Determining energy pathways for the energisation of radiation belt electrons by very low frequency waves
Lead Research Organisation:
Northumbria University
Department Name: Fac of Engineering and Environment
Abstract
We will investigate how the solar wind controls conditions inside Earth's magnetic bubble, known as the magnetosphere. In this region, the material is so tenuous that collisions between particles are very rare. Instead, the electrons and ions in near-Earth space undergo interactions with electromagnetic waves that change their energy and direction and can lead to significant electron acceleration to relativistic speeds. We will specifically investigate how the electromagnetic waves are energised by variability within the magnetosphere, driven by the variable conditions of the solar wind.
Organisations
Publications
Abraham J
(2022)
Thermal Energy Budget of Electrons in the Inner Heliosphere: Parker Solar Probe Observations
in The Astrophysical Journal
Allanson O
(2022)
Weak Turbulence and Quasilinear Diffusion for Relativistic Wave-Particle Interactions Via a Markov Approach
in Frontiers in Astronomy and Space Sciences
Allanson O
(2021)
Electron Diffusion and Advection During Nonlinear Interactions With Whistler-Mode Waves
in Journal of Geophysical Research: Space Physics
Allanson O
(2020)
Particle-in-Cell Experiments Examine Electron Diffusion by Whistler-Mode Waves: 2. Quasi-Linear and Nonlinear Dynamics
in Journal of Geophysical Research: Space Physics
Bakrania M
(2020)
Statistics of solar wind electron breakpoint energies using machine learning techniques
in Astronomy & Astrophysics
Bentley S
(2020)
Random Forest Model of Ultralow-Frequency Magnetospheric Wave Power
in Earth and Space Science
Bentley S
(2021)
The magnetospheric interactions of predicted ULF wave power
Description | Our understanding of the hazardous near-Earth space environment requires knowledge of how electromagnetic waves affect the number and energy of high-energy electrons that are trapped in Earth's magnetic fields. Through this work, we have studied in detail the spatial and temporal variability of a range of different electromagnetic waves. We have shown that our previous models of the wave-particle interactions resulted from too much averaging of observations, and that a better route for modelling is to construct more detailed reconstructions of the wave and plasma conditions in space. Temporal variability in the governing equations changes the solution of the equations, and much more work is required to understand this behaviour, especially given the wild variation of the waves and plasma conditions. |
Exploitation Route | These findings should benefit the academic sector as it seeks to better understand wave-particle interactions in terrestrial space plasmas and in the plasma environments of other astrophysical objects. There is a credible pathway from these findings to improvement of operational space weather models, although this will require more funded research activity. |
Sectors | Aerospace Defence and Marine Environment |
Title | Data files for 'Temporal variability of quasilinear pitch-angle diffusion' |
Description | Data in the three folders was used for "Temporal variability of quasilinear pitch-angle diffusion" Clare E. J. Watt" (2022),Hayley J. Allison,Sarah N Bentley,Rhys L Thompson,I Jonathan Rae,Oliver Allanson, Nigel P. Meredith,Johnathan P J Ross,Sarah A Glauert,Richard B. Horne,Shuai Zhang,Kyle R Murphy, Dovile Rasinskaite,Shannon Killey, Front. Astron. Space Sci. - Space Physics, DOI: 10.3389/fspas.2022.1004634 The data files contain the results and input for the ensemble numerical experiments described in the manuscript. There are 3 sets of experiments for 3 different L* locations. Each set of experiments has 6 different ?t (timescale of variability). Each experiment has 60 scenarios. In each folder, there are 60 files with phase space density as a function of pitch-angle (91 values) and time (121 values). There are also 60 files listing the series of index numbers for the random selection of diffusion coefficients used in each individual scenario. The index number refers to the lists at of diffusion coefficients archived at "PADIE diffusion coefficients for plasmaspheric hiss" (Watt et al., 2019) |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://figshare.northumbria.ac.uk/articles/dataset/Data_files_for_Temporal_variability_of_quasiline... |