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Plain Language Summary Radiation belts of the Earth, which are the zones of charged energetic particles trapped by the geomagnetic field, comprise enormous and dynamic systems. While the inner radiation belt, composed mainly of high-energy protons, is relatively stable, the outer belt, filled with energetic electrons, is highly variable and depends substantially on solar activity. Hence, extended reliable observations and the improved models of the electron intensities in the outer belt depending on solar wind parameters are necessary for prediction of their dynamics. The Cluster mission has been measuring electron flux intensities in the radiation belts since its launch in 2000, thus providing a huge dataset that can be used for radiation belts analysis. Using 16 years of electron measurements by the Cluster mission corrected for background contamination, we derived a uniform linear-logarithmic dependence of electron fluxes in the outer belt on the solar wind dynamic pressure.
The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.
The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.
We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES-15 measurements of 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling GOES-15 flux values and an upper boundary condition scaling factor (BF). The GOES-15 flux model utilizes an input and feedback delay of 2 and 2 time steps (i.e., 5 min time steps) with the most efficient number of hidden layers set to 10. Magnetic local time, Dst, Kp, solar wind dynamic pressure, AE, and solar wind velocity were found to perform as predicative indicators of GOES-15 flux and therefore were used as the exogenous inputs. The NARX-derived upper boundary condition scaling factor was used in conjunction with the Versatile Electron Radiation Belt (VERB) code to produce reconstructions of the radiation belts during the period of July-November 1990, independent of in-situ observations. Here, Kp was chosen as the sole exogenous input to be more compatible with the VERB code. This Combined Release and Radiation Effects Satellite-era reconstruction showcases the potential to use these neural network-derived boundary conditions as a method of hindcasting the historical radiation belts. This study serves as a companion paper to another recently published study on reconstructing the radiation belts during Solar Cycles 17-24 (Saikin et al., 2021, ), for which the results featured in this paper were used.
In the last years, electron density profile functions characterized by a linear dependence on the scale height showed good results when approximating the topside ionosphere. The performance above 800 km, however, is not yet well investigated.
This study investigates the capability of the semi-Epstein functions to represent electron density profiles from the peak height up to 20,000 km. Electron density observations recorded by the Van Allen Probes were used to resolve the scale height dependence in the plasmasphere.
It was found that the linear dependence of the scale height in the topside ionosphere cannot be directly used to extrapolate profiles above 800 km.
We find that the dependence of scale heights on altitude is quadratic in the plasmasphere. A statistical model of the scale heights is therefore proposed. After combining the topside ionosphere and plasmasphere by a unified model, we have obtained good estimations not only in the profile shapes, but also in the Total Electron Content magnitude and distributions when compared to actual measurements from 2013, 2014, 2016 and 2017.
Our investigation shows that Van Allen Probes can be merged to radio-occultation data to properly represent the upper ionosphere and plasmasphere by means of a semi-Epstein function.