标题： 通过COCONUT进行的时间演化的日冕高效磁流体力学建模 显示英文标题

标题： Efficient magnetohydrodynamic modelling of the time-evolving corona by COCONUT

摘要： 与受恒定磁图约束的准稳态日冕模型相比，由时变光球磁图驱动的时变日冕模型更为现实，并且可以保留更多有用的信息以准确描述太阳风演化和预测日冕物质抛射（CME）传播。 本文展示了使用隐式方法和相对较大的时间步长，能够高效且准确地执行时变日冕模拟。 我们还评估了太阳活动极小期的一个太阳自转周期（CR）内，时变和准稳态模拟捕捉到的日冕结构之间的差异。 我们在一个惯性坐标系中，使用一系列每小时更新一次的光球磁图，在2019年日食前后的两个CR期间，从太阳表面到$25\; R_s$模拟日冕结构的演化。 我们将时变模拟与准稳态模拟进行比较，证明即使在太阳活动极小期，这两种日冕建模方法之间的差异也可能非常明显。 在某个CR周期内的20$\;R_s$处，径向速度和密度的相对差异可超过$15 \%$和$25 \%$。 我们还评估了时间步长对模拟结果的影响。 使用大约10分钟的时间步长，在效率和必要的数值稳定性和准确性之间取得平衡，可以在太阳活动极小期的时变日冕模拟中实现这一点，整个CR周期的日冕演化仅用9小时完成（使用1080个CPU核心处理1.5M网格单元）。 模拟结果表明，使用隐式方法可以高效且准确地执行时变磁流体力学（MHD）日冕模拟，为准稳态模拟提供了一个更现实的替代方案。 因此，全隐式的时变日冕模型有望在实际空间天气预报中准确模拟时变日冕。 显示英文摘要

摘要： Compared to quasi-steady-state corona models that are constrained by a time-invariant magnetogram over a CR period, time-evolving corona models driven by time-varying photospheric magnetograms are more realistic and can maintain more useful information to accurately describe solar wind evolution and forecast CME propagation. This paper demonstrate that time-evolving corona simulations can be performed efficiently and accurately using an implicit method with relatively large time steps. We also evaluate differences between coronal structures captured by time-evolving and quasi-steady simulations over a CR period during solar minimum. We used a series of hourly updated photospheric magnetograms to drive the evolution of coronal structures from the solar surface to $25\; R_s$ during two CRs around the 2019 eclipse in an inertial coordinate system. We compare the time-evolving and quasi-steady simulations to demonstrate that the differences in these two types of coronal modelling can be obvious even for a solar minimum. The relative differences in radial velocity and density can be over $15 \%$ and $25 \%$ at 20$\;R_s$ during one CR period. We also evaluated the impact of time steps on the simulation results. Using a time step of approximately 10 minutes balances efficiency and necessary numerical stability and accuracy for time-evolving corona simulations around solar minima, with coronal evolution during a full CR simulated within only 9 hours (using 1080 CPU cores for 1.5M grid cells). The simulation results demonstrate that time-evolving MHD coronal simulations can be performed efficiently and accurately using an implicit method, offering a more realistic alternative to quasi-steady-state simulations. The fully implicit time-evolving corona model thus promises to simulate the time-evolving corona accurately in practical space weather forecasting.