Background Solar Wind Research Articles

Icarus 3.0: Dynamic heliosphere modelling

Space weather predictions are necessary to avoid damage caused by intense geomagnetic storms. Such strong storms are usually caused by a co-rotating interaction region (CIR) passing at Earth or by the arrival of strong coronal mass ejections (CMEs). To mitigate the damage, the effect of propagating CMEs in the solar wind must be estimated accurately at Earth and other locations. Modelling solar wind accurately is crucial for space weather predictions, as it is the medium for CME propagation. The Icarus heliospheric modelling tool is upgraded to handle dynamic inner heliospheric driving instead of using steady boundary conditions. The ideal magnetohydrodynamic (MHD) solver and the automated grid-adaptivity are adjusted to the latest MPI-AMRVAC version. This new combination allows us to model the solar heliosphere more accurately. The inner boundary conditions, prescribed at 0.1 AU for the heliospheric model, are updated time-dependently throughout the simulation. The coronal model (r<0.1 AU) is computed repeatedly for selected magnetograms, and the r=0.1 AU radial boundary prescription is provided to the heliospheric modelling tool. The particle sampling within MPI-AMRVAC is extended to handle stretched spherical grid information. It is well suited for tracing solar wind plasma conditions at the locations of planets and satellites in the heliosphere. The solar wind obtained in the simulation is dynamic and shows significant variations throughout the evolution. When comparing the results with the observations, the dynamic solar wind results are more accurate than previous results obtained with purely steady boundary driving. The CMEs propagated through the dynamic solar wind background produce more similar signatures in the time-series data than in the steady solar wind. Dynamic boundary driving in Icarus results in a more self-consistent solar wind evolution in the inner heliosphere. The upgraded particle sampling allows for a very versatile sampling of the solution at the spatio-temporally varying locations of satellites. The obtained space weather modelling tool for dynamic solar wind and CME simulations is better suited for space weather forecasting than a steady solar wind model.

Constraining Solar Wind Transport Model Parameters Using Bayesian Analysis

Abstract We apply nested-sampling Bayesian analysis to a model for the transport of magnetohydrodynamic-scale solar wind fluctuations. The dual objectives are to obtain improved constraints on parameters present in the turbulence transport model (TTM) and to support quantitative comparisons of the quality of distinct versions of the transport model. The TTMs analyzed are essentially the 1D steady-state ones presented in Breech et al. that describe the radial evolution of the energy, correlation length, and normalized cross helicity of the fluctuations, together with the proton temperature, in prescribed background solar wind fields. Modeled effects present in the TTM include nonlinear turbulence interactions, shear driving, and energy injection associated with pickup-ions. Each of these modeled effects involves adjustable parameters that we seek to constrain using Bayesian analysis. We find that, given the TTMs and observational data sets analyzed, the most appropriate TTM to recommend corresponds to 2D fluctuations and has von Kármán–Howarth parameters of α ≈ 0.16 and β ≈ 0.10, along with reasonably standard values for the other adjustable parameters. The analysis also indicates that it is advantageous to include pickup ion effects in the lengthscale evolution equation by assuming Z 2β/α λ is locally conserved. Such Bayesian analysis is readily extended to more sophisticated solar wind models, space weather models, and might lead to improved predictions of, for example, solar flare and coronal mass ejection interactions with the Earth.

Decent Estimate of CME Arrival Time From a Data‐Assimilated Ensemble in the Alfvén Wave Solar Atmosphere Model (DECADE‐AWSoM)

AbstractForecasting 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.

