arXiv subjects

Stefaan Poedts

Publications and source records attributed to Stefaan Poedts.

At least 37 records · Page 2Linked to original sources

arXiv2025

Investigating the impact of the dynamic solar wind on the propagation of a coronal mass ejection with two models and multi-spacecraft measurements

Coronal mass ejections (CMEs) are the main drivers of disturbances in the solar heliosphere because they propagate and interact with the magnetic field of the solar wind. It is crucial to investigate the evolution of CMEs and their deformation for understanding the interaction between the solar wind and CMEs. We quantify the effect of the dynamic solar wind on the propagation of a CME in the heliosphere with a hydrodynamic plasma cloud-cone model and a linear force-free spheromak model at various locations in the heliosphere. We chose a CME event that launched on SOL2021-09-23T04:39:45 and was observed by multiple spacecraft, namely BepiColombo, Parker Solar Probe, Solar Orbiter, Stereo A and ACE. The solar wind was modelled in the steady and dynamic regimes in the Icarus model. The CME parameters were approximated for the selected event, and two CME models (spheromak and cone) were launched from the inner heliosphere boundary. The obtained synthetic in situ measurements were compared to the observed in situ measurements at all spacecraft. The internal magnetic field of the flux rope was better reconstructed by the spheromak model than by the cone CME model. The cone CME model maintained a nearly constant longitudinal angular extension while somewhat contracting in the radial direction. In contrast, the spheromak model contracted in the longitudinal direction while expanding in the radial direction. The CME sheath and magnetic cloud signatures were better reproduced at the four spacecraft clustered around the CME nose by the spheromak CME model. The dynamic solar wind caused a greater deceleration of the modelled CME than the steady-state solar wind solution. Because the background was homogeneous, the modelled CME properties were only mildly affected by the solar wind regime, however.

astro-ph.SR↗

arXiv2025

HelioFill: Diffusion-Based Model for EUV Reconstruction of the Solar Farside

The loss of STEREO-B in 2014 created a persistent blind spot in Extreme Ultraviolet (EUV) imaging of the solar farside. We present HelioFill, to the authors' knowledge, the first denoising-diffusion inpainting model that restores full-Sun EUV coverage by synthesizing the STEREO-B sector from Earth-side (SDO) and STEREO-A views. Trained on full-Sun maps from 2011-2014 (when SDO+STEREO-A+B provided 360 degrees coverage), HelioFill couples a latent diffusion backbone with domain-specific additions: spectral gating, confidence weighting, and auxiliary regularizers, to produce operationally suitable 304 Angstrom reconstructions. On held-out data, the model preserves the observed hemisphere with mean SSIM 0.871 and mean PSNR 25.56 dB, while reconstructing the masked hemisphere with mean SSIM 0.801 and mean PSNR 17.41 dB and reducing boundary error by approximately 21 percent (Seam L2) compared to a state-of-the-art diffusion inpainting model. The generated maps maintain cross-limb continuity and coronal morphology (loops, active regions, and coronal-hole boundaries), supporting synoptic products and cleaner inner-boundary conditions for coronal/heliospheric models. By filling observational gaps with observationally consistent EUV emission, HelioFill maintains continuity of full-Sun monitoring and complements helioseismic farside detections, illustrating how diffusion models can extend the effective utility of existing solar imaging assets for space-weather operations.

astro-ph.SR↗

arXiv2025

Flare energetics, CME launch and heliospheric propagation for the May 2024 events, as derived from ensemble MHD modelling

