Understanding our capabilities in observing and modelling Coronal Mass Ejections

Aims. We introduce a new model for coronal mass ejections (CMEs) that has been implemented in the magnetohydrodynamics (MHD) inner heliosphere model EUHFORIA. Utilising a linear force-free spheromak (LFFS) solution, the model provides an intrinsic magnetic field structure for the CME. As a result, the new model has the potential to predict the magnetic components of CMEs at Earth. In this paper, we present the implementation of the new model and show the capability of the new model. Methods. We present initial validation runs for the new magnetised CME model by considering the same set of events as used in the initial validation run of EUHFORIA that employed the Cone model. In particular, we have focused on modelling the CME that was responsible for creating the largest geomagnetic disturbance (Dst index). Two scenarios are discussed: one where a single magnetised CME is launched and another in which we launch all five Earth-directed CMEs that were observed during the considered time period. Four out of the five CMEs were modelled using the Cone model. Results. In the first run, where the propagation of a single magnetized CME is considered, we find that the magnetic field components at Earth are well reproduced as compared to in-situ spacecraft data. Considering a virtual spacecraft that is separated approximately seven heliographic degrees from the position of Earth, we note that the centre of the magnetic cloud is missing Earth and a considerably larger magnetic field strength can be found when shifting to that location. For the second run, launching four Cone CMEs and one LFFS CME, we notice that the simulated magnetised CME is arriving at the same time as in the corresponding full Cone model run. We find that to achieve this, the speed of the CME needs to be reduced in order to compensate for the expansion of the CME due to the addition of the magnetic field inside the CME. The reduced initial speed of the CME and the added magnetic field structure give rise to a very similar propagation of the CME with approximately the same arrival time at 1 au. In contrast to the Cone model, however, the magnetised CME is able to predict the magnetic field components at Earth. However, due to the interaction between the Cone model CMEs and the magnetised CME, the magnetic field amplitude is significantly lower than for the run using a single magnetised CME. Conclusions. We have presented the LFFS model that is able to simulate and predict the magnetic field components and the propagation of magnetised CMEs in the inner heliosphere and at Earth. We note that shifting towards a virtual spacecraft in the neighbourhood of Earth can give rise to much stronger magnetic field components. This gives the option of adding a grid of virtual spacecrafts to give a range of values for the magnetic field components.

The current progression toward solar maximum provides a unique opportunity to use multi-perspective spacecraft observations together with numerical models to better understand the evolution and propagation of coronal mass ejections (CMEs). Of interest to both the scientific and forecasting communities are the Earth-directed “halo” CMEs, since they typically produce the most geoeffective events. However, determining the actual initial geometries of halo CMEs is a challenge due to the plane-of-sky projection effects. Thus the recent 15 February 2011 halo CME event has been selected for this study. During this event the Solar TErrestrial RElations Observatory (STEREO) A and B spacecraft were fortuitously located ∼ 90° away from the Sun–Earth line such that the CME was viewed as a limb event from these two spacecraft, thereby providing a more reliable constraint on the initial CME geometry. These multi-perspective observations were utilized to provide a simple geometrical description that assumes a cone shape for a CME to calculate its angular width and central position. The event was simulated using the coupled Wang–Sheeley–Arge (WSA)-Enlil 3D numerical solar corona-solar wind model. Daily updated global photospheric magnetic field maps were used to drive the background solar wind. To improve our modeling techniques, the sensitivity of the modeled CME arrival times to the initial input CME geometry was assessed by creating an ensemble of numerical simulations based on multiple sets of cone parameters for this event. It was found that the accuracy of the modeled arrival times not only depends on the initial input CME geometry, but also on the accuracy of the modeled solar wind background, which is driven by the input maps of the photospheric field. To improve the modeling of the background solar wind, the recently developed data-assimilated magnetic field synoptic maps produced by the Air Force Data Assimilative Photospheric flux Transport (ADAPT) model were used. The ADAPT maps provide a more instantaneous snapshot of the global photospheric field distribution than that provided by traditional daily updated synoptic maps. Using ADAPT to drive the background solar wind, an ensemble set of eight different CME arrival times was generated, where the spread in the predictions was ∼ 13 hours and was nearly centered on the observed CME shock arrival time.