Coronal mass ejection propagation in the dynamically coupled space weather tool: COCONUT + EUHFORIA

Numerical magnetohydrodynamics (MHD) models such as the European heliospheric forecasting information asset (EUHFORIA) have been developed to predict the arrival time of coronal mass ejections (CMEs) and accelerated high-energy particles. However, in EUHFORIA, transient magnetic structures are injected at 0.1 AU into a background solar wind created from a static solar wind model. This means the inserted CME model is completely independent of the coronal magnetic field and thus is missing all potential interactions between the CME and the solar wind in the corona. This paper aims to present the time-dependent coupling between the coronal model COolfluid COroNal UnsTructured (COCONUT) and the heliospheric forecasting tool EUHFORIA. This first attempt to couple these two simulations should allow us to follow directly the propagation of a flux rope from the Sun to Earth. We performed six COCONUT simulations where a flux rope is implemented at the solar surface using either the Titov-Démoulin CME model or the regularised Biot-Savart law (RBSL) CME model. At regular intervals, the magnetic field, velocity, temperature, and density of the 2D surface $R_ b odot $ were saved in boundary files. These series of coupling files were read in a modified version of EUHFORIA in order to progressively update its inner boundary. After presenting the early stage of the propagation in COCONUT, we examined how the disturbance of the solar corona created by the propagation of flux ropes is transmitted into EUHFORIA. In particular, we considered the thermodynamic and magnetic profiles at L1 and compared them with those obtained at the interface between the two models. We demonstrate that the properties of the heliospheric solar wind in EUHFORIA are consistent with those in COCONUT, acting as a direct extension of the coronal domain. Moreover, the disturbances initially created from the propagation of flux ropes in COCONUT continue to evolve from the corona in the heliosphere to Earth, with a smooth transition at the interface between the two simulations. Looking at the profile of magnetic field components at Earth and different distances from the Sun, we also find that the transient magnetic structures have a self-similar expansion in COCONUT and EUHFORIA. However, the amplitude of the profiles depends on the flux rope model used and its properties, thus emphasising the important role of the initial properties in solar source regions for accurately predicting the impact of CMEs. The dynamically coupled COCONUT plus EUHFORIA model chain constitutes a new space weather forecasting tool that can predict the characteristics of the flux-rope CMEs upon their arrival at L1.

Effects of Background Solar Wind and Drag Force on the Propagation of Coronal-mass-ejection-driven Shocks

The propagation of interplanetary shocks, particularly those driven by coronal mass ejections (CMEs), is still an outstanding question in heliophysics and space weather forecasting. Here, we address the effects of the ambient solar wind on the propagation of two similar CME-driven shocks from the Sun to Earth. The two shock events (CME03, 2010 April 3; CME12, 2012 July 12) have the following properties. Both events (1) were driven by a halo CME (i.e., the source location is near the Sun–Earth line); (2) had a CME source in the southern hemisphere; (3) had a similar transit time (∼2 days) to Earth; (4) occurred in a nonquiet solar period; and (5) led to a severe geomagnetic storm. The initial (near the Sun) propagation speed, as measured by coronagraph images, was slower (by ∼300 km s−1) for CME03 than CME12, but it took about the same amount of traveling time for both events to reach Earth. According to the in situ solar wind observations from the Wind spacecraft, the CME03-driven shock was associated with a faster solar wind upstream of the shock than the CME12-driven shock. This is also demonstrated in our global MHD simulations. Analysis of our simulation result indicates that the drag force indirectly plays an important role in the shock propagation. The present study suggests that in addition to the initial CME propagation speed near the Sun, the shock speed (in the inertial frame) and the ambient solar wind conditions—in particular, the solar wind speed—are key to timing the arrival of CME-driven shock events.

MHD Modeling of a Geoeffective Interplanetary Coronal Mass Ejection with the Magnetic Topology Informed by In Situ Observations

Variations of the magnetic field within a solar coronal mass ejection (CME) in the heliosphere depend on the CME’s magnetic structure as it leaves the solar corona and its interplanetary evolution. To account for this evolution, we developed a new numerical model of the inner heliosphere that simulates the propagation of a CME through a realistic solar wind background and allows various CME magnetic topologies. To this end, we incorporate the Gibson–Low CME model within our global MHD model of the inner heliosphere, GAMERA-Helio. We apply the model to study the propagation of the geoeffective CME that erupted on 2010 April 3, aiming to reproduce the temporal variations of the magnetic field vector during the CME’s passage by Earth. Parameters of the Gibson–Low CME are informed by STEREO white-light observations near the Sun. The magnetic topology for this CME—the tethered flux rope—is informed by in situ magnetic field observations near Earth. We performed two simulations testing different CME propagation directions. For an in-ecliptic direction, the simulation shows a rotation of all three magnetic field components within the CME, as seen at Earth, similar to that observed. However, the magnitudes of the components, particularly at the back of the CME, are underestimated by the model. With a southward direction, suggested by coronal imaging observations, the B x component lacks the observed change from negative to positive. In both cases, the model favors the east–west orientation of the flux rope, consistent with the orientation previously inferred from the images from STEREO/Heliospheric Imager.

