Properties Of Coronal Mass Ejections Research Articles

Correlation of Coronal Mass Ejection Shock Temperature with Solar Energetic Particle Intensity

Solar energetic particle (SEP) events have been observed by the Parker Solar Probe (PSP) spacecraft since its launch in 2018. These events include sources from solar flares and coronal mass ejections (CMEs). The IS⊙IS instrument suite on board PSP is measuring ions over energies from ∼ 20 keV nucleon−1 to 200 MeV nucleon−1 and electrons from ∼ 20 keV to 6 MeV. Previous studies sought to group CME characteristics based on their plasma conditions and arrived at general descriptions with large statistical errors, leaving open questions on how to properly group CMEs based solely on their plasma conditions. To help resolve these open questions, the plasma properties of CMEs have been examined in relation to SEPs. Here, we reexamine one plasma property, the solar wind proton temperature, and compare it to the proton SEP intensity in a region immediately downstream of a CME-driven shock for seven CMEs observed at radial distances within 1 au. We find a statistically strong correlation between proton SEP intensity and bulk proton temperature, indicating a clear relationship between SEPs and the conditions in the solar wind. Furthermore, we propose that an indirect coupling of SEP intensity to the level of turbulence and the amount of energy dissipation that results is mainly responsible for the observed correlation between SEP intensity and proton temperature. These results are key to understanding the interaction of SEPs with the bulk solar wind in CME-driven shocks and will improve our ability to model the interplay of shock evolution and particle acceleration.

Eruptive events with exceptionally bright emission in H I Ly-α observed by the Metis coronagraph

Context. Ultraviolet (UV) emission from coronal mass ejections can provide information on the evolution of plasma dynamics, temperature, and elemental composition, as demonstrated by the UV Coronagraph Spectrometer (UVCS) on board the SOlar and Heliospheric Observatory (SOHO). Metis, the coronagraph on board Solar Orbiter, provides for the first time coronagraphic imaging in the UV H I Ly-α line and, simultaneously, in polarized visible light, thus providing a host of information on the properties of coronal mass ejections and solar eruptions such as their overall dynamics, time evolution, mass content, and outflow propagation velocity in the expanding corona. Aims. For this work, we analyzed six coronal mass ejections observed by Metis between April and October 2021, which are characterized by a very strong H I Ly-α emission. We studied in particular the morphology, kinematics, and the temporal and radial evolution of the emission of such events, focusing on the brightest UV features. Methods. The kinematics of the eruptive events under consideration were studied by determining the height-time profiles of the brightest parts on the Metis plane of the sky. Furthermore, the 3D positions in the heliosphere of the coronal mass ejections were determined by employing co-temporal images, when available, from two other coronagraphs: LASCO/C2 on board SOHO, and COR2 on board STEREO-A. In three cases, the most likely source region on the solar surface could be identified. Finally, the radiometrically calibrated Metis images of the bright UV features were analyzed to provide estimates of their volume and density. From the kinematics and radiometric analysis, we obtained indications of the temperatures of the bright UV cores of these events. These results were then compared with previous studies with the UVCS spectrocoronagraph. Results. The analysis of these strong UV-emitting features associated with coronal mass ejections demonstrates the capabilities of the current constellation of space coronagraphs, Metis, LASCO/C2, and COR2, in providing a complete characterization of the structure and dynamics of eruptive events in their propagation phase from their inception up to several solar radii. Furthermore, we show how the unique capabilities of the Metis instrument to observe these events in both the H I Ly-α line and polarized VL radiation allow plasma diagnostics on the thermal state of these events.

Correcting Projection Effects in CMEs Using GCS‐Based Large Statistics of Multi‐Viewpoint Observations

