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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 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.