2019-2022: ISSI Team on "Magnetic open flux and solar wind structuring of interplanetary space" (lead: M. Temmer)
Correctly deriving magnetic open flux on the Sun and the distance to coronal hole (CH) boundaries is a long-standing open question and crucial for modelling the background solar wind (Linker et al., 2017; Wallace et al., 2019). Knowing the background solar wind in interplanetary (IP) space is fundamentally important for reliable coronal mass ejection (CME) propagation modelling and forecasting (e.g., Vršnak & Zic 2007; Temmer et al. 2011). However, estimates of open solar magnetic flux from remote photospheric and in situ spacecraft observations can differ by as much as a factor of two, which is well outside the measurement uncertainties (e.g., Arden et al., 2014). This suggests a fundamental issue in our understanding about the topology of the coronal magnetic field and the energisation of plasma. To tackle that issue, we will bring together an international team of experts with a wide range of expertise to determine the physical source of the (missing) open solar flux using the powerful approach of combining models and observations. Based on the results, we will develop a methodology for reproducing the interplanetary magnetic field open flux at 1AU distance range with full assessment of uncertainty that can serve as a benchmark for global coronal magnetic field and solar wind models.
2020-2022: ISSI Team on 3D CME reconstruction (lead: C. Verbeke, L. Mays)
Coronal Mass Ejections (CMEs) are large-scale eruptions of plasma and magnetic fields from the Sun. They are considered to be the main drivers of strong space weather events at Earth. Multiple models have been developed over the past decades to be able to predict the propagation of CMEs and their arrival time at Earth. Such models require input from observations, which can be used to fit the CME to an appropriate structure. The team aims to focus on both CME observations as well as modeling and ultimately provide a benchmark of where the community stands on CME arrival time prediction. Such a benchmark is essential for scientists to improve existing models and/or create new models, as well as for tracking improvements arising from new observations. For such a project, it is crucial to bring together expertise from both the observational and the modeling communities.