CME Arrival Time Prediction Based on Coronagraph Observations and Machine-learning Techniques

The timely and precise prediction of the arrival time of coronal mass ejections (CMEs) is crucial in mitigating their potential adverse effects. In this study, we present a novel prediction method utilizing a deep-learning framework coupled with physical characteristics of CMEs and background solar wind. Time series images from synchronized solar white-light and EUV observations of 156 geoeffective CME events during 2000–2020 are collected for this study, according to the Richardson and Cane interplanetary CME directory and the SOHO/LASCO CME catalog of NASA/CDAW. The CME parameters are obtained from the CDAW website and the solar wind parameters are from OMNI2 website. The observational images are first fed into a convolutional neural network (CNN) to train a regression model as Model A. The results generated by the original CNN are then integrated with 11 selected physical parameters in additional neural network layers of Model B to improve the predictions. Under optimal configurations, Model A achieves a minimum mean absolute error (MAE) of 7.87 hr, whereas Model B yields a minimum MAE of 5.12 hr. During model training, we employed tenfold cross validation to reduce the occasionality of biased data. The average MAE of Model B on 10 folds is 33% lower than that of model A. The results demonstrate that combining the imaging observations with the physical properties of CMEs and background solar wind to train a machine-learning model can benefit the forecasting of CME arrival times.

Recurrent Coronal Mass Ejections and Their Geomagnetic Storms Association on 2012 January 19: Solar Surface to Upper Earth’s Atmosphere Analyses

In this study, we have conducted an analysis of space weather disruptions that occurred on 19 January 2012. Our analysis identified three coronal mass ejections (CMEs), CME1, CME2, and CME3—which were ejected at 09:48:05 universal time (UT), 14:36:05 UT, and 16:12:06 UT, respectively. Nonrecurrent disturbances in space weather, such as geomagnetic storms, result from CMEs originating from the Sun and traveling toward Earth. We assess the contribution of CME–CME interactions on 2012 January 19 and the volume emission rate of nitric oxide (NO) near the Earth's upper atmosphere in prolonging the geomagnetic disturbances observed on 2012 January 23. The findings suggest an increase in intensity at the interacting boundaries of CME1 and CME2, indicating an increase in pressure and density, leading to the compression of the magnetosphere. The 3D reconstructions of the CMEs provide evidence of unequal expansion and rotations within coronagraphic frames attributed to structural variability in the background solar wind during the eruptions. Furthermore, highlights from the in situ observations suggest that the impact of the recurrent CMEs on the geomagnetic disturbance was more pronounced within the auroral region synchronizing with a significant increase in NO volume emission rate on 2012 January 23, near the upper Earth's atmosphere. Our focus is on exploring the interactions between these CMEs to understand their potential contribution to the extended duration of the observed geomagnetic disturbance.

Kinematic Differences between Gradual and Impulsive Coronal Mass Ejections: The Role of Flares

Coronal Mass Ejections (CMEs) are significant solar events that involve intense explosions of magnetic fields and mass particles out from the corona. These events are known to be the main driver of space weather and other disturbances experienced by the Earth. Generally, there are two types of CMEs – gradual and impulsive, and each type has different properties which is important to be studied on as they have potential to cause breakdowns in our systems. This study is aimed to analyze and differentiate the kinematic behavior of gradual and impulsive CME with the association of weak and strong flares. Data collection is made through SOHO LASCO catalogues and STEREO database which include velocity, acceleration and angular width as well as images. At the end of this study, it can be deduced that impulsive CME (specifically associated with strong flare) is the most prominent event that has greatest angular width and average velocity. The associated flare has contributed more heat energy to speed up the magnetic energy conversion which results to high velocity of plasma discharge. Since fast CME carries huge amount of momentum during the ejection, impulsive CMEs also experience decelerations due to loss of momentum that has been transferred to background solar wind.

