Studies of ICMEs observed by multi-spacecraft over varying longitudinal and radial separations provide valuable insight into the general properties, expansion, and possible interaction with other features of the solar wind environment as the ICME propagates. Previous studies have suggested that ICMEs are not coherent structures, but may display locally apparent coherence due to similar initial conditions and quasi homogeneity of the solar wind background through which they propagate.

In this study, we use a tool to match distinct features observed in the magnetic field profiles measured at each spacecraft as a proxy for coherence, and investigate the types of ICME and scales over which this is possible using those listed in the HELIO4CAST lineup catalogue v2.0 (https://helioforecast.space/lineups). In addition, we use the timing and positions of these matched features to calculate the mean propagation velocities of these features between the spacecraft. We present example CME events comparing the calculated mean propagation velocity profiles to those measured in situ where plasma data is available, and investigate the relationship between local and global expansion.

How to cite: Davies, E., Möstl, C., Weiler, E., and Forsyth, R.: Investigating the coherency and expansion of ICMEs using multi-spacecraft observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9858, https://doi.org/10.5194/egusphere-egu24-9858, 2024.

Solar cycle 25 might be close to its expected peak and related activity is at a high. In 2023 many complex events were observed remotely and measured in-situ. Some of them even caused aurorae in low latitudes, repeatedly confirming that the interaction between multiple CMEs, as well as CIRs, lead to extreme conditions in near-Earth space. We study a set of “homologous” events on the Sun, where several CMEs interacted and additionally interfered by a high-speed stream from a coronal hole. The two sets of events involve the same active regions and coronal hole but are separated by a full solar rotation. We point out the complexity for each set of events and aim to understand how the global magnetic field configuration leads to a general similarity in the activation of the CME source regions. The studied in-situ measurements are connected to the solar surface observations and interpreted by processes caused due to shock-magnetic obstacle interaction.

How to cite: Temmer, M., Dumbovic, M., Martinic, K., Cappello, G. M., Remeshan, A. K., Milosic, D., Koller, F., Calogovic, J., and Matkovic, F.: CME-CME-CIR interaction - comparison of "homologous" events from two different solar rotations , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8788, https://doi.org/10.5194/egusphere-egu24-8788, 2024.

Observations have shown a clear association of filament/prominence eruptions with the emergence of magnetic flux in or near filament channels. Magnetohydrodynamic (MHD) simulations have been employed to systematically study the conditions under which such eruptions occur. These simulations to date have modeled filament channels as two-dimensional (2D) flux ropes or 3D uniformly sheared arcades. Here we present MHD simulations of flux emergence into a more realistic configuration consisting of a bipolar active region containing a line-tied 3D flux rope. We use the coronal flux-rope model of Titov et al. (2014) as the initial condition and drive our simulations by imposing boundary conditions extracted from a flux-emergence simulation by Leake et al. (2013). We identify three mechanisms that determine the evolution of the system: (i) reconnection displacing foot points of field lines overlying the coronal flux rope, (ii) changes of the ambient field due to the intrusion of new flux at the boundary, and (iii) interaction of the (axial) electric currents in the pre-existing and newly emerging flux systems. The relative contributions and effects of these mechanisms depend on the properties of the pre-existing and emerging flux systems. Here we focus on the location and orientation of the emerging flux relative to the coronal flux rope. Varying these parameters, we investigate under which conditions an eruption of the latter is triggered.

How to cite: Torok, T., Linton, M. G., Leake, J. E., Mikic, Z., Lionello, R., Titov, V. S., and Downs, C.: Solar Eruptions Triggered by Flux Emergence Below or Near a Coronal Flux Rope, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2651, https://doi.org/10.5194/egusphere-egu24-2651, 2024.

