A near-real-time data-assimilative model of the solar corona
Cooper Downs, J. A. Linker, Ronald M. Caplan, Emily I. Mason, Pete Riley, Ryder Davidson, Andres Reyes, Erika Palmerio, R. Lionello, James Turtle, M. Ben-Nun, Miko M. Stulajter, V. S. Titov, Tibor Török, Lisa Upton, Raphaël Attié, Bibhuti Kumar Jha, C. N. Arge, C. J. Henney, G. Valori, H. Strecker, D. Calchetti, D. Germerott, J. Hirzberger, D. Orozco Suárez, J. Blanco Rodríguez, S. K. Solanki, Xin Cheng, Shang Wu
Abstract
The Sun's corona is its tenuous outer atmosphere of hot plasma, which is difficult to observe. Most models of the corona extrapolate its magnetic field from that measured on the photosphere (the Sun's optical surface) over a full 27-day solar rotational period, providing a time-stationary approximation. We present a model of the corona that evolves continuously in time, by assimilating photospheric magnetic field observations as they become available. This approach reproduces dynamical features that do not appear in time-stationary models. We used the model to predict coronal structure during the total solar eclipse of 8 April 2024 near the maximum of the solar activity cycle. There is better agreement between the model predictions and eclipse observations in coronal regions located above recently assimilated photospheric data.