Flux Rope Modeling of the 2022 September 5 Coronal Mass Ejection Observed by Parker Solar Probe and Solar Orbiter from 0.07 to 0.69 au

As both Parker Solar Probe (PSP) and Solar Orbiter (SolO) reach heliocentric distances closer to the Sun, they present an exciting opportunity to study the structure of coronal mass ejections (CMEs) in the inner heliosphere. We present an analysis of the global flux rope structure of the 2022 September 5 CME event that impacted PSP at a heliocentric distance of only 0.07 au and SolO at 0.69 au. We compare in situ measurements at PSP and SolO to determine global and local expansion measures, finding a good agreement between magnetic field relationships with heliocentric distance, but significant differences with respect to flux rope size. We use PSP/Wide-Field Imager for Solar Probe images as input to the ELlipse Evolution model based on Heliospheric Imager data (or ELEvoHI), providing a direct link between remote and in situ observations; we find a large discrepancy between the resulting modeled arrival times, suggesting that the underlying model assumptions may not be suitable when using data obtained close to the Sun, where the drag regime is markedly different in comparison to larger heliocentric distances. Finally, we fit the SolO's magnetometer and PSP's FIELDS data independently with the 3D Coronal ROpe Ejection (or 3DCORE) model, and find that many parameters are consistent between spacecraft. However, challenges are apparent when reconstructing a global 3D structure that aligns with arrival times at PSP and SolO, likely due to the large radial and longitudinal separations between spacecraft. From our model results, it is clear the solar wind background speed and drag regime strongly affect the modeled expansion and propagation of CMEs and need to be taken into consideration.

Solar Wind With Field Lines and Energetic Particles (SOFIE) Model: Application to Historical Solar Energetic Particle Events

AbstractIn this paper, we demonstrate the applicability of the data‐driven solar energetic particle (SEP) model, SOlar‐wind with FIeld‐lines and Energetic‐particles (SOFIE), to simulate the acceleration and transport processes of SEPs and make forecast of the energetic proton flux at energies ≥10 MeV that will be observed near 1 AU. The SOFIE model is built upon the Space Weather Modeling Framework developed at the University of Michigan. In SOFIE, the background solar wind plasma in the solar corona and interplanetary space is calculated by the Stream‐Aligned Aflvén Wave Solar‐atmosphere Model(‐Realtime) driven by the near‐real‐time hourly updated Global Oscillation Network Group solar magnetograms. In the background solar wind, coronal mass ejections (CMEs) are launched by placing an force‐imbalanced magnetic flux rope on top of the parent active region, using the Eruptive Event Generator using Gibson‐Low model. The acceleration and transport processes are modeled by the Multiple‐Field‐Line Advection Model for Particle Acceleration. In this work, nine SEP events (Solar Heliospheric and INterplanetary Environment challenge/campaign events) are modeled. The three modules in SOFIE are validated and evaluated by comparing with observations, including the steady‐state background solar wind properties, the white‐light image of the CMEs, and the flux of solar energetic protons, at energies of ≥10 MeV.

Magnetohydrodynamic Modeling of Background Solar Wind near Mars: Comparison with MAVEN and Tianwen-1

Combined with data assimilation methods, a three-dimensional magnetohydrodynamic (MHD) numerical model is an effective tool to explore the mechanism of space weather. As a driver of space weather, the dynamic development of stream interaction regions (SIRs) near the orbit of Mars is an area of active research. In this study, we use the interplanetary total variation diminishing (TVD) MHD model to simulate solar wind parameters and model SIRs near Mars from 2021 November 15 to 2021 December 31. In this model, the MHD equations are solved by the conservation TVD Lax–Friedrichs scheme in a rotating spherical coordinate system with six component meshes used on the spherical shell. Solar wind velocity, density, temperature, and magnetic field strength are given at the inner boundary due to the characteristic waves propagating outward. We compared modeled results with observations from Mars Atmospheric Volatile EvolutioN (MAVEN) and Tianwen-1 (China’s first Mars exploration mission). Statistical analysis shows that the simulated results can capture SIRs and are in good agreement with observations; moreover, the assimilated results based on the Kalman filter improve the accuracy of numerical prediction compared with simulated results. This paper is the first attempt to simulate SIR events combined with MAVEN and Tianwen-1 in situ observations. Our work demonstrates that using the MHD model with the Kalman filter to reconstruct solar wind parameters can help us study the characteristics of SIRs near Mars, improve the capabilities of space weather forecasting, and understand the background solar wind environment.