<p>Coronal mass ejections (CMEs) are arguably one of the most violent explosions in our solar system. CMEs are also one of the most important drivers for space weather. CMEs can have direct adverse effects on several human activities. Reliable and fast prediction of the CMEs arrival time is crucial to minimize such damage from a CME. We present a new pipeline combining machine learning (ML) with a physical drag-based model of CME propagation to predict the arrival time of the CME. We evaluate both standard ML approaches and a combination of ML + probabilistic drag based model (PDBM, Napoletano et al. 2018). More than 200 previously observed geo-effective partial-/full-halo CMEs make up the database for this study (with information extracted from the Richardson & Cane 2010 catalogue, the CDAW data centre CME list, the LASCO coronagraphic images, and the HEK database - Hurlburt et al. 2010). The P-DBM provides us with a reduced computation time, which is promising for space weather forecasts. We analyzed and compared various machine learning algorithms to identify the best performing algorithm for this database of the CMEs. We also examine the relative importance of various features such as mass, CME propagation speed, and height above the solar limb of the observed CMEs in the prediction of the arrival time. The model is able to accurately predict the arrival times of the CMEs with a mean square error of about 9 hours.  We also explore the differences in prediction from ML models and emblem prediction method namely P-DBM model.</p>

<p>Previous studies of Coronal Mass Ejections (CMEs) have shown the importance of understanding their geometrical structure and internal magnetic field configuration for improving forecasting at Earth. The precise prediction of the CME shock and the magnetic cloud arrival time, their magnetic field strength and the orientation upon impact at Earth is still challenging and relies on solar wind and CME evolution models and precise input parameters. In order to understand the propagation of CMEs in the interplanetary medium, we need to understand their interaction with the complex features in the magnetized background solar wind which deforms, deflects and erodes the CMEs and determines their geo-effectiveness. Hence, it is important to model the internal magnetic flux-rope structure in the CMEs as they interact with CIRs/SIRs, other CMEs and solar transients in the heliosphere. The spheromak model (Verbeke et al. 2019) in the heliospheric wind and CME evolution simulation EUHFORIA (Pomoell and Poedts, 2018), fits well with the data near the CME nose close to its axis but fails to predict the magnetic field in CME legs when these impact Earth (Scolini et al. 2019). Therefore, we implemented the FRi3D stretched flux-rope CME model (Isavnin, 2016) in EUHFORIA to model a more realistic CME geometry. Fri3D captures the three-dimensional magnetic field structure with parameters like skewing, pancaking and flattening that quantify deformations experienced by an interplanetary CME. We perform test runs of real CME events and validate the ability of FRi3D coupled with EUHFORIA in predicting the CME geo-effectiveness. We have modeled two real events with FRi3D. First, a CME event on 12 July 2012 which was a head-on encounter at Earth. Second, the flank CME encounter of 14 June 2012 which did not leave any magnetic field signature at Earth when modeled with Spheromak. We compare our results with the results from non-magnetized cone simulations and magnetized simulations employing the spheromak flux-rope model. We further discuss how constraining observational parameters using the stretched flux rope CME geometry in FRi3D affects the prediction of the magnetic field strength in our simulations, highlighting improvements and discussing future perspective.</p><p><em>This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0)</em></p>

A global, three‐dimensional (3‐D) numerical simulation model has been employed to study the Sun‐to‐Earth propagation of multiple (12) coronal mass ejections (CMEs) and their associated shocks in September 2011. The inputs to the simulation are based on actual solar observations, which include the CME speeds, source locations, and photospheric magnetic fields. The simulation result is fine tuned with in situ solar wind data observations at 1 AU by matching the arrival time of CME‐driven shocks. During this period three CME‐driven interplanetary (IP) shocks induced three sizable geomagnetic storms on 9, 17, and 26 September, with Dst values reaching −69, −70, and −101 nT, respectively. These storm events signify the commencement of geomagnetic activity in the solar cycle 24. The CME propagation speed near the Sun (e.g., < 30 RS) has been widely used to estimate the interplanetary CME (ICME)/Shock arrival time at 1 AU. Our simulation indicates that the background solar wind speed, as expected, is an important controlling parameter in the propagation of IP shocks and CMEs. Prediction of the ICME/shock arrival time at 1 AU can be more problematic for slow (e.g., < 500 km s−1) than fast CMEs (>1000 km s−1). This is because the effect of the background solar wind is more pronounced for slow CMEs. Here we demonstrate this difficulty with a slow (400 km s−1) CME event that arrived at the Earth in 3 days instead of the predicted 4.3 days. Our results also demonstrate that a long period (a month in this case) of simulation may be necessary to make meaningful solar source geomagnetic storm associations.

