Coronal Magnetic Field Extrapolation from Synchronic Data with AI-generated Solar Farside
Channel: COSPAR2021 Workshops
Date: 2021-02-02

Authors: Jeong Hyun-Jin, Yong-Jae Moon, Eunsu Park, Harim Lee

Abstract: Solar coronal magnetic fields are usually extrapolated from photospheric fields, for which farside data is taken when it was at the frontside, about two weeks earlier. In this study, we have improved global magnetic field extrapolations by using more realistic farside magnetograms generated by deep learning. We generate the farside magnetograms from three channel (17.1, 19.5, and 30.4 nm) farside observations of Solar Terrestrial Relations Observatories (STEREOs) by our deep learning model trained with frontside Solar Dynamics Observatory (SDO) extreme ultraviolet (EUV) images and magnetograms. For frontside testing data sets, we demonstrate that the generated magnetic field distributions are consistent with the real ones; not only active regions (ARs), but also quiet regions of the Sun. We make global magnetic field synchronic maps in which conventional farside data are replaced by farside ones generated by our model. The synchronic maps show much better not only the appearance of ARs but also the disappearance of others on the solar surface than before. We use these synchronized magnetic data to extrapolate the global coronal fields using Potential Field Source Surface (PFSS) model. The results of coronal fields, calculated from both the conventional and the synchronized data, are compared with coronal EUV observations from the SDO and STEREOs. Our results are more consistent with the observations than those of the conventional method in view of solar active regions and open field regions (coronal holes). Finally, we will discuss several positive prospects of our new methodology for the study of solar corona, heliosphere, and space weather.
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (2018-0-01422, Study on analysis and prediction technique of solar flares).