Updating Measures of CME Arrival Time Errors

AbstractCoronal mass ejections (CMEs) drive space weather effects at Earth and the heliosphere. Predicting their arrival is a major part of space weather forecasting. In 2013, the Community Coordinated Modeling Center started collecting predictions from the community, developing an Arrival Time Scoreboard (ATSB). Riley et al. (2018, https://doi.org/10.1029/2018sw001962) analyzed the first 5 years of the ATSB, finding a bias of a few hours and uncertainty of order 15 hr. These metrics have been routinely quoted since 2018, but have not been updated despite continued predictions. We revise analysis of the ATSB using a sample 3.5 times the size of that in the original study. We find generally the same overall metrics, a bias of −2.5 hr, mean absolute error of 13.2 hr, and standard deviation of 17.4 hr, with only a slight improvement comparing between the previously‐used and new sets. The most well‐established, frequently‐submitted model results tend to outperform those from seldomly‐contributed models. These “best” models show a slight improvement over the 11 year span, with more scatter between the models during early times and a convergence toward the same error metrics in recent years. We find little evidence of any correlations between the arrival time errors and any other properties. The one noticeable exception is a tendency for late predictions for short transit times and vice versa. We propose that any model‐driven systematic errors may be washed out by the uncertainties in CME reconstructions in characterization of the background solar wind, and suggest that improving these may be the key to better predictions.

The Opposite Behaviors of Proton and Electron Temperatures in Relation to Solar Wind Magnetic Energy: Parker Solar Probe Observations

Solar wind heating is an outstanding issue that has been discussed for decades. Research on the connection between solar wind particle temperatures and turbulence may provide insight into this issue. Based on Parker Solar Probe observations, this paper investigates the properties of solar wind proton and electron temperatures in relation to turbulent magnetic energy, via the calculation of correlation coefficients (CCs) between particle temperatures and magnetic energy. The calculations are regulated by the spatial scale, plasma beta (β), and the angle between the solar wind velocity and background magnetic field, where the plasma beta is the ratio of plasma thermal to magnetic pressure. Results show that the correlation between proton temperature and magnetic energy is positive and can be strong with a CC exceeding 0.8. The strong correlation preferentially occurs at ion scales, with the wind velocity and background magnetic field quasi-perpendicular and over a wide beta range (β < 3.0). On the other hand, the correlation between electron temperature and magnetic energy is commonly negative, often with an intermediate or negligible CC, accordingly. The CC with an amplitude up to 0.8 can arise at larger scales with the wind velocity and background magnetic field quasi-(anti)parallel and in the low-beta case (β < 0.6). The implication of these findings on the physics of turbulent heating in the solar wind is discussed.

A Coronal Mass Ejection Impacting Parker Solar Probe at 14 Solar Radii

The relationship between CME properties in the corona and their interplanetary counterparts is not well understood. Until recently, a wide spatial gap existed between the two regions, which prevented us from disentangling the spatial and temporal evolution of CMEs. NASA’s Parker Solar Probe (PSP) has imaged multiple CMEs since its launch in 2018, but these events either intercepted the spacecraft far from the corona or completely missed it. Here we describe one of the first CMEs observed simultaneously by remote sensing and in situ instruments, and compare the corresponding measured properties, such as orientation, cross section diameter, density, and speed. The CME encounter occurred on 2022 June 2, while PSP was around 14 solar radii from the Sun center. We reconstruct the CME with forward modeling and determine its morphology and kinematics. The reconstruction suggests that PSP misses the CME apex but encounters its flank. The encounter time matches the period when the PSP in situ measurements indicate the passage of a CME. We also reconstruct the flux rope diameter and orientation using the in situ magnetic field measurements. The results are consistent with the CME reconstruction from imaging data. The close agreement between remote sensing and in situ analyses suggests that discrepancies found in past studies are more likely associated with the CME temporal evolution. We also find that the magnetic field of the CME flank extrapolated to 1 au is well below the average solar wind background and likely indistinguishable from it. This point could explain past events where the CMEs' interplanetary counterparts were not identified.