Coronal mass ejections (CMEs) erupting from the host star are expected to affect the atmospheric erosion processes of planets. For planets with a magnetosphere, the embedded magnetic field in the CMEs is thought to be the most important parameter to affect planetary mass-loss. In this work, we investigate the effect of different magnetic field structures of stellar CMEs on the atmosphere of a hot Jupiter with a dipolar magnetosphere. We use a time-dependent 3D radiative magnetohydrodynamic (MHD) atmospheric escape model that self-consistently models the outflow from hot Jupiter’s magnetosphere and its interaction with stellar CMEs. For our study, we consider three configurations of magnetic field embedded in CMEs – (a) northward $B_z$ component, (b) southward $B_z$ component, and (c) radial component. We find that both the CMEs with northward $B_z$ and southward $B_z$ increase the planetary mass-loss rate when the CME arrives from the stellar side, with the mass-loss rate remaining higher for the CME with northward $B_z$ until it arrives on the opposite side. The largest magnetopause is found for the CME with a southward $B_z$ component. During the passage of a CME, the planetary magnetosphere goes through three distinct changes – (1) compressed magnetosphere, (2) enlarged magnetosphere, and (3) relaxed magnetosphere for all three CME configurations. The computed synthetic Ly $\alpha$ transit absorption generally increases when the CME is in interaction with the planet for all magnetic configurations but the maximum Ly $\alpha$ absorption is found for the case of radial CME with the most compressed magnetosphere.

给出了特殊类型的日冕物质抛射(CME)数值模拟定性结果,这种CME核心闭磁场结构前半部分磁力线的方向与太阳整体偶极场磁力线的方向相反.计算结果表明,这种CME核心闭磁场结构磁力线与太阳整体偶极场反向磁力线之间存在过渡磁场结构,在向外传播时过渡磁场结构所占的面积逐渐增大.这一结果可以用来解释飞船为什么能够观测到一类双极磁云,这类磁云前半部分磁场方向与太阳整体偶极场方向相反.为了模拟这一数值结果,强调需要采用包含嵌套闭磁场的冕流背景结构,并在合适的位置触发CME.

Space weather predictions related to coronal mass ejections (CMEs) requires understanding how a CME is initiated and how its properties change as it propagates. Most predictions have been limited to the arrival time of a CME and include little to no information about the CME's internal properties. ANother Type of Ensemble Arrival Time Results‐Physics‐driven Approach to Realistic Axis Deformation and Expansion (ANTEATR‐PARADE) represents the most thorough description of the interplanetary evolution of CMEs in a highly computationally‐efficient model (Kay & Nieves‐Chinchilla, 2020, https://doi.org/10.1029/2020JA028911). presents the derivation of this model, where we have added an elliptical cross section to the original arrival time model ANTEATR and introduced internal magnetic and thermal forces that, combined with the drag, can alter the shape of the central axis and cross section. ANTEATR‐PARADE results include the transit time of CMEs, as well as the shape and size, propagation and expansion velocities, density, and magnetic field properties upon impact. We determine the dependence of each output on each of the ANTEATR‐PARADE input parameters. For a fast CME, we see that the parameterization of our thermal and magnetic models tends to be more important than the actual initial temperature or magnetic field strength. We extend to other CMEs and find that the sensitivities change with CME scale with thermal forces being more important for a weaker CME and magnetic forces being more important for a stronger CME. The most critical parameters for space weather predictions are the CME mass, the initial magnetic field strength, the adiabatic index, and the profile of the axial magnetic field strength.