Supported by the Space Weather with Quantified Uncertainty (SWQU) NSF program, we have been developing the Next Generation Space Weather Modeling Framework at the University of Michigan for three years. The main goal of the project is to provide useful probabilistic forecast of major space weather events about 24 hours before the geospace impact occurs. We are using the first-principles models in the Space Weather Modeling Framework (SWMF) in combination with uncertainty quantification and data assimilation. Using the advanced MaxPro experimental design and fully automated Python scripts, we have performed thousands of solar wind background and coronal mass ejection (CME) simulations with the solar corona, inner heliosphere and eruptive event generator based on the Gibson-Low fluxrope (EEGGL) models of the SWMF. Our CME initiation model is at the surface of the Sun, so the CME can interact with the background solar wind and the magnetic field of the erupting active region. Based on these simulations, we have performed the uncertainty quantification analysis using the Bayesian inversion formula and a newly defined distance metric adapted to solar simulations. One important finding is that the physically meaningful range of the background solar wind model parameters depends on the solar cycle. We have identified the three most important parameters that impact the background solar wind model and two more parameters (the strength and helicity of the magnetic field of the fluxrope) that impact the CME eruption model. The reduced dimensionality of the parameter space enables reducing the size of the ensemble. Data assimilation provides further opportunity to improve the predictions. We are using in-situ observations at L1 prior to the CME to constrain the background solar wind and coronal white-light image observations right after the eruption to find the optimal flux rope parameters. We find that the CME arrival time error is significantly reduced to less than 5 hours by the data assimilation based on three events. Using an ensemble of simulations also provides a likely range for the various quantities of interest, including arrival time, solar wind speed and density and the B_Z component of the magnetic field. The main product of the project, the Michigan Sun-to-Earth Model with Quantified Uncertainty and Data Assimilation (MSTEM-QUDA) is available as an open-source distribution at https://github.com/MSTEM-QUDA

How to cite: Toth, G., Chen, Y., Huan, X., van der Holst, B., Jivani, A., Chen, H., Sachdeva, N., Huang, Z., and Manchester, W.: Sun-to-Earth CME Modeling with Data Assimilation and Uncertainty Quantification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4425, https://doi.org/10.5194/egusphere-egu24-4425, 2024.

CLEAR will deliver capabilities for robust and quantifiable forecasts of the space radiation level of up to 24 hours, in support of aviation, satellites, and space exploration. Solar energetic particles (SEPs) can be accelerated over a wide range of energies extending up to GeVs. At relatively low energies (e.g., ~10 MeV), their flux intensity can exceed the background of galactic cosmic rays by several orders of magnitude. Protons of >100 MeV with elevated fluxes exceeding 1 proton flux unit are responsible for an increased astronaut exposure inside spacecraft shielding. Protons of >150MeV are very difficult to shield against as they can penetrate 20 gm cm (7.4 cm of Al, or 15.5 cm of water/human tissue). Furthermore, > 500 MeV protons can penetrate the atmosphere and pose radiation hazards to aviation. Besides protons, energetic heavy ions, e.g., Fe ions, can be of more severe radiation concerns. SEPs are hazardous not only to humans but also to electronics and other sensitive components in space, affecting satellite operations. The sparsity and high variability in terms of intensity, duration, composition,and energy spectra of SEP events make them difficult to predict. The CLEAR Center will develop, test and validate a self-contained, modular (“plug and play”) framework that includes all major elements impacting SEPs in the inner heliosphere: 4π maps of photospheric magnetic fields, corona (1 − 20Rs), inner and middle heliosphere (0.1 AU to Jupiter’s orbit) plasma environment, magnetic connectivity with respect to the solar source, flare/CME initiation, SEP seed population, flare and shock acceleration, and energetic particle transport. In addition, the framework will be able to accommodate radiation interaction models, which will be used to study the penetration of spacecraft walls, radiation effects on the terrestrial magnetosphere, and the radiation doses received by human tissues.

How to cite: Zhao, L. and Gombosi, T. and the CLEAR Team: CLEAR – All-Clear SEP Forecast: A NASA Space Weather Center of Excellence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4457, https://doi.org/10.5194/egusphere-egu24-4457, 2024.

Our study covers a comprehensive analysis of Interplanetary Coronal Mass Ejections (ICMEs) across a wide distance from 0.25-5.42 AU and temporal range from 1975-2022. Our primary focus is a statistical examination of a variety of physical parameters for the structures within ICMEs, specifically the sheath and magnetic obstacle (MO). Our methodological approach integrates data merging from 13 individual ICME catalogs into a unified catalog, facilitating a comprehensive evaluation of in-situ measurements obtained from diverse spacecraft. This approach offers an opportunity to discern variances across different solar cycles. Our empirical findings provide intriguing insights. Notably, MOs preceded by a sheath exhibit a marked increase in size upon reaching 1 AU from the Sun. Furthermore, both structures, MO and sheath, experience a strong increase in size around 0.75 AU, correlating with a decrease in the measured density at this distance. Moreover, our analysis reveals a shift in the spatial positioning of material accumulation proximate to the sheath interface. This transformation suggests a potential transition in the underlying mechanism governing sheath formation, indicating a shift from externally driven to internally accumulated material processes.