EUHFORIA modelling of the Sun-Earth chain of the magnetic cloud of 28 June 2013

Context. Predicting geomagnetic events starts with an understanding of the Sun-Earth chain phenomena in which (interplanetary) coronal mass ejections (CMEs) play an important role in bringing about intense geomagnetic storms. It is not always straightforward to determine the solar source of an interplanetary coronal mass ejection (ICME) detected at 1 au. Aims. The aim of this study is to test by a magnetohydrodynamic (MHD) simulation the chain of a series of CME events detected from L1 back to the Sun in order to determine the relationship between remote and in situ CMEs. Methods. We analysed both remote-sensing observations and in situ measurements of a well-defined magnetic cloud (MC) detected at L1 occurring on 28 June 2013. The MHD modelling is provided by the 3D MHD European Heliospheric FORecasting Information Asset (EUHFORIA) simulation model. Results. After computing the background solar wind, we tested the trajectories of six CMEs occurring in a time window of five days before a well-defined MC at L1 that may act as the candidate of the MC. We modelled each CME using the cone model. The test involving all the CMEs indicated that the main driver of the well-defined, long-duration MC was a slow CME. For the corresponding MC, we retrieved the arrival time and the observed proton density. Conclusions. EUHFORIA confirms the results obtained in the George Mason data catalogue concerning this chain of events. However, their proposed solar source of the CME is disputable. The slow CME at the origin of the MC could have its solar source in a small, emerging region at the border of a filament channel at latitude and longitude equal to +14 degrees.

Numerical MHD models of stream interaction regions (SIRs) and corotating interaction regions (CIRs) using sunRunner3D: comparison with observations

ABSTRACT In this work, we present numerical simulations of Stream Interaction Regions (SIRs) and Corotating Interaction Regions (CIRs) using the sunrunner3d tool that employs as a coronal model the boundary conditions obtained by corhel/mas with the pluto code that describes the global 3D structure of the solar wind using the magnetohydrodynamics (MHD) approach in the inner heliosphere. Specifically, we selected a set of SIRs and CIRs observed by the Parker Solar Probe (PSP) and STEREO-A (STA) missions during the Carrington rotations (CRs) 2207 to 2210 and CRs from 2020 to 2022. In order to describe the dynamics of the plasma that constitutes the solar wind background conditions for the selected CRs, we solve the ideal MHD equations in an inertial frame of reference, managing the solar rotation by rotating the boundary values in ϕ (longitude) at a rate corresponding to the sidereal rotation rate of the solar equator. We show that our results using sunrunner3d can globally reproduce the plasma parameters, such as radial velocity, number proton density, and radial magnetic field strength of these large-scale structures, observed by PSP and STA at distances near the Sun and around 1 au, respectively. These results allow exploring the global evolution of SIRs/CIRs in the inner heliosphere using sunrunner3d.