Abstract. The apparent contradiction between small-scale source regions of, and large-scale coronal response to, coronal mass ejections (CMEs) has been a long-standing puzzle. For some, CMEs are considered to be inherently large-scale events – eruptions in which a number of flux systems participate in an unspecified manner, while others consider magnetic reconnection in special global topologies to be responsible for the large-scale response of the lower corona to CME events. Some of these ideas may indeed be correct in specific cases. However, what is the key element which makes CMEs large-scale? Observations show that the extent of the coronal disturbance matches the angular width of the CME – an important clue, which does not feature strongly in any of the above suggestions. We review observational evidence for the large-scale nature of CME source regions and find them lacking. Then we compare different ideas regarding how CMEs evolve to become large-scale. The large-scale magnetic topology plays an important role in this process. There is amounting evidence, however, that the key process is magnetic reconnection between the CME and other magnetic structures. We outline a CME evolution model, which is able to account for all the key observational signatures of large-scale CMEs and presents a clear picture how large portions of the Sun become constituents of the CME. In this model reconnection is driven by the expansion of the CME core resulting from an over-pressure relative to the pressure in the CME's surroundings. This implies that the extent of the lower coronal signatures match the final angular width of the CME.

Our knowledge of the physical processes carrying information across Coronal Mass Ejections (CMEs), thereby controlling the way CME structures respond to external disturbances  in interplanetary space, is still incomplete. One prominent question is whether CMEs are “coherent” structures, i.e. potentially capable of responding in a uniform manner to external forces, and across what (macroscopic) spatial scales does such coherence exist. A necessary condition for different regions within a given CME to exhibit a coherent behavior is that they must be causally connected to the perturbation source. Past studies suggested interplanetary CMEs may behave as coherent structures only locally, and indicated that the spatial scale of coherence may be hampered by interactions with large-scale structures in the solar wind. Additionally, observational studies often assumed the correlation in the magnetic field profiles at different spacecraft locations as a proxy for coherence, but the physical link between correlation and coherence is still to be established. Characterizing the physical mechanisms mediating CME structural changes in different solar wind conditions at a fundamental level is therefore imperative to better understand their evolution and impact on space-borne and ground-based anthropic activities. In this study, we investigate the role of Alfvénic fluctuations (AFs) as mediators of coherence within interplanetary CMEs, and the physical relationship between correlation and coherence using multi-point observations near 1 au. In order to determine if and to what extent AFs alter CMEs at different spatial scales, we compare CME signatures at multiple spacecraft in terms of presence/absence of AFs, AF properties (if present), and correlation of magnetic signatures.  We contextualize the results in terms of the CME interaction history and the causal connection of different spacecraft observations. This study reveals how AFs affect the correlation of CME magnetic signatures across different spatial scales, and helps reconcile correlation scales within CMEs with their coherent behavior. 

