Global MHD Modeling of the Solar Corona and Inner Heliosphere for the Whole Heliosphere Interval

Details Global MHD Modeling of the Solar Corona and Inner Heliosphere for the Whole Heliosphere Interval Global MHD Modeling of the Solar Corona and Inner Heliosphere for the Whole Heliosphere Interval

Dec 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011soph..274..361r&link_type=abstract

Solar Physics, Volume 274, Issue 1-2, pp. 361-377

Physics

6

Sun, Corona, Corotating Interaction Regions, Magnetic Fields, Solar Wind, Interplanetary Medium

Scientific paper

In an effort to understand the three-dimensional structure of the solar corona and inner heliosphere during the Whole Heliosphere Interval (WHI), we have developed a global magnetohydrodynamics (MHD) solution for Carrington rotation (CR) 2068. Our model, which includes energy-transport processes, such as coronal heating, conduction of heat parallel to the magnetic field, radiative losses, and the effects of Alfvén waves, is capable of producing significantly better estimates of the plasma temperature and density in the corona than have been possible in the past. With such a model, we can compute emission in extreme ultraviolet (EUV) and X-ray wavelengths, as well as scattering in polarized white light. Additionally, from our heliospheric solutions, we can deduce magnetic-field and plasma parameters along specific spacecraft trajectories. In this paper, we present a general analysis of the large-scale structure of the solar corona and inner heliosphere during WHI, focusing, in particular, on i) helmet-streamer structure; ii) the location of the heliospheric current sheet; and iii) the geometry of corotating interaction regions. We also compare model results with i) EUV observations from the EIT instrument onboard SOHO; and ii) in-situ measurements made by the STEREO-A and B spacecraft. Finally, we contrast the global structure of the corona and inner heliosphere during WHI with its structure during the Whole Sun Month (WSM) interval. Overall, our model reproduces the essential features of the observations; however, many discrepancies are present. We discuss several likely causes for them and suggest how model predictions may be improved in the future.

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