Search for: All records

Abstract Magnetic switchbacks are rapid high-amplitude reversals of the radial magnetic field in the solar wind that do not involve a heliospheric current sheet crossing. First seen sporadically in the 1970s in Mariner and Helios data, switchbacks were later observed by the Ulysses spacecraft beyond 1 au and have been recently discovered to be a typical component of solar wind fluctuations in the inner heliosphere by the Parker Solar Probe spacecraft. While switchbacks are now well understood to be spherically polarized Alfvén waves thanks to Parker Solar Probe observations, their formation has been an intriguing and unsolved puzzle. Here we provide a simple yet predictive theory for the formation of these magnetic reversals: the switchbacks are produced by the distortion and twisting of circularly polarized Alfvén waves by a transversely varying radial wave propagation velocity. We provide an analytic expression for the magnetic field variation, establish the necessary and sufficient conditions for the formation of switchbacks, and show that the proposed mechanism works in a realistic solar wind scenario. We also show that the theoretical predictions are in excellent agreement with observations, and the high-amplitude radial oscillations are strongly correlated with the shear of the wave propagation speed. The correlation coefficient is around 0.3–0.5 for both encounter 1 and encounter 12. The probability of this being a lucky coincidence is essentially zero withp-values below 0.1%. 

Abstract Parker Solar Probe observations reveal that the near-Sun space is almost filled with magnetic switchbacks (“switchbacks” hereinafter), which may be a major contributor to the heating and acceleration of solar wind. Here, for the first time, we develop an analytic model of an axisymmetric switchback with uniform magnetic field strength. In this model, three parameters control the geometry of the switchback: height (length along the background magnetic field), width (thickness along radial direction perpendicular to the background field), and the radial distance from the center of switchback to the central axis, which is a proxy of the size of the switchback along the third dimension. We carry out 3D magnetohydrodynamic simulations to investigate the dynamic evolution of the switchback. Comparing simulations conducted with compressible and incompressible codes, we verify that compressibility, i.e., parametric decay instability, is necessary for destabilizing the switchback. Our simulations also reveal that the geometry of the switchback significantly affects how fast the switchback destabilizes. The most stable switchbacks are 2D-like (planar) structures with large aspect ratios (length to width), consistent with the observations. We show that when plasma beta (β) is smaller than one, the switchback is more stable asβincreases. However, whenβis greater than 1, the switchback becomes very unstable as the pattern of the growing compressive fluctuations changes. Our results may explain some of the observational features of switchbacks, including the large aspect ratios and nearly constant occurrence rates in the inner heliosphere. 

Abstract Mercury possesses a miniature but dynamic magnetosphere driven primarily by the solar wind through magnetic reconnection. A prominent feature of the dayside magnetopause reconnection that has been frequently observed is flux transfer events (FTEs), which are thought to be an important player in driving the global convection at Mercury. Using the BATSRUS Hall magnetohydrodynamics model with coupled planetary interior, we have conducted a series of global simulations to investigate the generation and characteristics of FTEs under different solar wind Alfvénic Mach numbers (M_A) and interplanetary magnetic field (IMF) orientations. An automated algorithm was also developed to consistently identify FTEs and extract their key properties from the simulations. In all simulations driven by steady upstream conditions, FTEs are formed quasi‐periodically with recurrence time ranging from 2 to 9 s, and their characteristics vary in time as they evolve and interact with the surrounding plasma and magnetic field. Our statistical analysis of the simulated FTEs reveals that the key properties of FTEs, including spatial size, traveling speed and core field strength, all exhibit notable dependence on the solar windM_Aand IMF orientation, and the trends identified from the simulations are generally consistent with previous MErcury Surface Space ENvironment, GEochemistry, and Ranging observations. It is also found that FTEs formed in the simulations contribute about 3%–13% of the total open flux created at the dayside magnetopause that participates in the global circulation, suggesting that FTEs indeed play an important role in driving the Dungey cycle at Mercury. 