Interplanetary coronal mass ejections (ICMEs) are the heliospheric counterparts of solar coronal mass ejections, and their comprehensive cataloging near Earth has enabled significant advances across space science disciplines. As a part of the Project Space Life by Eco Astronomy Inc, this review presents a synthesis of the Near-Earth ICME since 1996” dataset compiled by I. G. Richardson and H. V. Cane, highlighting its historical development, methodology, key findings, and broad applications. The dataset encompasses approximately 600 ICMEs observed at 1 AU from 1996 through early 2024, spanning solar cycles 23, 24, and the rise of 25. We discuss how ICMEs are identified using in-situ plasma, magnetic field, composition, and energetic particle signatures, and how this approach has evolved with improved data (e.g. ACE spacecraft measurements). The ICME catalogs reveals clear solar-cycle trends, ICME occurrence rises by an order of magnitude from solar minimum to maximum with the yearly counts peaking in 2000 (51 events) and dipping to only a few events at recent minima. It also captures intriguing temporal patterns such as a quasi-periodicity of ~150 days in ICME occurrence (Cane & Richardson, January 1, 2003). We synthesize the typical ICME properties (duration, speed, magnetic field strength) and how they vary between cycles: e.g. cycle 23 produced more frequent and faster ICMEs than the weaker cycle 24. The dataset’s extensive annotations (footnotes) link each ICME to associated phenomena like geomagnetic sudden commencements, storm indices, and cosmic ray depressions, allowing analysis of ICME impacts. We review how ~90% of major geomagnetic storms (Dst ≤ –100 nT) in 1996–2005 were caused by ICMEs or their driven shocks (Richardson & Cane, 2007), underlining their geo effectiveness. We summarize statistical correlations between ICME parameters (speed, magnetic field, size) and geomagnetic storm intensity and discuss notable events. Beyond geomagnetism, ICMEs are shown to modulate galactic cosmic rays, causing short-term intensity drops (Forbush decreases) in ~80% of cases (I & H, 2011) and contributing to long-term cosmic-ray modulation over the solar cycle. The rich Richardson-Cane ICME database has fostered multidisciplinary benefits: improving space weather forecasts (by providing empirical event data for CME arrival and storm predictions), informing heliospheric physics (e.g. ICME propagation and solar-cycle variability), elucidating cosmic ray transport (through ICME-caused particle decreases), and aiding studies of impacts on technological systems (satellites, power grids, GPS) and Earth’s atmosphere. We conclude by emphasizing the value of this continually updated ICME catalogs for future research and cross-disciplinary applications, and we include a comprehensive appendix of ICME analysis figures derived from the dataset.

<p>Interplanetary coronal mass ejections (ICMEs), large clouds of plasma and magnetic field regularly expelled from the Sun, are one of the main drivers of space weather effects in the solar system. While the prediction of their arrival time at Earth and other locations in the heliosphere is still a complex task, it is also necessary to further understand the time evolution of their geometric and magnetic structure, which is even more challenging considering the limited number of available observation points.</p><p>Forbush decreases (FDs), short-term drops in the flux of galactic cosmic rays (GCR), can be caused by the shielding from strong and/or turbulent magnetic structures in the solar wind, such as ICMEs and their associated shock/sheath regions. In the past, FD observations have often been used to determine the arrival times of ICMEs at different locations in the solar system, especially where sufficient solar wind plasma and magnetic field measurements are not (or not always) available. One of these locations is Mars, where the Radiation Assessment Detector (RAD) onboard the Mars Science Laboratory (MSL) mission's Curiosity rover has been continuously measuring GCRs and FDs on the surface for more than 7 years.</p><p>In this work, we investigate whether FD data can be used to derive additional information about the ICME properties than just the arrival time by performing a statistical study based on catalogs of FDs observed at Earth or Mars. In particular, we find that the linear correlation between the FD amplitude and the maximum steepness, which was already seen at Earth by previous authors (Belov et al., 2008, Abunin et al., 2012), is likewise present at Mars, but with a different proprtionality factor.</p><p>By consulting physics-based analytical models of FDs, we find that this quantity is not expected to be influenced by the different energy ranges of GCR particles observed by the instruments at Earth and Mars. Instead, we suggest that the difference in FD characteristics at the two planets is caused by the radial enlargement of the ICMEs, and particularly their sheath regions, as they propagate from Earth (1 AU) to Mars (~ 1.5 AU). This broadening factor derived from our analysis extends observations for the evolution closer to the Sun by Janvier et al. (2019, JGR Space Physics) to larger heliocentric distances and is consistent with these results.</p>

