Fluid closures for the modelling of reconnection and instabilities in magnetotail current sheets

Abstract

The integration of kinetic effects in fluid models is important for global simulations

of the Earth’s magnetosphere. Although magnetohydrodynamics (MHD), which is

currently used for large scale modelling in space weather research, is a useful tool,

there are other physical effects not included in the MHD model which are important

at smaller scales such as the Hall effect, the pressure tensor and electron inertia.

In this thesis we use a two-fluid ten-moment model, which includes the pressure

tensor of both species, to study some of the phenomena associated with magnetotail

dynamics – magnetic reconnection, current sheet instabilities and ballooning instabilities,

followed by global simulations in which these processes interact. We first

introduce an extension of existing ten-moment models by using a nonlocal heat flux,

which approximates Landau damping in the fluid framework, followed by a study of

magnetic reconnection during the merging of two flux tubes or magnetic islands. We

then perform linear calculations and simulations of the drift-kink and lower hybrid

drift instabilities in thin current sheets, and simulations of the ballooning instability

in current sheets with curved mangetic geometries. Comparisons to kinetic simulations

show the improvements compared to MHD and standard two-fluid models as

well as the limitations of the ten-moment model. We then perform simulations which

include a dipole field and self-consistent formation of the magnetotail current sheet

and show that the stretching and disruption of the sheet, which is expected to occur

during magnetic substorms, can be captured by the model.

Finally, in an exploration of how the moment equations can be extended and what

additional insight is gained from higher moment models, we use the maximum entropy

method to reconstruct particle distributions in reconnection regions. The results

show that without information other than the moments, the model can reproduce the

general structure of the distributions but not all of the finer details.