Ionospheric energy inputs affecting plasma outflow and neutral upwelling

Details Ionospheric energy inputs affecting plasma outflow and neutral upwelling Ionospheric energy inputs affecting plasma outflow and neutral upwelling

Dec 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufmsm44a..08o&link_type=abstract

American Geophysical Union, Fall Meeting 2011, abstract #SM44A-08

Physics

[2407] Ionosphere / Auroral Ionosphere, [2431] Ionosphere / Ionosphere/Magnetosphere Interactions, [2706] Magnetospheric Physics / Cusp, [2736] Magnetospheric Physics / Magnetosphere/Ionosphere Interactions

Scientific paper

Ion outflow in the ionosphere has shown evidence of correlation with both Poynting flux and soft electron precipitation in the cusp (Strangeway et al., JGR 2005). The heat input from these energy sources might also affect neutral gas in the ionosphere, contributing to upwelling phenomena seen at the dayside cusp (Lühr et al., GRL 2004). Using data from the Fast Auroral Snapshot Explorer (FAST) and the Challenging Minisatellite Payload (CHAMP) satellites, correlations of electromagnetic and particle energy inputs are examined with both ion outflow and neutral upwelling in the cusp. This study confirms the results from Strangeway 2005 and extends that study to include time periods throughout a solar cycle. Inclusion of CHAMP data expands the parameters to include data on the density of neutral gas at orbital altitudes. The added ability to process large quantities of data quickly and reference the data between separate satellites in this statistical survey gives clues to the consistency of the observed correlations with ion outflow over time and to the relative importance of these energy sources in the neutral upwelling phenomenon. It also provides the ability to understand these connections in a broad spectrum of conditions of the Sun and solar wind as well as in the Earth's magnetosphere. The data used in the analysis is available from U.C. Berkeley (FAST) and Helmholtz Centre Potsdam (CHAMP). Analysis is done with open sources tools including new Python libraries such as SpacePy (Morley et al., SciPy 2010).

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