Many questions must be answered before understanding the relationship between the emerging magnetic flux through the solar surface and the extreme geoeffective events. The main ingredients for getting X-ray class flares and large interplanetary Coronal Mass Ejections (CMEs) are the build-up of electric current in the corona, the existence of magnetic free energy, magnetic energy/helicity ratio, twist, and magnetic stress in active regions (ARs). The upper limit of solar energy in the space research era, as well as the potential for experiencing superflares and extreme solar events, can be predicted using MHD simulations of CMEs. To address this problem, we consider the recent events of May 2024 and use three MHD models: 1) OHM ("Observationally driven High order scheme Magnetohydrodynamic code") for investigating the magnetic evolutions at a synthetic dipole structure. 2) TMF (time-dependent magneto-friction) for setting up an initial non-potential magnetic field in the active region. A zero-beta MHD model for tracing the magnetic evolution of active regions. 3) EUHFORIA (''European heliospheric forecasting information asset'') for interplanetary CME propagations. For the eruptive flares with CMEs, magnetic solar energy is computed along with data-constrained MHD simulations for the May 2024 events. We show the consistency between the data-initiated realistic simulation of the May 2024 big event and energy scalings from an idealised simulation of a bipolar eruption using OHM. The estimated free magnetic energy did not surpass $5.2 \times 10^{32}\;$erg. Good arrival time predictions ($<3$ hours) are achieved with the EUHFORIA simulation with the cone model. We note the interest in coupling all the chains of codes from the Sun to the Earth and developing different approaches to test the results.

astro-ph.SR↗

arXiv2025

Modelling gyrosynchrotron emission from coronal energetic electrons in a CME flux rope

Solar flares and coronal mass ejections (CMEs) can accelerate electrons, causing bursts such as type IV emissions in the solar radio continuum. Although radio spectroscopy is a powerful diagnostic tool for the corona, the origin and mechanisms of type IV bursts remain uncertain. In situ measurements can occasionally shed some light on these mechanisms, but they are limited in space and time. Sophisticated numerical modelling offers the best approach to improve our understanding of the physical processes involved. This research examines type IV radio bursts, exploring the effects of various electron distribution properties and CMEs on their generation and characteristics. To transcend idealised assumptions, we employ realistic, anisotropic electron distributions - obtained from particle transport simulations within complex magnetohydrodynamic (MHD) environments - as input for radio emission models. We use the 3D MHD model COCONUT to generate coronal background configurations, including a CME modelled as a modified Titov-Démoulin magnetic flux rope (MFR). These MHD simulations are used by the PARADISE particle transport code, which injects energetic electrons into the MFR and tracks their evolution. Finally, we feed the electron distributions and solar wind parameters into the Ultimate Fast Gyrosynchrotron (GS) Codes to compute radio emission along lines of sight. Electrons injected close to the MFR's central axis remain largely confined, producing a GS emission spectrum resembling observed type IV characteristics. Varying observer positions, CME properties, and spectral indices of the electron energy distributions modify the intensities and durations of the observed bursts. The strongest GS emission is observed to originate from the CME flanks. Our results indicate that GS emission is the major component in type IV spectra, although additional contributors cannot be ruled out.

astro-ph.SR↗

arXiv2025

SIP-IFVM: An observation-based magnetohydrodynamic model of coronal mass ejection

Currently, achieving a balance between computational efficiency, accuracy, and numerical stability in CME simulations, particularly in the sub-Alfv{'e}nic coronal region, remains a significant challenge. This paper aims to address the challenge by integrating observational data and developing advanced numerical algorithms, focusing on reproducing large-scale CME evolutions that are consistent with observations in the coronal region. Based on the recently developed fully implicit thermodynamic MHD coronal model (Wang et al. 2025a), we further use an observation-based RBSL flux rope to trigger a CME event during CR 2111. Additionally, we improve the temporal accuracy using a 2nd-order accurate ESDIRK2 method, with the intermediate stage solutions computed by the 2nd-order accurate BDF2 pseudo-time marching method. To enhance the numerical stability of ESDIRK2, we apply approximate linearisation in the implicitly solved intermediate stages. Furthermore, we adjust the time-evolving magnetic field B1 to zero at the end of each physical time step to further validate the extended magnetic field decomposition approach proposed by (Wang et al. 2025a). It is noticed that the model successfully reproduces the CME evolution consistent with white-light coronagraph observations, enables faster-than-real-time CME propagation simulations from solar surface to 0.1 AU using only a few dozen CPU cores on approximately 1 million grid cells, and remains numerically stable in CME simulations involving low-\b{eta} regions. The simulation results show that this novel MHD coronal model, combined with an observation-based magnetic flux rope, is sufficiently numerically stable and computationally efficient to reproduce real CME events propagating through the sub-Alfv{é}nic coronal region. Thus, the observation-based CME model is well suited for practical applications in daily space weather forecasting.

