Sub-Auroral Polarization Streams: A complex interaction between the magnetosphere, ionosphere, and thermosphere

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

“…It is also difficult to determine the spatial and temporal evolution of the low-altitude structure across finite monitors. Even when the ionosphere is driven by first-principle magnetospheric models that provide the particle precipitation (e.g., Connor et al, 2016;Raeder et al, 2016Raeder et al, , 2001Zhang et al, 2015), the precipitation itself is still crudely estimated without having a physical energy spectrum. However, to date, most ionosphere models coupled with thermospheric dynamics, such as Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) (Richmond et al, 1992;Roble et al, 1988), Coupled Thermosphere Ionosphere Model (CTIM) (Fuller-Rowell & Rees, 1980;Rees & Fuller-Rowell, 1988), and Global Ionosphere Thermosphere Model (GITM) (Ridley et al, 2006), are driven by auroral precipitation obtained from empirical precipitation models (e.g., Hardy et al, 1987;Newell et al, 2009;Spiro et al, 1982).…”

Recent Developments in Our Knowledge of Inner Magnetosphere‐Ionosphere Convection

“…For example, Yu et al () modeled SAPS on 17 March 2013 using ring current‐atmosphere interactions model with self‐consistent magnetic field and Block Adaptive Tree Solarwind‐Roe‐Upwind Scheme and captured a SAPS feature at subauroral latitudes, but the SAPS velocities were underestimated, and its location was deeper than in actual observations. Raeder et al () modeled the same event using Open Geospace General Circulation Model, Coupled Thermosphere Ionosphere Model, and Rice Convection Model and found better overall agreement with observations in terms of SAPS location and velocity; they attributed the improvement (compared to Yu et al, ) to the contribution of ionospheric feedback in the trough. The influence of SAPS on thermospheric winds was analyzed using the Thermosphere Ionosphere Electrodynamics General Circulation Model by Wang, Talaat, et al () who showed that SAPS drive westward thermospheric winds due to joule heating and ion drag, similar to the observations presented in Zhang et al ().…”

“…Modeling efforts: A majority of the modeling efforts during the last solar cycle were focused on SAPS observations during geomagnetic storms, especially the St. Patrick's day storms in 2013 and 2015 (Huba et al, ; Krall et al, ; Raeder et al, ; Yu et al, ). For example, Yu et al () modeled SAPS on 17 March 2013 using ring current‐atmosphere interactions model with self‐consistent magnetic field and Block Adaptive Tree Solarwind‐Roe‐Upwind Scheme and captured a SAPS feature at subauroral latitudes, but the SAPS velocities were underestimated, and its location was deeper than in actual observations.…”

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, ).…”

“…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, 2017;Jordanova et al, 2016;Kang et al, 2016;Ma et al, 2018;Tu et al, 2014) and ionospheric precipitation/conductance (Chen, Lemon, Guild, et al, 2015;Chen, Lemon, Orlova, et al, 2015;Perlongo et al, 2017;Yu et al, 2016). Following earlier efforts in combining kinetic models with global MHD models (De Zeeuw et al, 2004;Ebihara & Tanaka, 2013;Glocer et al, 2009Glocer et al, , 2013Pembroke et al, 2012), more ring current models have been equipped with such capability during the past few years by coupling with global MHD models (e.g., Cramer et al, 2017;Raeder et al, 2016;Welling et al, 2018;Yu et al, 2017Yu et al, , 2014. The above advanced models are largely capable of reproducing various particle dynamics within the global magnetosphere and providing important feedback processes on particle populations, the electric/magnetic fields, and dynamics in other geospace regions.…”