The Scalable Plasma Ion Composition and Electron Density (SPICED) Model for Earth's Inner Magnetosphere. Issue 9 (13th September 2021)

• Record Type: Journal Article
• Authors: James, Matthew K.; Yeoman, Tim K.; Jones, Petra; Sandhu, Jasmine K.; Goldstein, Jerry
• Is Part Of: Journal of geophysical research. Volume 126:Issue 9(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-13
• Subjects: Magnetospheric physics -- Periodicals; Space environment -- Periodicals; Cosmic physics -- Periodicals; Planets -- Atmospheres -- Periodicals; Heliosphere (Astrophysics) -- Periodicals; Geophysics -- Periodicals; 523.01
• DOI: 10.1029/2021JA029565
• Languages: English
• ISSNs: 2169-9380

Abstract

Abstract: The plasma mass loading of the terrestrial equatorial inner magnetosphere is a key determinant of the characteristics and propagation of ultra low frequency waves. Electron number density is also an important factor for other types of waves such as chorus, hiss and EMIC waves. In this paper, we use Van Allen Probe data from September 2012 to February 2019 to create average models of electron densities and average ion mass in the plasmasphere and plasmatrough, near the Earth's magnetic equator. These models are combined to provide an estimate of the most probable plasma mass density in the equatorial region. We then use machine learning to form a set of models which are parameterized by the SuperMAG ring current index based on the design of the average models. The resulting set of models are capable of predicting the average ion mass, electron density and plasma mass density in the range 2 ≤ L ≤ 5.9 and over all magnetic local time sectors during a range of conditions where − 75 ≤ S M R ≤ + 27 nT. Key Points: Van Allen Probe data are used to create models of electron density and average ion mass Models are combined to describe plasma mass density in the magnetic equatorial plane Models are parameterized using artificial neural networks