astro-ph.SR↗

arXiv2025

SIP-IFVM: A time-evolving coronal model with an extended magnetic field decomposition strategy

Time-evolving magnetohydrodynamic (MHD) coronal modeling, driven by a series of time-dependent photospheric magnetograms, represents a new generation of coronal simulations. This approach offers greater realism compared to traditional coronal models constrained by a static magnetogram. However, its practical application is seriously limited by low computational efficiency and poor numerical stability. Therefore, we propose an extended magnetic field decomposition strategy and implement it in the implicit MHD model to develop a coronal model that is both efficient and numerically stable enough for simulating the long-term evolutions of the global corona. The traditional decomposition strategies split the magnetic field into a time-invariant potential field and a time-dependent component $\mathbf{B}_1$. It works well for quasi-steady-state coronal simulations where $\left|\mathbf{B}_1\right|$ is typically small. However, as the inner-boundary magnetic field evolves, $\left|\mathbf{B}_1\right|$ can grow significantly larger and its discretization errors often lead to nonphysical negative thermal pressure, ultimately causing the code to crash. In this paper, we mitigate such undesired situations by introducing a temporally piecewise-constant variable to accommodate part of the non-potential field and remain $\left|\mathbf{B}_1\right|$ consistently small throughout the simulations. We incorporate this novel magnetic field decomposition strategy into our implicit MHD coronal model and apply it to simulate the evolution of coronal structures within 0.1 AU over two solar-maximum Carrington rotations. The results show that this coronal model effectively captures observations and performs more than 80 times faster than real time using only 192 CPU cores, making it well-suited for practical applications in simulating the time-evolving corona.

astro-ph.SR↗

arXiv2025

Efficient magnetohydrodynamic modelling of the time-evolving corona by COCONUT

Compared to quasi-steady-state corona models that are constrained by a time-invariant magnetogram over a CR period, time-evolving corona models driven by time-varying photospheric magnetograms are more realistic and can maintain more useful information to accurately describe solar wind evolution and forecast CME propagation. This paper demonstrate that time-evolving corona simulations can be performed efficiently and accurately using an implicit method with relatively large time steps. We also evaluate differences between coronal structures captured by time-evolving and quasi-steady simulations over a CR period during solar minimum. We used a series of hourly updated photospheric magnetograms to drive the evolution of coronal structures from the solar surface to $25\; R_s$ during two CRs around the 2019 eclipse in an inertial coordinate system. We compare the time-evolving and quasi-steady simulations to demonstrate that the differences in these two types of coronal modelling can be obvious even for a solar minimum. The relative differences in radial velocity and density can be over $15 \%$ and $25 \%$ at 20$\;R_s$ during one CR period. We also evaluated the impact of time steps on the simulation results. Using a time step of approximately 10 minutes balances efficiency and necessary numerical stability and accuracy for time-evolving corona simulations around solar minima, with coronal evolution during a full CR simulated within only 9 hours (using 1080 CPU cores for 1.5M grid cells). The simulation results demonstrate that time-evolving MHD coronal simulations can be performed efficiently and accurately using an implicit method, offering a more realistic alternative to quasi-steady-state simulations. The fully implicit time-evolving corona model thus promises to simulate the time-evolving corona accurately in practical space weather forecasting.

astro-ph.SR↗

arXiv2025

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. The inner boundary conditions, prescribed at 0.1 AU for the heliospheric model, are updated time-dependently throughout the simulation. The coronal model is computed repeatedly for selected magnetograms. The particle sampling within MPI-AMRVAC is extended to handle stretched spherical grid information. 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 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.

astro-ph.SR↗

arXiv2024

Constraining the inner boundaries of COCONUT through plasma \b{eta} and Alfvén speed

