Data-driven MHD Simulation Of Time-dependent Solar Wind

Solar wind plays an important role in space weather, and 3 dimensional(3D)magnetohydrodynamics(MHD) simulation serves as one of the essential methods of studying it. In this paper, we try to construct a time-dependent solar wind MHD model from the solar surface to 1 astronomical unit(AU) and beyond.The code is based on our previous work of SIP-AMR-CESE model. This model implements the space-time conservation element and solution element(CESE)MHD solver on an 6-component grid with adaptive mesh re?nement(AMR)technique.Base on the SIP-AMR-CESE model, we design a negative-pressure controlling method. A series of switches are used to detect the locations where negative pressure may occur, and the pressure equation is adopted in the MHD equations at these locations to control the negative pressure. Besides, we choose a row-scaling method, which re-scales the MHD variables according to their local values, and further improves the stability of our model.In this simulation, we ?rst achieve the initial solar wind background with time-relaxation method by inputting a potential ?eld obtained from the synoptic photospheric magnetic ?eld, and then generate the time-evolving solar wind by advancing the initial 3D solar wind background with continuously varying photospheric magnetic ?eld. The model updates the inner boundary conditions by using the projected normal characteristic(PNC) method, inputting the highcadence photospheric magnetic ?eld data corrected by solar di?erential rotation,and limiting the mass ?ux escaping from the solar photosphere.We employ the model to investigate the solar wind evolution from July 1st to August 11 th in 2008 using the synoptic maps provided by Global Oscillation Network Group(GONG). We compare the numerical results with the previous studies on the solar wind, the solar coronal observations from the Extreme ultraviolet Imaging Telescope(EIT) board on Solar and Heliospheric Observatory(SOHO), and the measurements from OMNI at 1 astronomical unit(AU).Comparisons show that the present data-driven MHD model’s results have overall good agreement with the large-scale dynamical coronal and interplanetary structures, including the sizes and distributions of coronal holes, the positions and shapes of the streamer belts, the heliocentric distances of the Alfv′enic surface, and the transitions of the solar wind speeds and magnetic ?eld polarities. However, the model fails to capture the small-sized equatorial holes and their associated high-speed stream, and the modeled solar wind near 1 AU has a little higher density and weaker magnetic ?eld strength than observed. Maybe high-cadence observed photospheric magnetic ?eld(particularly 3D global measurements), combined with plasma measurements, will enable the data-driven model to more accurately capture the time-dependent changes of the solar wind ambient for further improvements.