SH13A-4068:
3D Coronal Density Reconstruction and Retrieving Coronal Magnetic Field Structures during Solar Minimum and Maximum

Monday, 15 December 2014
Maxim Kramar, Catholic University of America, Washington, DC, United States, Vladimir Airapetian, NASA Goddard Space Flight Center, Greenbelt, MD, United States and Joseph M Davila, NASA Goddard SFC, Greenbelt, MD, United States
Abstract:
Measurement of the coronal magnetic field is a crucial ingredient in understanding the nature of solar coronal phenomena at all scales. We employ STEREO/COR1 data obtained during minimum and maximum of solar activity (Carrington rotations, CR, 2066 and 2131) to retrieve and analyze the three-dimensional (3D) coronal electron density in the range of heights from 1.5 to 4 Rsun using the tomography method and qualitatively deduce structures of the coronal magnetic field. The 3D electron density analysis is complemented by the 3D STEREO/EUVI emissivity in 195 A band obtained by tomography for the same CR periods. A global 3D thermodynamic MHD model of the solar corona was used to relate the reconstructed 3D density and emissivity to open/closed magnetic field structures. We show that the locations of density maximum can serve as an indicator of current sheet position, while the locations of the maximum of the density gradient can be a reliable indicator of closed-open magnetic field boundaries. We find that the magnetic field configuration during CR 2066 has a tendency to become radially open at heliocentric distances above 2.5 Rsun. We also find that the potential field model with a fixed source surface (PFSS) is not consistent with the positions of the boundaries between the regions with open and closed magnetic field structures. This indicates that the assumption of the potential nature of the coronal global magnetic field is not satisfied even during the deep solar minimum. Results of our 3D density reconstruction will help to constrain solar coronal field models and test the accuracy of the magnetic field approximations for coronal modeling.