We describe an empirical model to predict the 1‐AU arrival of coronal mass ejections (CMEs). This model is based on an effective interplanetary (IP) acceleration described by Gopalswamy et al. [2000b] that the CMEs are subject to, as they propagate from the Sun to 1 AU. We have improved this model (1) by minimizing the projection effects (using data from spacecraft in quadrature) in determining the initial speed of CMEs, and (2) by allowing for the cessation of the interplanetary acceleration before 1 AU. The resulting effective IP acceleration was higher in magnitude than what was obtained from CME measurements from spacecraft along the Sun‐Earth line. We evaluated the predictive capability of the CME arrival model using recent two‐point measurements from the Solar and Heliospheric Observatory (SOHO), Wind, and ACE spacecraft. We found that an acceleration cessation distance of 0.76 AU is in reasonable agreement with the observations. The new prediction model reduces the average prediction error from 15.4 to 10.7 hours. The model is in good agreement with the observations for high‐speed CMEs. For slow CMEs the model as well as observations show a flat arrival time of ∼4.3 days. Use of quadrature observations minimized the projection effects naturally without the need to assume the width of the CMEs. However, there is no simple way of estimating the projection effects based on the surface location of the Earth‐directed CMEs observed by a spacecraft (such as SOHO) located along the Sun‐Earth line because it is impossible to measure the width of these CMEs. The standard assumption that the CME is a rigid cone may not be correct. In fact, the predicted arrival times have a better agreement with the observed arrival times when no projection correction is applied to the SOHO CME measurements. The results presented in this work suggest that CMEs expand and accelerate near the Sun (inside 0.7 AU) more than our model supposes; these aspects will have to be included in future models.

To study the evolution and propagation of Coronal Mass Ejections (CMEs), the advanced magnetized flux rope CME model, Flux Rope in 3D (FRi3D), has been integrated into the European Heliospheric Forecasting Information Asset (EUHFORIA). Recent updates have been addressing the computational efficiency and numerical stability issues of this CME model. In this work, the latest improvements to the FRi3D model are represented, including optimizations of the integral calculations in the ai.fri3d Python package, an updated CME leg disconnection method, and the introduction of a new datacube injection methodology for time‐efficient FRi3D simulations. Within the datacube injection method, the input values of FRi3D at the inner boundary of EUHFORIA are precomputed, eliminating the need to calculate the FRi3D CME model during the solar wind simulation with superimposed CMEs. The datacube injection method is tested by modeling the CME event of 12 July 2012, and by conducting ensemble runs for this event. The updates to the FRi3D Python package reduced the computation time to , and the datacube methodology achieved a computational time reduction of up to compared to previous FRi3D versions. Numerical stability was significantly improved, and ensemble simulations demonstrated robust ensemble spreads for the thermodynamic and magnetic time profiles on Earth. These updates enhance the efficiency, stability, and accuracy of the FRi3D model, making it highly suitable for predicting both the CME arrival time, magnetic field strength, and velocity. As a result, the advancements contribute significantly to the future operational space weather forecasting capabilities of the FRi3D CME model.

<p>Coronal Mass Ejections (CMEs) are the main drivers of interplanetary shocks and space weather disturbances. One of the key parameters that determine the geo-effectiveness of the CME is its internal magnetic configuration. Strong CMEs directed towards Earth can have a severe impact on our planet and their prediction can mitigate possible damages. </p><p> </p><p>The novel heliospheric model Icarus, which is implemented within the framework of MPI-AMRVAC (Xia et al., 2018) introduces new capabilities to model the heliospheric wind and real CME events. Advanced techniques, such as adaptive mesh refinement and grid stretching are implemented. By imposing these techniques, we avoid cell deformation in the domain and only the necessary/desired areas are refined to higher spatial resolutions (and coarsened again when the high resolution is no longer necessary, e.g. behind a travelling shock wave). The refinement and coarsening conditions are controlled by the user. These techniques result in optimised computer memory usage and a significant speed-up, which is crucial for forecasting purposes. </p><p> </p><p>In order to model the magnetic field of the CME and its interaction with the solar wind, the Gibson and Low model is implemented in Icarus. In order to assess the ICARUS model capabilities to predict the solar wind conditions in the heliosphere, especially at L1, we consider a real CME event.  Further, we perform a comparison of the results of the existing Linear Force-Free Spheromak model and the new advanced model. To perform the full comparison we compare the time series data at L1 and other satellites, while we also monitor the time that simulations require to model the heliospheric wind and CME events. </p><p> </p><p>The solution mesh refinement is applied to the CMEs in order to model its arrival time and interior magnetic field better. To analyse the results, the radial, longitudinal and latitudinal components of the magnetic field are compared to the original EUHFORIA simulations and the observed data. As a result, the new magnetized model gives an opportunity to model the CME better and a bigger range of parameters to investigate to model the event as accurately as possible.  </p><p> </p><p>This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0).</p>