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Drawing connections between heliospheric spacecraft and solar wind sources is a vital step in understanding the evolution of the solar corona into the solar wind and contextualizing \textit{in situ} timeseries. Furthermore, making advanced predictions of this linkage for ongoing heliospheric missions, such as Parker Solar Probe (PSP), is necessary for achieving useful coordinated remote observations and maximizing scientific return. The general procedure for estimating such connectivity is straightforward (i.e. magnetic field line tracing in a coronal model) but validating the resulting estimates difficult due to the lack of an independent ground truth and limited model constraints. In its most recent orbits, PSP has reached perihelia of 13.3$R_\odot$ and moreover travels extremely fast prograde relative to the solar surface, covering over 120 degrees longitude in three days. Here we present footpoint predictions and subsequent validation efforts for PSP Encounter 10, the first of the 13.3$R_\odot$ orbits, which occurred in November 2021. We show that the longitudinal dependence of \textit{in situ} plasma data from these novel orbits provides a powerful method of footpoint validation. With reference to other encounters, we also illustrate that the conditions under which source mapping is most accurate for near-ecliptic spacecraft (such as PSP) occur when solar activity is low, but also requires that the heliospheric current sheet is strongly warped by mid-latitude or equatorial coronal holes. Lastly, we comment on the large-scale coronal structure implied by the Encounter 10 mapping, highlighting an empirical equatorial cut of the Alfv\`{e}n surface consisting of localized protrusions above unipolar magnetic separatrices., Comment: 33 Pages, 7 Figures, JGR Space Physics, Published Online 2023/3/28, In Final Production

The arrival time prediction of Coronal mass ejections (CMEs) is an area of active research. Many methods with varying levels of complexity have been developed to predict CME arrival. However, the mean absolute error (MAE) of predictions remains above 12 hours, even with the increasing complexity of methods. In this work we develop a new method for CME arrival time prediction that uses magnetohydrodynamic simulations involving data-constrained flux-rope-based CMEs, which are introduced in a data-driven solar wind background. We found that, for 6 CMEs studied in this work, the MAE in arrival time was ~8 hours. We further improved our arrival time predictions by using ensemble modeling and comparing the ensemble solutions with STEREO-A&B heliospheric imager data. This was done by using our simulations to create synthetic J-maps. A machine learning (ML) method called the lasso regression was used for this comparison. Using this approach, we could reduce the MAE to ~4 hours. Another ML method based on the neural networks (NNs) made it possible to reduce the MAE to ~5 hours for the cases when HI data from both STEREO-A&B were available. NNs are capable of providing similar MAE when only the STEREO-A data is used. Our methods also resulted in very encouraging values of standard deviation (precision) of arrival time. The methods discussed in this paper demonstrate significant improvements in the CME arrival time predictions. Our work highlights the importance of using ML techniques in combination with data-constrained magnetohydrodynamic modeling to improve space weather predictions.

The solar wind (SW) and local interstellar medium (LISM) are turbulent media. Their interaction is governed by complex physical processes and creates heliospheric regions with significantly different properties in terms of particle populations, bulk flow and turbulence. Our knowledge of the solar wind turbulence \nature and dynamics mostly relies on near-Earth and near-Sun observations, and has been increasingly improving in recent years due to the availability of a wealth of space missions, including multi-spacecraft missions. In contrast, the properties of turbulence in the outer heliosphere are still not completely understood. In situ observations by Voyager and New Horizons, and remote neutral atom measurements by IBEX strongly suggest that turbulence is one of the critical processes acting at the heliospheric interface. It is intimately connected to charge exchange processes responsible for the production of suprathermal ions and energetic neutral atoms. This paper reviews the observational evidence of turbulence in the distant SW and in the LISM, advances in modeling efforts, and open challenges., Comment: 82 pages, 31 figures. Paper accepted by Space Science Reviews (collection: The Heliosphere in the Local Interstellar Medium: Into the Unknown), and presented at the ISSI Workshop on November 8-12, 2021

Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for the prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 12-July-2012 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in post-eruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hour. We further estimate the average subjective uncertainties in the GCS fittings, by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5.74 degrees, 11.23 degrees, 24.71 degrees, and 11.4% respectively. Using these, we have created 77 ensemble members for the 12-July-2012 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hours for the 12-July-2012 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 12-July-2012 CME, whereas the uncertainties in longitude and tilt can introduce a relatively large spread in the magnetic field predicted at Earth.

The magnetic fields of interplanetary coronal mass ejections (ICMEs), which originate close to the Sun in the form of a flux rope, determine their geoeffectiveness. Therefore, robust flux rope-based models of CMEs are required to perform magnetohydrodynamic (MHD) simulations aimed at space weather predictions. We propose a modified spheromak model and demonstrate its applicability to CME simulations. In this model, such properties of a simulated CME as the poloidal and toroidal magnetic fluxes, and the helicity sign can be controlled with a set of input parameters. We propose a robust technique for introducing CMEs with an appropriate speed into a background, MHD solution describing the solar wind in the inner heliosphere. Through a parametric study, we find that the speed of a CME is much more dependent on its poloidal flux than on the toroidal flux. We also show that the CME speed increases with its total energy, giving us control over its initial speed. We further demonstrate the applicability of this model to simulations of CME-CME collisions. Finally, we use this model to simulate the 12 July 2012 CME and compare the plasma properties at 1 AU with observations. The predicted CME properties agree reasonably with observational data.

The magnetometer (MAG) on Voyager 1 (V1) has been sampling the interstellar magnetic field (ISMF) since August 2012. The V1 MAG observations have shown draped ISMF in the very local interstellar medium disturbed occasionally by significant enhancements in magnetic field strength. Using a three-dimensional, data driven, multi-fluid model, we investigated these magnetic field enhancements beyond the heliopause that are supposedly associated with solar transients. To introduce time-dependent effects at the inner boundary at 1 astronomical unit, we used daily averages of the solar wind parameters from the OMNI data set. The model ISMF strength, direction, and proton number density are compared with V1 data beyond the heliopause. The model reproduced the large-scale fluctuations between 2012.652 and 2016.652, including major events around 2012.9 and 2014.6. The model also predicts shocks arriving at V1 around 2017.395 and 2019.502. Another model driven by OMNI data with interplanetary coronal mass ejections (ICMEs) removed at the inner boundary suggests that ICMEs may play a significant role in the propagation of shocks into the interstellar medium., Comment: Accepted by Astrophysical Journal Letters on 06/21/2017