Iterative Tomography: A Key to Providing Time-Dependent 3-D Reconstructions of the Inner Heliosphere and the Unification of Space Weather Forecasting Techniques - Jackson, Bernard V.; Buffington, Andrew; Cota, Lucas; Odstrcil, Dusan; Bisi, Mario M.; Fallows, Richard; Tokumaru, Munetoshi (Frontiers in Astronomy and Space Sciences, 2020)
Over several decades UCSD has developed and continually updated a time dependent iterative three-dimensional (3-D) reconstruction technique to provide global heliospheric parameters – density, velocity, and component magnetic fields. For expediency, this has used a kinematic model as a kernel to provide a fit to either interplanetary scintillation (IPS) or Thomson-scattering observations. This technique has been used in near real time over this period, employing Institute for Space-Earth Environmental Research (ISEE), Japan IPS data to predict the propagation of these parameters throughout the inner heliosphere. We have extended the 3-D reconstruction analysis to include other IPS Stations around the Globe in a Worldwide Interplanetary Scintillation Stations (WIPSS) Network. In addition, we also plan to resurrect the Solar Mass Ejection Imager (SMEI) Thomson-scattering analysis as a basis for 3-D analysis to be used by the latest NASA Small Explorer heliospheric imagers of the Polarimeter to Unify the Corona and Heliosphere (PUNCH) mission, the All Sky Heliospheric Imager (ASHI), and other modern wide-field imagers. Better data require improved Heliospheric modeling that incorporates non-radial transport of heliospheric flows, and shock processes. Looking ahead to this, we have constructed an interface between the 3-D reconstruction tomography and 3-D MHD models, and currently include the ENLIL model as a kernel in the reconstructions to provide this fit. In short, we are now poised to provide all of these innovations in a next step: to include them for planned ground-based and spacecraft instruments, all to be combined into a truly global 3-D heliospheric system which utilizes these aspects in their data and modeling.