AbstractThis study addresses the limitations of single‐viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the Graduated Cylindrical Shell (GCS) model. The data set combines 326 previously analyzed CMEs and 34 newly examined events, categorized by their source regions into active region (AR) eruptions, active prominence (AP) eruptions, and prominence eruptions (PE). Estimates of errors are made using a bootstrapping approach. The findings highlight that the average 3D speed of CMEs is ∼1.3 times greater than the 2D speed. PE CMEs tend to be slow, with an average speed of 432 km s−1. AR and AP speeds are higher, at 723 and 813 km s−1, respectively, with the latter having fewer slow CMEs. The distinctive behavior of AP CMEs is attributed to factors like overlying magnetic field distribution or geometric complexities leading to less accurate GCS fits. A linear fit of projected speed to width gives a gradient of ∼2 km s−1 deg−1, which increases to 5 km s−1 deg−1 when the GCS‐fitted ‘true’ parameters are used. Notably, AR CMEs exhibit a high gradient of 7 km s−1 deg−1, while AP CMEs show a gradient of 4 km s−1 deg−1. PE CMEs, however, lack a significant speed‐width relationship. We show that fitting multi‐viewpoint CME images to a geometrical model such as GCS is important to study the statistical properties of CMEs, and can lead to a deeper insight into CME behavior that is essential for improving future space weather forecasting.

Discrepancies in the Properties of a Coronal Mass Ejection on Scales of 0.03 au as Revealed by Simultaneous Measurements at Solar Orbiter and Wind: The 2021 November 3–5 Event

Simultaneous in situ measurements of coronal mass ejections (CMEs), including both plasma and magnetic field, by two spacecraft in radial alignment have been extremely rare. Here, we report on one such CME measured by Solar Orbiter (SolO) and Wind on 2021 November 3–5, while the spacecraft were radially separated by a heliocentric distance of 0.13 au and angularly by only 2.2°. We focus on the magnetic cloud (MC) part of the CME. We find notable changes in the R and N magnetic field components and in the speed profiles inside the MC between SolO and Wind. We observe a greater speed at the spacecraft farther away from the Sun without any clear compression signatures. Since the spacecraft are close to each other and computing fast magnetosonic wave speed inside the MC, we rule out temporal evolution as the reason for the observed differences, suggesting that spatial variations over 2.2° of the MC structure are at the heart of the observed discrepancies. Moreover, using shock properties at SolO, we forecast an arrival time 2 hr 30 minutes too late for a shock that is just 5 hr 31 minutes away from Wind. Predicting the north–south component of the magnetic field at Wind from SolO measurements leads to a relative error of 55%. These results show that even angular separations as low as 2.2° (or 0.03 au in arc length) between spacecraft can have a large impact on the observed CME properties, which raises the issue of the resolutions of current CME models, potentially affecting our forecasting capabilities.

A catalogue of observed geo-effective CME/ICME characteristics

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such as Coronal Mass Ejections (CMEs), to improve our ability to forecast their propagation characteristics and mitigate the risks to our technologically driven society. The essential part of achieving this goal is to assess the performance of forecasting models. To this end, the quality and availability of suitable data are of paramount importance. In this work, we merged publicly available data of CMEs from both in-situ and remote observations in order to build a dataset of CME properties. To evaluate the accuracy of the dataset and confirm the relationship between in-situ and remote observations, we have employed the Drag-Based Model (DBM) due to its simplicity and modest consumption of computational resources. In this study, we have also explored the parameter space for the drag parameter and solar wind speed using a Monte Carlo approach to evaluate how efficiently the DBM determines the propagation of CMEs for the events in the dataset. The geoeffective CMEs selected as a result of this work are compliant with the hypothesis of DBM (isolated CME, constant solar wind speed beyond 20 R⊙) and also yield further insight into CME features such as arrival time and arrival speed at L1 point, lift-off time, speed at 20 R⊙ and other similar quantities. Our analysis based on the acceptance rate in the DBM inversion procedure shows that almost 50% of the CME events in the dataset are well described by DBM as they propagate in the heliosphere. The dataset includes statistical metrics for the DBM model parameters. The probability distribution functions (PDFs) for the free parameters of DBM have been derived through a Monte Carlo-like inversion procedure. Probability distribution functions obtained from this work are comparable to PDFs employed in previous works. The analysis showed that there exist two different most probable values (median values) of solar wind speed for DBM input based on slow (wslow ≈ 386 km/s) and fast (wfast ≈ 547 km/s) solar wind type. The most probable value for the drag parameter (γ ≈ 0.687 × 10−7 km−1) in our study is somewhat higher than the values reported in previous studies. Using a data-driven approach, this procedure allows us to present a homogeneous, reliable, and robust dataset for the investigation of CME propagation. Additionally, possible CME events are identified where the DBM prediction is not valid due to model limitations and higher uncertainties in the input parameters. These events require further thorough investigation in the future.

Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Models

Coronal mass ejections (CMEs) are massive solar eruptions, which have a significant impact on Earth. In this paper, we propose a new method, called DeepCME, to estimate two properties of CMEs, namely, CME mass and kinetic energy. Being able to estimate these properties helps better understand CME dynamics. Our study is based on the CME catalog maintained at the Coordinated Data Analysis Workshops Data Center, which contains all CMEs manually identified since 1996 using the Large Angle and Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory. We use LASCO C2 data in the period between 1996 January and 2020 December to train, validate, and test DeepCME through 10-fold cross validation. The DeepCME method is a fusion of three deep-learning models, namely ResNet, InceptionNet, and InceptionResNet. Our fusion model extracts features from LASCO C2 images, effectively combining the learning capabilities of the three component models to jointly estimate the mass and kinetic energy of CMEs. Experimental results show that the fusion model yields a mean relative error (MRE) of 0.013 (0.009, respectively) compared to the MRE of 0.019 (0.017, respectively) of the best component model InceptionResNet (InceptionNet, respectively) in estimating the CME mass (kinetic energy, respectively). To our knowledge, this is the first time that deep learning has been used for CME mass and kinetic energy estimations.

Investigating the Magnetic Structure of Interplanetary Coronal Mass Ejections Using Simultaneous Multispacecraft In Situ Measurements

In situ measurements from spacecraft typically provide a time series at a single location through coronal mass ejections (CMEs), and they have been one of the main methods to investigate CMEs. The CME properties derived from these in situ measurements are affected by temporal changes that occur as the CME passes over the spacecraft, such as radial expansion and aging, as well as spatial variations within a CME. This study uses multispacecraft measurements of the same CME at close separations to investigate both the spatial variability (how different a CME profile is when probed by two spacecraft close to each other) and the so-called aging effect (the effect of the time evolution on in situ properties). We compile a database of 19 events from the past 4 decades measured by two spacecraft with a radial separation of <0.2 au and an angular separation of <10°. We find that the average magnetic field strength measured by the two spacecraft differs by 18% of the typical average value, which highlights nonnegligible spatial or temporal variations. For one particular event, measurements taken by the two spacecraft allow us to quantify and significantly reduce the aging effect to estimate the asymmetry of the magnetic field strength profile. This study reveals that single-spacecraft time series near 1 au can be strongly affected by aging and that correcting for self-similar expansion does not capture the whole aging effect.

A Titov–Démoulin Type Eruptive Event Generator for β > 0 Plasmas

We provide exact analytical solutions for the magnetic field produced by prescribed current distributions located inside a toroidal filament of finite thickness. The solutions are expressed in terms of toroidal functions, which are modifications of the Legendre functions. In application to the MHD equilibrium of a twisted toroidal current loop in the solar corona, the Grad–Shafranov equation is decomposed into an analytic solution describing an equilibrium configuration against the pinch-effect from its own current and an approximate solution for an external strapping field to balance the hoop force. Our solutions can be employed in numerical simulations of coronal mass ejections (CMEs). When superimposed on the background solar coronal magnetic field, the excess magnetic energy of the twisted current loop configuration can be made unstable by applying flux cancellation to reduce the strapping field. Such loss of stability accompanied by the formation of an expanding flux rope is typical for the Titov & Démoulin eruptive event generator. The main new features of the proposed model are as follows: the filament is filled with finite β plasma with finite mass and energy, the model describes an equilibrium solution that will spontaneously erupt due to magnetic reconnection of the strapping magnetic field arcade, and there are analytic expressions connecting the model parameters to the asymptotic velocity and total mass of the resulting CME, providing a way to connect the simulated CME properties to multipoint coronograph observations.