Space weather modelling has been gaining importance due to our increasing dependency on technology sensitive to space weather effects, such as satellite services, air traffic and power grids. Improving the reliability, accuracy and numerical performance of space weather modelling tools, including global coronal models, is essential to develop timely and accurate forecasts and to help partly mitigate the space weather threat. Global corona models, however, require accurate boundary conditions, for the formulations of which we have very limited observational data. Unsuitable boundary condition prescriptions may lead to inconsistent features in the solution flow field and spoil the code's accuracy and performance. In this paper, we develop an adjustment to the inner boundary condition of the COCONUT global corona model to better capture the dynamics over and around the regions of stronger magnetic fields by constraining the plasma \b{eta} and the Alfvén speed. Using data from solar observations and solar atmospheric modelling codes such as Bifrost, we find that the baseline homogeneous boundary condition formulations for pressure and density do not capture the plasma conditions physically accurately. We develop a method to adjust these prescribed pressure and density values by placing constraints on the plasma \b{eta} and the Alfvén speed that act as proxies. We demonstrate that we can remove inexplicable fast streams from the solution by constraining the maximum Alfvén speed and the minimum plasma \b{eta} on the boundary surface. We also show that the magnetic topology is not significantly affected by this treatment otherwise. The presented technique shows the potential to ease the modelling of solar maxima, especially removing inexplicable features while, at the same time, not significantly affecting the magnetic field topology around the affected regions.

physics.space-ph↗

arXiv2024

Cross-Field Diffusion Effects on Particle Transport in a Solar Coronal Flux Rope

Solar energetic particles (SEPs) associated with solar flares and coronal mass ejections (CMEs) are key agents of space weather phenomena, posing severe threats to spacecraft and astronauts. Recent observations by Parker Solar Probe (PSP) indicate that the magnetic flux ropes of a CME can trap energetic particles and act as barriers, preventing other particles from crossing. In this paper, we introduce the novel COCONUT+PARADISE model to investigate the confinement of energetic particles within a flux rope and the effects of cross-field diffusion (CFD) on particle transport in the solar corona, particularly in the presence of a CME. Using the global magnetohydrodynamic coronal model COCONUT, we generate background configurations containing a CME modeled as a Titov-Démoulin flux rope (TDFR). We then utilize the particle transport code PARADISE to inject monoenergetic 100 keV protons inside one of the TDFR legs near its footpoint and evolve the particles through the COCONUT backgrounds. To study CFD, we employ two different approaches regarding the perpendicular proton mean free path (MFP): a constant MFP and a Larmor radius-dependent MFP. We contrast these results with those obtained without CFD. While particles remain fully trapped within the TDFR without CFD, we find that even relatively small perpendicular MFP values allow particles on the outer layers to escape. In contrast, the initially interior trapped particles stay largely confined. Finally, we highlight how our model and this paper's results are relevant for future research on particle acceleration and transport in an extended domain encompassing both the corona and inner heliosphere.

astro-ph.SR↗

arXiv2024

Graph-GIC: A Smart and Parallelized Geomagnetically Induced Current Modelling Algorithm Based on Graph Theory for Space Weather Applications

Geomagnetically Induced Current (GIC) refers to the electromagnetic response of the Earth and its conductive modern infrastructures to space weather and would pose a significant threat to high-voltage power grids designed for the alternative current operation. To assess the impact of space weather on the power grid, one needs to calculate the GIC on a national or continental scale. In this study, we developed a smart and parallelized GIC modelling algorithm, Graph GIC. This algorithm deploys a graph representing a power grid in a single-line diagram, in which substations/transformers act as nodes and transmission lines as edges. With these denotations, a power grid and its electric parameters are mathematically represented with an adjacency matrix and an admittance matrix. We used sparse matrix and parallelisation techniques to expedite the intensive computation in cases of large-scale power grids. The Graph GIC was validated with a benchmark grid, applied to the GIC calculation of the 500 kV power grid of Guangdong, China, and conducted preliminary analysis on the grid's susceptibility to geomagnetic storms. The Graph GIC algorithm has the advantage of an intuitive and highly scalable graph representation of a power grid at any scale. It achieves high-accuracy calculation and a speedup of about 18 times after parallelisation. This algorithm could be applied to assess the impact of space weather on a power grid up to continental scales and could be incorporated into global space weather modelling frameworks.

physics.space-ph↗

arXiv2024

The effect of data-driving and relaxation model on magnetic flux rope evolution and stability

