Hybrid Description of Outflowing Ionospheric Plasma: A Monte Carlo/n-Moment Transport Equations Model

Details Hybrid Description of Outflowing Ionospheric Plasma: A Monte Carlo/n-Moment Transport Equations Model Hybrid Description of Outflowing Ionospheric Plasma: A Monte Carlo/n-Moment Transport Equations Model

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsa23a1466j&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #SA23A-1466

Physics

[2475] Ionosphere / Polar Cap Ionosphere, [2481] Ionosphere / Topside Ionosphere, [2736] Magnetospheric Physics / Magnetosphere/Ionosphere Interactions, [7959] Space Weather / Models

Scientific paper

At terrestrial high latitudes, the plasma flows along “open” field lines, gradually going from a collision-dominated region into a collisionless region. Over several decades, the (fluid-like) generalized transport equations, TE, and the particle-based Monte Carlo, MC, approaches evolved as two of the most powerful simulation techniques that address this problem. In contrast to the computationally intensive Monte Carlo, the transport equations’ approach is relatively much more efficient but its validity is questionable in the collisional-to-collisionless transition region where double-peaked velocity distribution functions can form. We developed a hybrid model that combines the strengths of both approaches. In particular, arbitrary n-order transport equations were applied within the collision-dominated region, while a Monte Carlo simulation is applied within the collisionless region and the collisional-to-collisionless transition region. As a case study, we applied this model on the Coulomb-Milne problem because of its relevance to the ion outflow problem. A parametric study was carried out where we systematically varied the test-to-background ion mass ratio, mi/mb, the altitude where the MC and the ME are coupled, the expansion order of the TE, n, and the number of the MC simulations particles, N. The efficiency and accuracy of the model, and how they depend on those parameters will be discussed.

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