Self-consistent propagation of flux ropes in realistic coronal simulations

Context.The text has been edited to adhere to American English based on the spelling style used in the text. In order to anticipate the geoeffectiveness of coronal mass ejections (CMEs), heliospheric simulations are used to propagate transient structures injected at 0.1 AU. Without direct measurements near the Sun, the properties of these injected CMEs must be derived from models coming from observations or numerical simulations, and thus they contain a lot of uncertainty.Aims.The aim of this paper is to demonstrate the possible use of the new coronal model COCONUT to compute a detailed representation of a numerical CME at 0.1 AU after its injection at the solar surface and propagation in a realistic solar wind, as derived from observed magnetograms.Methods.We present the implementation and propagation of modified Titov-Démoulin flux ropes in the COCONUT 3D magnetohydrodynamics coronal model. Background solar wind was reconstructed in order to model two opposite configurations representing a solar activity maximum and minimum, respectively. Both configurations were derived from magnetograms that were obtained by the Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory satellite. We tracked the propagation of 24 flux ropes that differ only by their initial magnetic flux. In particular, we investigated the geometry of the flux ropes during the early stages of their propagation as well as the influence of their initial parameters and solar wind configuration on 1D profiles derived at 0.1 AU.Results.At the beginning of the propagation, the shape of the flux ropes varied between simulations during low and high solar activity. We found dynamics that are consistent with the standard CME model, such as pinching of the CME legs and the appearance of post-flare loops. Despite the differences in geometry, the synthetic density and magnetic field time profiles at 0.1 AU are very similar in both solar wind configurations. These profiles are also similar to those observed further in the heliosphere and suggest the presence of a magnetic ejecta composed of the initially implemented flux rope and a sheath ahead of it. Finally, we uncovered relationships between the properties of the magnetic ejecta, such as relationships between density or speed and the initial magnetic flux of our flux ropes.Conclusions.The implementation of the modified Titov-Démoulin flux rope in COCONUT enables us to retrieve the major properties of CMEs at 0.1 AU for any phase of the solar cycle. When combined with heliospheric simulations, COCONUT could lead to more realistic and self-consistent CME evolution models and thus more reliable predictions.

Propagation of coronal mass ejections from the Sun to the Earth

Coronal Mass Ejections (CMEs), as they can inject a large amounts of mass and magnetic flux into the interplanetary space, are the primary source of space weather phenomena on the Earth. The present review first briefly introduces the solar surface signatures of the origins of CMEs and then focuses on the attempts to understand the kinematic evolution of CMEs from the Sun to the Earth. CMEs have been observed in the solar corona in white-light from a series of space missions over the last five decades. In particular, LASCO/SOHO has provided almost continuous coverage of CMEs for more than two solar cycles until today. However, the observations from LASCO suffered from projection effects and limited field of view (within 30 Rs from the Sun). The launch in 2006 of the twin STEREO spacecraft made possible multiple viewpoints imaging observations, which enabled us to assess the projection effects on CMEs. Moreover, heliospheric imagers (HIs) onboard STEREO continuously observed the large and unexplored distance gap between the Sun and Earth. Finally, the Earth-directed CMEs that before have been routinely identified only near the Earth at 1 AU in in situ observations from ACE and WIND, could also be identified at longitudes away from the Sun-Earth line using the in situ instruments onboard STEREO. Our review presents the frequently used methods for estimation of the kinematics of CMEs and their arrival time at 1 AU using primarily SOHO and STEREO observations. We emphasize the need of deriving the three-dimensional (3D) properties of Earth-directed CMEs from the locations away from the Sun-Earth line. The results improving the CME arrival time prediction at Earth and the open issues holding back progress are also discussed. Finally, we summarize the importance of heliospheric imaging and discuss the path forward to achieve improved space weather forecasting.

A Regional Ionospheric Storm Forecasting Method Using a Deep Learning Algorithm: LSTM

AbstractAn ionospheric storm forecasting method was proposed using a deep learning algorithm, LSTM (long short‐term memory). We used the perturbation index to denote the level of an ionospheric storm, deduced from foF2 data, and helped to remove most of the local time and seasonal variations in the ionosphere. In constructing the model, a number of correlated factors were used as inputs, including the properties of coronal mass ejections, solar flare bursts, interplanetary conditions, and geomagnetic and ionospheric states, and the output was whether an ionospheric storm occurred locally in the next 24 hr. Data sets from 2007 to 2014 were used to train the model, and those from 2015 to 2016 were used for validation. The results showed that the model behaved well in most events. The mean precision rate, recall rate, accuracy, and F1 score of the model were 71.7%, 59.7%, 92.7%, and 65.0% in northern China and 78.9%, 56.3%, 96.3% and 65.0% in southern China, respectively. The LSTM forecasting model performed better than other models such as persistence, multiple‐layer perceptron and support vector machine models. Case studies also showed good performance during geomagnetic storms of different strengths. We believe that this model can be beneficial for functional ionospheric storm operation.