How to cite: Larrodera, C. and Temmer, M.: Evolution of sheaths and magnetic obstacle from the inner to the outer heliosphere. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10017, https://doi.org/10.5194/egusphere-egu24-10017, 2024.

A coronal mass ejection (CME) is a significant release of plasma and accompanying magnetic field from the solar corona, and is one important source of severe space weather events. With the accumulation of CME observations by coronagraphs and the excellent performance of convolutional neural network (CNN) in image classification, fast and accurate prediction of the transit (arrival) time of CMEs became possible. In this study, we present a new prediction method utilizing both a deep learning framework and the physical characteristic of CMEs based on remote-sensing observations. In total, the initial and arrival data of 168 geo-effective CME events from 2000-2020 are collected for the study. A convolutional neural network model is trained with the coronagraph images of the events observed by SOHO/LASCO. The output of the trained CNN is further combined with the initial CME speed to carry out a linear fitting process. The comparison with the prediction results merely based on a CNN or a linear fitting by CME speed indicates that the hybrid model can improve the accuracy of CME arrival time prediction.

How to cite: Li, Y., Yang, Y., Shen, F., and Lin, R.: CME Transit Time Prediction Based on Coronagraph Observations and Machine Learning Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2230, https://doi.org/10.5194/egusphere-egu24-2230, 2024.

We revisit the observations of filament eruption,   extreme-ultraviolet (EUV) wave,  and  CME which originated from the active region (AR) NOAA 12887 on 28 October 2021. We analyze  a jet which initiated close to the flare loop footpoints, and its impact on neighboring loops. The event was observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) satellite at various wavebands and by the Solar TErrestrialRElations Observatory-Ahead (STEREO-A) with its Extreme-Ultraviolet Imager( EUVI) and COR1 instruments with a different view angle from SDO.

We show that the EUV-wave event consists of several waves as well as non-wave phenomena. The wave componentsinclude: the fast-mode part of the EUV wave event, creation of oscillations in nearby loops, and the appearance of wave trains. The non wave component consists of stationary fronts. We analyze selected oscillating loops and find that the periods of these oscillations range from 230 – 549 s. 

On the other hand the jet material lights loops which form a 3D null point. We evidence the existence of a  pseudo-streamer and its relationship with the CME (flux rope).

Our numerical MHD simulations with high resolution evidence  the existence of a pseudo-streamer, and its relationship with the CME (flux rope). We   catch the dynamic reconnection process between the flux rope and the pseudo-streamer and discuss the validity of our method compared to static methods.

How to cite: Schmieder, B., Guo, J., Devi, P., Chandra, R., Guo, Y., and Poedts, S.: A pseudo-streamer unveiled by a jet and its interaction with a CME, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3405, https://doi.org/10.5194/egusphere-egu24-3405, 2024.

Coronal Mass Ejections (CME) are the drivers of the most destructive space weather at Earth; therefore, determining their onset mechanism is of paramount importance for both space physics understanding and space weather prediction.  Two types of models for CME onset have been proposed: an ideal instability as in the kink or torus models, or magnetic reconnection as in the breakout or tether-cutting models. These two types are distinguished by the nature of the pre-eruption filament channel that powers the CME, a twisted flux rope in the case of the ideal mechanisms and a sheared arcade in the case of reconnection.  We describe two powerful new capabilities within the Space Weather Modeling Framework (SWMF) that enable the simulation of either ideal or reconnection driven CMEs. For ideal onset, we have developed and implemented a finite-beta extension of the well-known Titov-Demoulin twisted flux rope model. We present simulations using this capability and describe its application to event studies. For reconnection-driven onset we have developed and implemented the STITCH formalism, which efficiently captures the buildup of magnetic shear along a polarity inversion line by the process of helicity condensation.  We present simulations using this capability, as well, and describe its application to event studies. Furthermore, we discuss how these capabilities within SWMF will enable the community to simulate well-observed events with both ideal and reconnection onset, and by detailed comparison with the observations, finally determine the CME onset mechanism.

