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Characterizing Temperature Anisotropy with a Decade of RISR-N Extreme Ion Heating Events

Aidan
Thayer
New Jersey Institute of Technology
Abstract text

One of the longstanding problems in ionospheric science is that we typically assume the F-region ion velocity distribution to be an isotropic Maxwellian, meaning the ion temperature is the same in all directions with respect to the magnetic field. However, works from St.-Maurice et al., (1976), and Raman et al., (1981), show that in times of heating due to moderate to strong electric fields (above 50 mV/m), the O+ velocity distribution distorts, and the ion temperature becomes anisotropic. Here, data from the Resolute Bay Incoherent Scatter Radar-North (RISR-N) taken during extreme heating events, where the ion temperature is consistently above 2500 K for greater than 15 minutes, are used to resolve the ratio between the temperature perpendicular and parallel to the magnetic field. By assuming diffusion is the dominant physical process vertical to the magnetic field, we can assume that plasma along a flux tube is subject to similar ion-neutral frictional heating due to the ExB drift. Thus, this calculation is performed using beams scanning the same magnetic flux tubes, as confirmed through spearman correlation. This presentation will provide results characterizing temperature anisotropy derived from heating events of a variety of intensities, showing the versatility and applications of the approach for characterizing temperature anisotropy for all AMISR systems.

Authors
Aidan Thayer, Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ
Lindsay V Goodwin, Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ
William Longley, Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ
Jean Pierre St Maurice, Department of Physics and Engineering Physics, University of Saskatchewan, Saskatoon, SK, Canada & Department of Physics and Astronomy, University of Western Ontario, London, ON, Canada
Student in poster competition
Poster category
DATA - Data Assimilation, Data Analytics, Methods and Management