The State of the White-Light Corona over the Minimum and Ascending Phases of Solar Cycle 25 – Comparison with Past Cycles

We report on the state of the corona over the minimum and ascending phases of Solar Cycle (SC) 25 on the basis of the temporal evolutions of its radiance and of the properties of coronal mass ejections (CMEs), as determined from white-light observations performed by the SOHO/LASCO-C2 coronagraph. These evolutions are further compared with those determined during the past two Solar Cycles using the same methods. The integrated radiance of the K-corona and the occurrence rate of CMEs closely track the indices/proxies of solar activity, prominently the total magnetic field for the radiance and the 10.7 cm radio flux for the CMEs, all undergoing a steep increase during the ascending phase of SC 25. This increase is much steeper than anticipated on the basis of the predicted quasi-similarity between SC 25 and SC 24, and is confirmed by the recent evolution of the sunspot number. The radiance reached the same base level during the minima of SC 24 and SC 25, but the latitudinal extent of the streamer belt differed, being flatter during the latter minimum and in fact more similar to that of the minimum of SC 23. Synchronizing the descending branches of SC 23 and SC 24 led to a duration of SC 24 of 11.0 years, similar to that given by the sunspot number. In contrast, the base level of the occurrence rate of CMEs during the minimum of SC 25 was significantly larger than during the two previous minima. The southern hemisphere is conspicuously more active than the northern, in agreement with several predictions and the current evolution of the hemispheric sunspot numbers. In particular, the occurrence rate of the subset of CMEs with known mass, their mass rate, and the number of CMEs with speeds larger than 350 km s−1 in the southern hemisphere exceeds by far the respective values in the northern hemisphere. The mean apparent width of CMEs and the number of halo CMEs remains at relatively large, constant levels throughout the early phase of SC 25, implying the persistence of weak total pressure in the heliosphere. These results, and particularly the perspective of a corona being more active than anticipated, are extremely promising for the forthcoming observations by both Solar Orbiter and Parker Solar Probe.

Magnetic cloud prediction model for forecasting space weather relevant properties of Earth-directed coronal mass ejections

Context.Coronal mass ejections (CMEs) are major eruptive events on the Sun that result in the ejection of large-scale magnetic clouds (MCs) in interplanetary space, consisting of plasma with enhanced magnetic fields whose direction changes coherently when measured in situ. The severity of CME-induced geomagnetic perturbations and space weather impacts depends on the direction and strength of the interplanetary magnetic field (IMF), as well as on the speed and duration of the passage of the magnetic cloud associated with the storm. The coupling between the heliospheric environment and Earth’s magnetosphere is strongest when the IMF direction is persistently southward (i.e. negativeBz) for a prolonged period. Predicting the magnetic profile of such Earth-directed CMEs is therefore critical for estimating their space weather consequences; this remains an outstanding challenge, however.Aims.Our aim is to build upon and integrate diverse techniques towards the development of a comprehensive magnetic cloud prediction (MCP) model that can forecast the magnetic field vectors, Earth-impact time, speed, and duration of passage of solar storms.Methods.The configuration of a CME is approximated as a radially expanding force-free cylindrical structure. Combining near-Sun geometrical, magnetic, and kinematic properties of CMEs with the probabilistic drag-based model and cylindrical force-free model, we propose a method for predicting the Earth-arrival time, propagation speed, and magnetic vectors of MCs during their passage through 1 AU. Our model is able to predict the passage duration of the storm without recourse to computationally intensive time-dependent dynamical equations.Results.Our method is validated by comparing the MCP model output with observations of ten MCs at 1 AU. In our sample, we find that eight MCs show a root mean square (rms) deviation smaller than 0.1 between the predicted and observed magnetic profiles, and the passage durations of seven MCs fall within the predicted range.Conclusions.Based on the success of this approach, we conclude that predicting the near-Earth properties of MCs based on an analysis and modelling of near-Sun CME observations is a viable endeavour with potential applications for the development of early-warning systems for space weather and enabling mitigation strategies.