This work was supported by the NSF SHINE Program and the NASA Living With a Star Program.

How to cite: Antiochos, S., van der Holst, B., Gombosi, T., Sokolov, I., Zhao, L., and Dahlin, J.: Determining the CME Onset Mechanism , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13582, https://doi.org/10.5194/egusphere-egu24-13582, 2024.

Coronal Mass Ejections (CMEs) are the major source of space weather events, causing severe disturbance to Sun-Earth space environment. Since there are more and more space activities and facilities, it’s becoming increasingly significant to detect and track CMEs. We develop a new algorithm to automatically detect CMEs and derive CME’s kinematic parameters based on machine learning. Our method consists of three steps: Recognition, tracking and determination of parameters. First, we train a convolutional neural network (CNN) to classify images from SOHO LASCO coronagraph observation into two categories that contains CME(s) or not. Next, we apply Principal Component Analysis (PCA) algorithm and Otsu’s method to acquire binary-labelled CME regions. Then, we employ the track-match algorithm to track CME motion in time-series image sequence and finally determine CME kinematic parameters e.g., velocity, angular width (AW), and central position angle (CPA). The algorithm is validated on several CME events with different morphological characteristics. We compare the results with a manual CME catalog and automatic CME catalogs (including Computer Aided CME Tracking (CACTus), Solar Eruptive Event Detection System (SEEDS), CORonal Image Process method (CORIMP)). Our algorithm shows some advantages in the recognition of CME structure and the accuracy of the kinematic parameters. In the future, the algorithm is capable of being applied to initialize magnetohydrodynamic simulations to study the propagation characteristics of real CME events in the interplanetary space, and provide a more efficient prediction of CMEs' geo-effectiveness.

How to cite: Lin, R., Yang, Y., Shen, F., Pi, G., and Li, Y.: An Algorithm For Determination of CME Kinematic Parameters Based On Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1718, https://doi.org/10.5194/egusphere-egu24-1718, 2024.

One of the major challenges in space weather forecasting is to reliably predict the magnetic structure of interplanetary coronal mass ejections (ICMEs) in the near-Earth space. In the framework of global MHD modelling, several efforts have been made to model the CME magnetic field from Sun to Earth. However, it remains challenging to deduce a flux-rope solution that can reliably model the magnetic structure of a CME. Spheromaks are one of the models that are widely used to characterize the internal magnetic structure of a CME. However, recent studies show that spheromaks are prone to experience a large rotation when injected in the heliospheric domain which may affect the prediction efficacy of CME magnetic fields at 1 AU. Moreover, the fully inserted spheromaks do not have any legs attached to the Sun. In addition, due to the inherent topology of the spheromak, the in-situ signature may exhibit a double flux-rope-like profile not reproduced by standard locally cylindrical flux rope models. Aiming to study the dynamics of CMEs exhibiting different magnetic topologies, we implement a new flux-rope model in “European heliospheric forecasting information asset” (EUHFORIA). Our flux-rope model includes an initially force-free toroidal flux-rope that is embedded in the low-coronal magnetic field. The dynamics of the flux rope in the low and middle corona is solved by a non-uniform advection constrained by the observed kinematics of the event. This results in a global non-toroidal loop-like magnetic structure that locally manifests as a cylindrical structure. At heliospheric distances, the evolution is modeled as a MHD process using EUHFORIA. As proof of concept, we use this tool to two CME events. Comparing the model results with the in-situ magnetic field configuration of the ICME at 1 au, we find that the simulated magnetic field profiles of the flux-rope are in very good agreement with the in-situ observations. Therefore, the framework of toroidal model implementation as developed in this study could prove to be a major step-forward in forecasting the geo-effectiveness of CMEs.

How to cite: Sarkar, R., Pomoell, J., Kilpua, E., and Asvestari, E.: Integration of a Novel Flux Rope Model into Global MHD Simulations for Analyzing the Space Weather Effects of Coronal Mass Ejections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14401, https://doi.org/10.5194/egusphere-egu24-14401, 2024.