We investigate the effect of data-driving on flux rope eruptivity in magnetic field simulations by analysing fully data-driven modelling results of active region (AR) 12473 and AR11176, as well as preforming relaxation runs for AR12473 (found to be eruptive). Here, the driving is switched off systematically at different time steps. We analyse the behaviour of fundamental quantities, essential for understanding the eruptivity of magnetic flux ropes (MFRs). The data-driven simulations are carried out with the time-dependent magnetofrictional model (TMFM) for AR12473 and AR11176. For the relaxation runs, we employ the magnetofrictional method (MFM) and a zero-beta magnetohydrodynamic (MHD) model to investigate how significant the differences between the two relaxation procedures are when started from the same initial conditions. To determine the eruptivity of the MFRs, we calculate characteristic geometric properties, such as the cross-section, MFR height along with stability parameters, such as MFR twist and the decay index. For eruptive cases, we investigate the effect of sustained driving beyond the point of eruptivity on the MFR properties. We find that the fully-driven AR12473 MFR is eruptive while the AR11176 MFR is not. For the relaxation runs, we find that the MFM MFRs are eruptive when the driving is stopped around the flare time or later, while the MHD MFRs show eruptive behaviour even if the driving is switched off one and a half days before the flare occurs. We find that characteristic MFR properties can vary greatly even for the eruptive cases of different relaxation simulations. The results suggest that data driving can significantly influence the evolution of the eruption, with differences appearing even when the relaxation time is set to later stages of the simulation when the MFRs have already entered an eruptive phase.

astro-ph.SR↗

arXiv2024

Magnetic connectivity from the Sun to the Earth with MHD models I. Impact of the magnetic modelling for connectivity validation

This article discusses the magnetic connectivity between the Sun and the Earth, which is essential for understanding solar wind and space weather events. Due to limited direct observations, reliable simulations are necessary. The most commonly used method is the two-step ballistic method, but it has many free parameters that affect the results. The authors propose a method based on self-consistent magnetohydrodynamic (MHD) models. They combine the COCONUT coronal model with the EUHFORIA heliospheric model to compute magnetic field lines from the Earth to the Sun and quantify spatial and temporal uncertainties. To validate their method, they analyze four events associated with high-speed streams from well-identified coronal holes. The results show partial overlap with the assumed coronal holes of origin, ranging from 19% to 100% depending on the event. They also examine the magnetic polarity observed on Earth, finding that MHD simulations provide a good polarity estimation, with agreement ranging from 36% to 69% across the events. Spatial and temporal uncertainties explain the mixed results for some cases. MHD models appear more effective during periods of maximum solar activity due to the latitudinal extent of the heliospheric current sheet (HCS). The authors conclude that MHD models offer results as good as the two-step ballistic method, with potential for improvement as more critical physics are integrated into the models.

astro-ph.SR↗

arXiv2024

Recent advances in solar data-driven MHD simulations of the formation and evolution of CME flux ropes

Filament eruptions and coronal mass ejections are physical phenomena related to magnetic flux ropes carrying electric current. A magnetic flux rope is a key structure for solar eruptions, and when it carries a southward magnetic field component when propagating to the Earth. It is the primary driver of strong geomagnetic storms. As a result, developing a numerical model capable of capturing the entire progression of a flux rope, from its inception to its eruptive phase, is crucial for forecasting adverse space weather. The existence of such flux ropes is revealed by the presence of sigmoids in active regions or hot channels by observations from space and ground instruments. After proposing cartoons in 2D, potential, linear, non-linear-force-free-field (NLFFF) and non-force-free-field (NFFF) magnetic extrapolations, 3D numerical magnetohydrodynamic (MHD) simulation models were developed, first in a static configuration and later dynamic data-driven MHD models using high resolution observed vector magnetograms. This paper reviews a few recent developments in data-driven mode, such as the time-dependent magneto-frictional (TMF) and thermodynamic magnetohydrodynamic (MHD) models. Hereafter, to demonstrate the capacity of these models to reveal the physics of observations, we present the results for three events explored in our group: 1. the eruptive X1.0 flare on 28 October 2021; 2. the filament eruption on 18 August 2022; and 3. the confined X2.2 flare on 6 September 2017. These case studies validate the ability of data-driven models to retrieve observations, including the formation and eruption of flux ropes, 3D magnetic reconnection, CME three-part structures and the failed eruption. Based on these results, we provide some arguments for the formation mechanisms of flux ropes, the physical nature of the CME leading front, and the constraints of failed eruptions.