Effect of the Heliospheric State on CME Evolution

The culmination of solar cycle 24 by the end of 2019 has created the opportunity to compare the differing properties of coronal mass ejections (CMEs) between two whole solar cycles: solar cycle 23 (SC 23) and solar cycle 24 (SC 24). We report on the width evolution of limb CMEs in SCs 23 and 24 in order to test the suggestion by Gopalswamy et al. that CME flux ropes attain pressure balance at larger heliocentric distances in SC 24. We measure CME width as a function of heliocentric distance for a significantly large number of limb CMEs (∼1000) and determine the distances where the CMEs reach constant width in each cycle. We introduced a new parameter, the transition height (hc) of a CME, defined as the critical heliocentric distance beyond which the CME width stabilizes to a quasi-constant value. Cycle and phase-to-phase comparisons are based on this new parameter. We find that the average value of hc in SC 24 is 62% higher than that in SC 23. SC 24 CMEs attain their peak width at larger distances from the Sun than SC 23 CMEs do. The enhanced transition height in SC 24 is new observational ratification of the anomalous expansion. The anomalous expansion of SC 24 CMEs, which is caused by the weak state of the heliosphere, accounts for the larger heliocentric distance where the pressure balance between CME flux rope and the ambient medium is attained.

A Machine Learning Approach to Predicting SEP Events Using Properties of Coronal Mass Ejections

AbstractSolar energetic particles (SEPs) can cause severe damage to astronauts and their equipment, and can disrupt communications on Earth. A lack of thorough understanding the eruption processes of solar activities and the subsequent acceleration and transport processes of energetic particles makes it difficult to forecast the occurrence of an SEP event and its intensity using conventional modeling with physics‐based parameters. Therefore, in order to provide an advance warning for astronauts to seek shelter in a timely manner, we apply neural networks to forecast the occurrence of SEP events. We use the properties of coronal mass ejections (CMEs) archived in the Coordinated Data Analysis Workshops catalog based on SOHO Large Angle and Spectrometric Coronagraph Experiment observations. We also derive some features based on these properties associated with the CME, and analyze the contribution of each feature to the overall prediction. Our algorithm achieves an average True Skill Statistic of 0.906, an average F1 score of 0.246, an average probability of detection of 0.920, and an average false alarm rate of 0.882. An analysis of the features shows that sunspot number and a feature based on Type II radio bursts contribute the most, but when grouped together, CME speed‐related features are the most important features.

Can We Detect Coronal Mass Ejections through Asymmetries of Sun-as-a-star Extreme-ultraviolet Spectral Line Profiles?

Coronal mass ejections (CMEs) are the largest-scale eruptive phenomena in the solar system. Associated with enormous plasma ejections and energy releases, CMEs have an important impact on the solar–terrestrial environment. Accurate predictions of the arrival times of CMEs at the Earth depend on precise measurements of their 3D velocities, which can be achieved by using simultaneous line-of-sight (LOS) and plane-of-sky (POS) observations. Besides the POS information from routine coronagraph and extreme-ultraviolet (EUV) imaging observations, spectroscopic observations could unveil the physical properties of CMEs, including their LOS velocities. We propose that spectral line asymmetries measured by Sun-as-a-star spectrographs can be used for routine detections of CMEs and estimations of their LOS velocities during their early propagation phases. Such observations can also provide important clues for the detection of CMEs on other solar-like stars. However, few studies have concentrated on whether we can detect CME signals and accurately diagnose CME properties through Sun-as-a-star spectral observations. In this work, we construct a geometric CME model and derive the analytical expressions for full disk-integrated EUV line profiles during CMEs. For different CME properties and instrumental configurations, the full disk-integrated line profiles are synthesized. We further evaluate the detectability and diagnostic potential of CMEs from the synthetic line profiles. Our investigations provide important constraints on the future design of Sun-as-a-star spectrographs for CME detections through EUV line asymmetries.

