Self‐Consistent Modeling of Electron Precipitation and Responses in the Ionosphere: Application to Low‐Altitude Energization During Substorms

Abstract

We report a new modeling capability that self‐consistently couples physics‐based magnetospheric electron precipitation with its impact on the ionosphere. Specifically, the ring current model RAM‐SCBE is two‐way coupled to an ionospheric electron transport model GLOW (GLobal airglOW), representing a significant improvement over previous models, in which the ionosphere is either treated as a 2‐D spherical boundary of the magnetosphere or is driven by empirical precipitation models that are incapable of capturing small‐scale, transient variations. The new model enables us to study the impact of substorm‐associated, spectrum‐resolved electron precipitation on the 3‐D ionosphere. We found that after each substorm injection, a high‐energy tail of precipitation is produced in the dawn sector outside the plasmapause, by energetic electrons (10 < E < 100 keV) scattered by whistler‐mode chorus waves. Consequently, an ionospheric sublayer characterized by enhanced Pedersen conductivity arises at unusually low altitude (∼85 km), with its latitudinal width of ∼5–10° in the auroral zone. The sublayer structure appears intermittently, in correlation with recurrent substorm injections. It propagates eastward from the nightside to the dayside in the same drift direction of source electrons injected from the plasma sheet, resulting in global impact within the ionosphere. This study demonstrates the model's capability of revealing complex cross‐scale interactions in the geospace environment.

Potential Evidence of Low‐Energy Electron Scattering and Ionospheric Precipitation by Time Domain Structures

“…The diffuse aurora, generated by plasma sheet electron precipitation (∼0.1–10 keV) (Horne et al, 2003; Ni et al, 2008; Thorne et al, 2010), constitutes the dominant energy input among all types of aurora (Newell et al, 2009). Scattering of plasma sheet electrons into the diffuse aurora and its ionospheric feedback play a key role in magnetosphere‐ionosphere coupling (Frahm et al, 1997; Khazanov et al, 2014; Yu et al, 2018), thus having attracted significant attention (Khazanov et al, 2018; Ni et al, 2016).…”

The Case for Improving the Robinson Formulas

“…used the Link model to develop such profiles, andFang et al (2010) used the Lummerzheim model for a similar purpose. One study,Khazanov et al (2018), went further than this, using the Khazanov and Liemohn model to compute Pedersen and Hall conductances and relate these to the Robinson formulas Yu et al (2018). used the GLOW model instead of the Robinson formulas within a coupled global geospace simulation, demonstrating that the Robinson formulas are perhaps not even needed for large-scale modeling efforts.…”

Recent Advancements and Remaining Challenges Associated With Inner Magnetosphere Cross‐Energy/Population Interactions (IMCEPI)

“…Different models are interconnected to represent the sophisticated, nonlinearly coupled geospace system, allowing for a better understanding of the internal interactions. Compared to earlier models (e.g., Fok et al, , ; Ilie et al, ; Jordanova et al, , ; Lemon et al, ; Liemohn et al, ; Toffoletto et al, ), the inner magnetosphere models are now capable of resolving particle dynamics across a broader range of energy or regions, covering thermal‐energy plasmasphere, warm ring current particles, and energetic radiation belt populations (Fok et al, ; Ganushkina, Amariutei, et al, ; Huba & Sazykin, ; Huba et al, ; Jordanova et al, , ; Krall et al, ); they are more self‐consistently linked with the ionosphere system by taking into account more physics‐based ionosphere‐thermosphere processes (Raeder et al, ; Wiltberger et al, ; Xi et al, ; Yu et al, ); they can be driven by various tail dynamics using different approaches such as injecting particles within prescribed electromagnetic fields (e.g., Brito et al, ; Ganushkina et al, ; Jordanova et al, ) or by earthward propagating bubbles (e.g., Cramer et al, ; Yang et al, , ). They also include more realistic representation of the influence of plasma waves by including more types of waves or using newly derived pitch angle/energy/cross‐energy diffusion coefficients or loss rates based on tremendously increased data base in space, leading to significant improvement in the modeling of the energization/decay of inner magnetosphere populations (e.g., Aryan et al, ; Jordanova et al, ; Kang et al, ; Ma et al, ; Tu et al, ) and ionospheric precipitation/conductance (Chen, Lemon, Guild, et al, ; Chen, Lemon, Orlova, et al, ; Perlongo et al, ; Yu et al, ).…”