperThermal Electron Transport (STET) modifications at 08:00 UT and 21:00 magnetic local time on 17 March 2013.

from ~20 to 8 MLT, similar to what was reported by Sazykin et al. (2002). Ring current pressure structure shown in Figures 4 and 5, as well as the flute‐like structures (e.g., see features within the black oval in Figure 10b) that appear in Birkeland current density and presented in Figures 10 and 11, indicates the development of interchange instability that requires further quantitative investigation beyond the scope of this paper. The possibility of interchange instability in near‐Earth plasma has a rich history and had been discussed for many space plasma physics applications (e.g., Xing and Wolf, 2007). Mingalev et al. (2006) found that downward current structures are more localized compared to upward currents. This is clearly seen in the Birkeland currents simulations presented in Figure 11. Considering interchange instability in the pre- sence of field‐aligned current, Golovchanskaya and Maltsev (2003) argue that their modified interchange instability generates structures that are topologically consistent with the discrete arcs observed during periods of steady magnetospheric convection. They also pointed out that the resulting interchange instability structure could be relevant to the north‐south arcs that are observed by Zesta et al. (2000). Similar north‐south topological structures can be seen in the simulated Birkeland currents presented in Figure 11. With the STET modifications, there is less interchange instability from ~20 to 1 MLT, where the conductance has been enhanced. It is easier to drive Birkeland currents in the region of higher conductance, which reduces the feedback on the electric field. The plot of the |E × B| drift speed shows that there are less strong flow channels from ~20 to 1 MLT with the STET modifications, but that the SAPS are stronger and extend to lower latitude with the STET modification. Late in the main phase at 20:00 UT, features of interchange instability in the simulated Birkeland currents from ~4 to 8 MLT (see Figures 10c and 10d) without and with the STET modifications are not as distinctly different. This also requires further quantitative investigation beyond the scope of this paper.

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Figure 11. For 08:00 UT on 17 March 2013: At 850 km the simulated (a, b) Birkeland current density, (c, d) precipitating electron flux, (e, f) Hall conductance, and (g, h) E × x B drift speed without and, with STET modifications. The white and, gray curves correspond to the Rice Convection Model‐EquilibriumRCM‐E plasmapause and the 2.5 ‐Siemen contour, respectively. MLAT = magnetic latitude; MLT = magnetic local time; STET = SuperThermal Electron Transport; SAPS = subauroral polarization drifts.