Coronal Mass Ejections and Dimmings: A Comparative Study Using MHD Simulations and SDO Observations

Abstract Solar coronal dimmings have been observed extensively in recent years. Due to their close association with coronal mass ejections (CMEs), there is a critical need to improve our understanding of the physical processes that cause dimmings as well as their relationship with CMEs. In this study, we investigate coronal dimmings by combining simulation and observational efforts. By utilizing a data-constrained global magnetohydrodynamics model (Alfvén-wave solar model), we simulate coronal dimmings resulting from different CME energetics and flux rope configurations. We synthesize the emissions of different EUV spectral bands/lines and compare with SDO/AIA and EVE observations. A detailed analysis of the simulation and observation data suggests that the transient dimming/brightening are related to plasma heating processes, while the long-lasting core and remote dimmings are caused by mass-loss process induced by the CME. Moreover, the interaction between the erupting flux rope with different orientations and the global solar corona could significantly influence the coronal dimming patterns. Using metrics such as dimming depth and dimming slope, we investigate the relationship between dimmings and CME properties (e.g., CME mass, CME speed) in the simulation. Our result suggests that coronal dimmings encode important information about the associated CMEs, which provides a physical basis for detecting stellar CMEs from distant solar-like stars.

A revised cone model and its application to non-radial prominence eruptions

Context. The traditional cone models achieve great success in studying the geometrical and kinematic properties of halo coronal mass ejections (CMEs). Aims. In this Letter, a revised cone model is proposed to investigate the properties of CMEs as a result of non-radial prominence eruptions. Methods. The cone apex is located at the source region of an eruption instead of the Sun center. The cone axis deviates from the local vertical by an inclination angle of θ1 and an angle of ϕ1. The length and angular width of the cone are r and ω, respectively. Results. The model was successfully applied to two CMEs originating from the western limb on 2011 August 11 and 2012 December 7. By comparing the projections of the cones with the CME fronts simultaneously observed by the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory and the Extreme-Ultraviolet Imager on board the ahead Solar TErrestrial RElations Observatory, the properties of the CMEs were derived, including the distance, angular width, inclination angle, deviation from the plane of the sky, and true speed in space. Conclusions. This revised cone model provides a new and complementary approach in exploring the whole evolutions of CMEs.

Modelling a multi-spacecraft coronal mass ejection encounter with EUHFORIA

Context. Coronal mass ejections (CMEs) are a manifestation of the Sun’s eruptive nature. They can have a great impact on Earth, but also on human activity in space and on the ground. Therefore, modelling their evolution as they propagate through interplanetary space is essential. Aims. EUropean Heliospheric FORecasting Information Asset (EUHFORIA) is a data-driven, physics-based model, tracing the evolution of CMEs through background solar wind conditions. It employs a spheromak flux rope, which provides it with the advantage of reconstructing the internal magnetic field configuration of CMEs. This is something that is not included in the simpler cone CME model used so far for space weather forecasting. This work aims at assessing the spheromak CME model included in EUHFORIA. Methods. We employed the spheromak CME model to reconstruct a well observed CME and compare model output to in situ observations. We focus on an eruption from 6 January 2013 that was encountered by two radially aligned spacecraft, Venus Express and STEREO-A. We first analysed the observed properties of the source of this CME eruption and we extracted the CME properties as it lifted off from the Sun. Using this information, we set up EUHFORIA runs to model the event. Results. The model predicts arrival times from half to a full day ahead of the in situ observed ones, but within errors established from similar studies. In the modelling domain, the CME appears to be propagating primarily southward, which is in accordance with white-light images of the CME eruption close to the Sun. Conclusions. In order to get the observed magnetic field topology, we aimed at selecting a spheromak rotation angle for which the axis of symmetry of the spheromak is perpendicular to the direction of the polarity inversion line (PIL). The modelled magnetic field profiles, their amplitude, arrival times, and sheath region length are all affected by the choice of radius of the modelled spheromak.

Geoeffectiveness Prediction of CMEs

Coronal mass ejections (CMEs), the most important pieces of the puzzle that drive space weather, are continuously studied for their geomagnetic impact. We present here an update of a logistic regression method model, that attempts to forecast if a CME will arrive at the Earth and it will be associated with a geomagnetic storm defined by a minimum Dst value smaller than −30 nT. The model is run for a selection of CMEs listed in the LASCO catalogue during the solar cycle 24. It is trained on three fourths of these events and validated for the remaining one fourth. Based on five CME properties (the speed at 20 solar radii, the angular width, the acceleration, the measured position angle and the source position – binary variable) the model successfully predicted 98% of the events from the training set, and 98% of the events from the validation one.