We present results of 131 geomagnetic storm simulations using the University of Michigan Space Weather Modeling Framework Geospace configuration. We compare the geomagnetic indices derived from the simulation with those observed, and use 2D cuts in the noon-midnight planes to compare the magnetopause locations with empirical models. We identify the location of the current sheet center and look at the plasma parameters to deduce tail dynamics. We show that the simulation produces geomagnetic index distributions similar to those observed, and that their relationship to the solar wind driver is similar to that observed. While the magnitudes of the Dst and polar cap potentials are close to those observed, the simulated AL index is consistently underestimated. Analysis of the magnetopause position reveals that the subsolar position agrees well with an empirical model, but that the tail flaring in the simulation is much smaller than that in the empirical model. The magnetotail and ring currents are closely correlated with the Dst index, and reveal a strong contribution of the tail current beyond 8 R E to the Dst index during the storm main phase. 

Collisionless magnetic reconnection typically requires kinetic treatment that is, in general, computationally expensive compared to fluid-based models. In this study, we use the magnetohydrodynamics with an adaptively embedded particle-in-cell (MHD-AEPIC) model to study the interaction of two magnetic flux ropes. This innovative model embeds one or more adaptive PIC regions into a global MHD simulation domain such that the kinetic treatment is only applied in regions where the kinetic physics is prominent. We compare the simulation results among three cases: (1) MHD with adaptively embedded PIC regions, (2) MHD with statically (or fixed) embedded PIC regions, and (3) a full PIC simulation. The comparison yields good agreement when analyzing their reconnection rates and magnetic island separations as well as the ion pressure tensor elements and ion agyrotropy. In order to reach good agreement among the three cases, large adaptive PIC regions are needed within the MHD domain, which indicates that the magnetic island coalescence problem is highly kinetic in nature, where the coupling between the macro-scale MHD and micro-scale kinetic physics is important. 

Abstract Forecasting the arrival time of Earth‐directed coronal mass ejections (CMEs) via physics‐based simulations is an essential but challenging task in space weather research due to the complexity of the underlying physics and limited remote and in situ observations of these events. Data assimilation techniques can assist in constraining free model parameters and reduce the uncertainty in subsequent model predictions. In this study, we show that CME simulations conducted with the Space Weather Modeling Framework (SWMF) can be assimilated with SOHO LASCO white‐light (WL) observations and solar wind observations at L1 prior to the CME eruption to improve the prediction of CME arrival time. The L1 observations are used to constrain the model of the solar wind background into which the CME is launched. Average speed of CME shock front over propagation angles are extracted from both synthetic WL images from the Alfvén Wave Solar atmosphere Model (AWSoM) and the WL observations. We observe a strong rank correlation between the average WL speed and CME arrival time, with the Spearman's rank correlation coefficients larger than 0.90 for three events occurring during different phases of the solar cycle. This enables us to develop a Bayesian framework to filter ensemble simulations using WL observations, which is found to reduce the mean absolute error of CME arrival time prediction from about 13.4 to 5.1 hr. The results show the potential of assimilating readily available L1 and WL observations within hours of the CME eruption to construct optimal ensembles of Sun‐to‐Earth CME simulations. 

Abstract We explore the performance of the Alfvén Wave Solar atmosphere Model with near-real-time (NRT) synoptic maps of the photospheric vector magnetic field. These maps, produced by assimilating data from the Helioseismic Magnetic Imager (HMI) on board the Solar Dynamics Observatory, use a different method developed at the National Solar Observatory (NSO) to provide a near contemporaneous source of data to drive numerical models. Here, we apply these NSO-HMI-NRT maps to simulate three full Carrington rotations: 2107.69 (centered on the 2011 March 7 20:12 CME event), 2123.5 (centered on 2012 May 11), and 2219.12 (centered on the 2019 July 2 solar eclipse), which together cover various activity levels for solar cycle 24. We show the simulation results, which reproduce both extreme ultraviolet emission from the low corona while simultaneously matching in situ observations at 1 au as well as quantify the total unsigned open magnetic flux from these maps.