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6. Summary The importance of ionospheric conductivity in coupling magnetospheric and ionospheric plasmas has been recognized since the early days of space science, and it is believed that precipitating electrons are the domi- nant contributor to auroral conductance [Hardy et al., 1989; Chen, Lemon, Guild, et al., 2015, Chen et al., 2018]. Because ionospheric conductance is difficult to measure directly (e.g., Kosch et al., 1998), the capabil- ity to model precipitating electrons accurately is critically important. This has motivated careful examina- tion of how precipitating electrons are calculated in global models based on first principles. As demonstrated in our previous studies (Khazanov et al., 2015–2018), and sections 2 and 3 of this paper, plasma sheet electrons that are scattered into the loss cone by WPI processes and precipitated to the iono- sphere lose their energy due to nonelastic collisions with the neutral atmosphere and produce SEs. These initial auroral precipitation electrons with energies above 500 eV (which are mostly responsible for the for- mation of electric conductance) do not disappear into the ionosphere completely but rather escape to the magnetosphere. Khazanov et al. (2014) found that 15–40% of the total aurora energy returns back to the mag- netosphere and the conjugate ionosphere. Some of the escaping electrons are trapped in the inner plasma sheet via Coulomb collision or WPI processes that scatter them out of the loss cone. Other escaping electrons (primary and secondary) can reach the conjugate ionosphere along closed magnetic field lines and continu- ously ionize the upper atmosphere at the conjugate locations. After the first bounce, the precipitating elec- trons that have originated in the conjugate ionosphere also follow the same cycle as the primary precipitating electrons of magnetospheric origin, and a portion of them can again be reflected back to the original ionosphere along closed field lines, continuing the collisional processes with the neutral atmo- sphere. This reflection process is repeated multiple times in the diffuse aurora regions of both magnetically conjugate points and, as we demonstrate above, leads to a dramatic enhancement of the intensity of electron fluxes that ends up stabilizing between the ionosphere and magnetosphere altitudes. We investigate the effects of the enhanced electron energy fluxes, due to the electron energy interplay between the two magnetically conjugate ionospheres, on the ring current and inner magnetospheric electric field during the 17 March 2013 geomagnetic storm. Using the Aerospace version of the magnetically and electrically self‐consistent RCM‐E inner magnetosphere model (Chen et al., 2018; Chen, Lemon, Guild, et al., 2015) simulations without and with STET modifications were made and the results are compared. A summary of the results follows: 1. With the STET modifications, there can be significant differences in the simulated precipitating electron energy fluxes during the storm. Outside the plasmapause, the precipitating electron energy flux is gener- ally enhanced from midnight to dawn to noon through the main and recovery phases, and the enhance- ment occurs at lower latitudes than without the STET modification. However, outside the plasmapause during the early main phase of the storm, a paucity of precipitating electron energy flux develops from dusk to premidnight with STET modifications as the result of changes of the ionospheric electric field that maps back to the magnetosphere distributing ring current ions and electrons. 2. In the auroral region of significant electron precipitation, the simulated Hall and Pedersen conductances with the STET modification vary similarly as the precipitating electron energy fluxes during the storm. The Hall conductance is generally larger than the Pedersen conductance in the auroral region. However, the STET‐modified conductance pattern along with the RCM‐E magnetospheric feedback makes these conductances drastically reorganized on the global scale. 3. As a result, with STET modifications the redistribution of the electric field is significant during the early main phase for this storm event. Where the simulated auroral conductance is enhanced, there is a weak- ening of the electric field. Because it is easier to drive currents through the ionosphere where there is high conductance, this results in less feedback to the electric field. Effectively, less shielding of the electric field occurs at lower MLATs or equatorial R in the auroral region with the STET modifications. Where there is very low conductance outside of the auroral region with the STET modification, there is a strengthening of the electric field. 4. With STET modification, the RCM‐E code suppresses the area of interchange instability development but enhances the region of SAPS and their intensities. 5. With a less shielded electric field on the nightside, the ion pressure is larger at lower R values with the STET modification, and this is associated with a strong ring current perturbation magnetic field. The over- all energy content of the ring current is somewhat increased with the inclusion of the STET modification.

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Thus, the STET modifications of backscatter and multiple reflections (which is largely neglected in most dif- fuse aurora models) have significant implications not only for the precipitating electron energy flux but also for the ionospheric electric field and ring current formation. To summarize our discussion presented in this paper, we conclude that STET‐modified energy flux in RCM‐ E code leads to significant differences in the global conductance pattern, ionospheric electric field formation, Birkeland current structure, ring current energization and its energy content, SAPS intensifications and their MLAT/MLT locations, interchange instability redistribution, and overall energy interplay on the global scale.

Acknowledgments References The OMNI data used as input for the RCM‐E simulations were obtained from Anderson, P. C., Hanson, W. B., Heelis, R. A., Craven, J. D., Baker, D. N., & Frank, L. A. (1993). A proposed production model of rapid – the GSFC/SPDF OMNIWeb interface subauroral ion drifts and their relationship to substorm evolution. Journal of Geophysical Research, 98(A4), 6069 6078. https://doi.org/ (http://omniweb.gsfc.nasa.gov). We 10.1029/92JA01975 thank numerous geomagnetic Bilitza, D., Altadill, D., Truhlik, V., Shubin, V., Galkin, I., Reinisch, B., & Huang, X. (2017). International Reference Ionosphere 2016: From ‐ – observatories (Kakioka [JMA], ionospheric climate to real time weather predictions. , 15, 418 429. https://doi.org/10.1002/2016SW001593 Honolulu and San Juan [USGS], Bilitza, D., & Reinisch, B. (2008). International Reference Ionosphere 2007: Improvements and new parameters. 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