The plasmasphere is an inner part of the Earth’s magnetosphere. Dense and cold plasmas (a few eV) are generated in the Earth’s ionosphere. Electrons in the ionosphere move along the Earth's magnetic field lines and those with energies larger than the escape energy can reach the inner magnetosphere; however, because ions are heavier, they cannot move to the inner magnetosphere. Therefore, an electric field develops in the region between the ionosphere and the inner magnetosphere. The ionospheric ions begin to move upward because of the generated electric field. The ionospheric electrons and ions move to the inner magnetosphere together. Light ions such as H+, He+, and O+ can easily escape from the ionosphere. During some hours and days, the escaping plasma accumulates until an equilibrium state is reached. The plasmasphere nearly rotates with the Earth. The region of the plasmasphere changes in size because of the geomagnetic activity, which causes a substantial loss of the plasmaspheric plasma and/or the refilling of the plasmasphere to occur during the geomagnetic active periods.
Whistler radio waves produced by lightning propagate along the Earth's magnetic field lines through the ionosphere, plasmasphere, and magnetosphere. The radio waves change frequencies during the propagation. Carpenter (1966) observed a sharp drop in frequency dispersion at approximately 3 Re, which is the plasmapause. The imager for magnetopause-to-aurora global exploration (IMAGE) satellite observed the resonance scattering of sunlight by He+ in the plasmasphere and captured images of the plasmasphere (Burch, 2000; Sandel et al., 2000). A tail on the plasmasphere, caused by plasmaspheric rotation and the electric fields generated by solar wind and magnetosphere interaction (Nishida, 1966), was also observed by the IMAGE satellite. The IMAGE satellite also showed the occurrence of interesting phenomena such as fingers, crenulations, channels, notches, shoulder, and shadow.
The plasma density gradient in the radial direction at the equator was estimated using ULF wave observations on the ground and satellite observations (Angerami and Carpenter, 1966; Denton et al., 2009; Sandhu et al., 2016). The plasma density gradient was estimated at 4–6 using the power-law model.
Plasmasphere models can either be based on satellite or ground-based observation data or are physical models. Carpenter and Anderson (1992) developed an empirical model of equatorial electron density in the range 2.25 < L < 8 using sweep frequency receiver radio measurements obtained by the international Sun-Earth explorer (ISEE) 1 satellite. The model shows the structures of the plasmasphere, plasmapause, and plasma trough for solar cycle variation. O'Brien and Moldwin (2003) developed an empirical model of the plasmapause location as a function of Kp, AE, and Dst using the combined release and radiation effects satellite (CRRES) observations. The global core plasma model (GCPM) is based on data from the dynamics explorer (DE) and ISEE satellites (Gallagher, 2000). The GCPM provides empirically derived plasma densities and ion compositions of H+, He+, and O+ as functions of geomagnetic and solar conditions. The GCPM also includes models for the plasmapause, trough, and polar cap. Plasma parameters below 2,000 km altitudes were calculated using the international reference ionosphere (IRI) (Bilitza et al., 2011). An electron temperature model at 1000–10,000 km altitudes was developed based on Akebono satellite measurements (Kutiev et al., 2004). The electron densities obtained from the upper hybrid resonance (UHR) frequency measured by the plasma wave and sounder (PWS) on the Akebono satellite were fitted to field-aligned electron density profiles using the sum of exponential and power-law functions (Kitamura et al., 2009). The transition height from O+ to H+ was found. The IMAGE model comes from radio plasma imager (RPI) measurements by the IMAGE satellite (Huang et al., 2004). The model provides a density distribution with L-value and latitude. The Institute of Terrestrial Magnetism, Ionosphere and Radio wave Propagation (IZMIRAN) model presents vertical profiles of electron density at altitudes of 1000–36,000 km based on whistler observations (Chasovitin et al., 1998). The global plasma ionosphere density model (GPID) is a physical model used to estimate the ion density and electron temperature in the plasmasphere along a magnetic flux tube (Webb and Essex, 2001). The model gives O+ and H+ densities and temperatures depending on solar and magnetic activities. The Sheffield university plasmasphere ionosphere model (SUPIM) estimates the densities, field-aligned fluxes and temperatures of O+, H+, He+, N2+, O2+, and NO+ ions, and electrons with time-dependent equations of continuity, momentum, and energy balance along eccentric-dipole magnetic field lines (Bailey et al., 1997). The field line interhemispheric plasma (FLIP) model solves the equations of continuity, momentum, and energy conservation for O+, H+, He+, and N+ ions along the inclined dipole geomagnetic field lines (Tu et al., 2003). A suprathermal ion mass spectrometer (SMS) on the Akebono satellite revealed ion heating and outflow in the polar region, which are important for the refilling of the plasmasphere (Watanabe et al., 1992; Abe et al., 1993).
A neural network was applied to build a plasmasphere model. Bortnik et al. (2016) developed a plasmasphere model that reconstructed the equatorial electron number density of the inner magnetosphere as a function of space and time from the electron number density estimated by three time history of events and macroscale interactions during substorms (THEMIS) probes between 2008 and 2014 and use the SYM-H index. The model shows the dynamics of plasmaspheric plume formation and corotation. Zhelavskaya et al. (2017) constructed a plasmasphere density distribution model with a neural network for the period from October 1, 2012 to July 1, 2016 using IMAGE/EUV data. The model showed the global evolution, erosion, and plume of the plasmasphere. Zheng et al. (2019) developed a three-dimensional solar wind-driven global dynamic plasmapause model using a neural network based on multi-satellite measurements with 37,859 plasmapause crossing events from January 4, 1995 to December 31, 2015. The model uses the parameters of solar wind speed, Bz of interplanetary magnetic field, SYM-H, and AE indices. The shape of the plasmapause was highly sensitive to these parameters as well as diurnal, seasonal, and annual variations.