MHD modelling of coronal streamers and their oscillations

Context. The present work investigates solar coronal dynamics in particular streamer waves. Streamer waves are transverse oscillations of the streamer stalk, often generated by the passage of a coronal mass ejection (CME). Recent observational studies infer that the streamer wave is an eigenmode of the streamer plasma slab and an excellent candidate for coronal seismology. Aims. In the present work, we aim to numerically investigate the theoretical concepts of the physics and properties of streamer waves and to complement the observational statistical analysis of these events. Methods. We used the magnetohydrodynamics (MHD) module of MPI-AMRVAC. An adaptive mesh refinement scheme was employed to achieve high resolution for the streamer structure. All the simulations were computed on the same base grid with the same numerical methods. We considered a dipole magnetic field on the Sun and a uniformly accelerating solar wind. We introduced a θ-velocity perturbation within our computational domain in the plane of a streamer to excite the transverse motion. Results. A numerical model for the streamer wave phenomena was constructed in the framework of 2.5D MHD. We performed a parameter study and identified a sensitivity of the streamer dynamics to the background solar wind speed, the characteristics of the perturbation, and the input parameters for the model, such as temperature and magnetic field. We performed a statistical analysis and compared the obtained modelling results with the database of such events from observations from three different coronagraphs. We observed a narrow range of phase speeds and a correlation between wavelength and period. This is consistent with the observations and supports the idea that the streamer wave is an eigenmode of the streamer plasma slab. The measured phase speed is consistently significantly higher than the speed calculated from the measured period and wavelength. The simple fit, when the difference between these two speeds is exactly the background solar wind speed, only matches a small fraction of the data. The obtained results indicate that further investigation is required into the Doppler shift effect in the MHD theory for coronal seismology.

Refined Modeling of Geoeffective Fast Halo CMEs During Solar Cycle 24

AbstractThe propagation of geoeffective fast halo coronal mass ejections (CMEs) from solar cycle 24 has been investigated using the European Heliospheric Forecasting Information Asset (EUHFORIA), ENLIL, Drag‐Based Model (DBM) and Effective Acceleration Model (EAM) models. For an objective comparison, a unified set of a small sample of CME events with similar characteristics has been selected. The same CME kinematic parameters have been used as input in the propagation models to compare their predicted arrival times and the speed of the interplanetary (IP) shocks associated with the CMEs. The performance assessment has been based on the application of an identical set of metrics. First, the modeling of the events has been done with default input concerning the background solar wind, as would be used in operations. The obtained CME arrival forecast deviates from the observations at L1, with a general underestimation of the arrival time and overestimation of the impact speed (mean absolute error [MAE]: 9.8 ± 1.8–14.6 ± 2.3 hr and 178 ± 22–376 ± 54 km/s). To address this discrepancy, we refine the models by simple changes of the density ratio (dcld) between the CME and IP space in the numerical, and the IP drag (γ) in the analytical models. This approach resulted in a reduced MAE in the forecast for the arrival time of 8.6 ± 2.2–13.5 ± 2.2 hr and the impact speed of 51 ± 6–243 ± 45 km/s. In addition, we performed multi‐CME runs to simulate potential interactions. This leads, to even larger uncertainties in the forecast. Based on this study we suggest simple adjustments in the operational settings for improving the forecast of fast halo CMEs.

A Numerical Study of the Effects of a Corotating Interaction Region on Cosmic-Ray Transport. II. Features of Cosmic-Ray Composition and Rigidity

We continue the numerical modeling of a corotating interaction region (CIR) and the effects it has on solar-rotational recurrent variations of galactic cosmic rays (GCRs). A magnetohydrodynamic model is adapted to simulate the background solar wind plasma with a CIR structure in the inner heliosphere, which is incorporated into a comprehensive Parker-type transport model. The focus is on the simulation of the effects of a CIR on GCR protons and the two helium isotopes as a function of heliolongitude. This is to establish whether the difference in composition affects how they are modulated by the CIR in terms of their distribution in longitude. It is demonstrated that particle diffusion and drift influence the effects of the CIR with increasing rigidity from 100 MV up to 15 GV. It is found that protons and helium isotopes are modulated differently with longitude by the CIR and that particle drift influences the modulation effects in longitude. These differences dissipate with increasing rigidity. The final results are focused on the simulated amplitude of these GCR flux variations as a function of rigidity. The amplitude displays a power-law behavior above ∼1 GV with an index similar to the power index of the rigidity dependence of the assumed diffusion coefficients. The simulations further show that below this rigidity, the amplitude at first flattens off, displaying a plateau-like profile, but it then increases systematically with decreasing rigidity below ∼0.3 GV. Again, a power-law behavior is displayed, but it is completely different from that above 1 GV.