The First Comparative Study of Data-driven Solar Coronal Field Models

To better understand the magnetic field in the solar corona, it is crucial to accurately measure the time-evolving coronal field. Recently, a new modeling methodology, the data-driven coronal field model, in which the coronal magnetic field evolves in response to the sequentially updated photospheric boundary field, has been developed quite rapidly. We report on the very first attempt to systematically compare different data-driven models by using a magnetic flux emergence simulation as a ground-truth data set. We find that all models succeed in reproducing, at least, the helical flux rope structure. However, there exist a certain degree of model dependence and discrepancies from the ground-truth field. We discuss causes of the discrepancies and possible solutions to improve the models.