astro-ph.SR↗

arXiv2024

Density-gradient-driven drift waves in the solar corona

It has been suggested that under solar coronal conditions, drift waves may contribute to coronal heating. Specific properties of the drift waves to be expected in the solar corona have, however, not yet been determined using more advanced numerical models. We investigate the linear properties of density-gradient-driven drift waves in the solar coronal plasma using gyrokinetic ion-electron simulations with the gyrokinetic code GENE, solving the Vlasov-Maxwell equations in five dimensions assuming a simple slab geometry. We determine the frequencies and growth rates of the coronal density gradient-driven drift waves with changing plasma parameters, such as the electron \b{eta} , the density gradient, the magnetic shear and additional temperature gradients. To investigate the influence of the finite Larmor radius effect on the growth and structure of the modes, we also compare the gyrokinetic simulation results to those obtained from drift-kinetics. In most of the investigated conditions, the drift wave has positive growth rates that increase with increasing density gradient and decreasing \b{eta} . In the case of increasing magnetic shear, we find that from a certain point, the growth rate reaches a plateau. Depending on the considered reference environment, the frequencies and growth rates of these waves lie on the order of 0.1 mHz to 1 Hz. These values correspond to the observed solar wind density fluctuations near the Sun detected by WISPR, currently of unexplained origin. As a next step, nonlinear simulations are required to determine the expected fluctuation amplitudes and the plasma heating resulting from this mechanism.

astro-ph.SR↗

arXiv2024

Toroidal modified Miller-Turner CME model in EUHFORIA: II. Validation and comparison with flux rope and spheromak

Rising concerns about the impact of space weather-related disruptions demand modelling and reliable forecasting of coronal mass ejection (CME) impacts. In this study, we demonstrate the application of the modified Miller-Turner (mMT) model implemented in EUropean Heliospheric FORecasting Information Asset (EUHFORIA), to forecast the geo-effectiveness of observed coronal mass ejection (CME) events in the heliosphere. The goal is to develop a model that not only has a global geometry to improve overall forecasting but is also fast enough for operational space weather forecasting. We test the original full torus implementation and introduce a new three-fourth Torus version called the Horseshoe CME model. This new model has a more realistic CME geometry, and it overcomes the inaccuracies of the full torus geometry. We constrain the torus geometrical and magnetic field parameters using observed signatures of the CMEs before, during, and after the eruption. The assessment of the model's capability to predict the most important Bz component is performed using the advanced Dynamic Time Warping technique. The Horseshoe model prediction of CME arrival time and geo-effectiveness for both validation events compare well to the observations and are weighed with the results obtained with the spheromak and FRi3D models that were already available in EUHFORIA. The runtime of the Horseshoe model simulations is close to that of the spheromak model, which is suitable for operational space weather forecasting. Yet, the capability of the magnetic field prediction at 1~AU of the Horseshoe model is close to that of the FRi3D model. In addition, we demonstrate that the Horseshoe CME model can be used for simulating successive CMEs in EUHFORIA, overcoming a limitation of the FRi3D model.

physics.space-ph↗

arXiv2024

The operationally ready full three-dimensional magnetohydrodynamic (3D MHD) model from the Sun to Earth: COCONUT+Icarus

Solar wind modelling has become a crucial area of study due to the increased dependence of modern society on technology, navigation, and power systems. Accurate space weather forecasts can predict upcoming threats to Earth's geospace. In this study, we examine a novel full magnetohydrodynamic (MHD) chain from the Sun to Earth. The goal of this study is to demonstrate the capabilities of the full MHD modelling chain from the Sun to Earth by finalising the implementation of the full MHD coronal model into the COolfluid COroNa UnsTructured (COCONUT) model and coupling it to the MHD heliospheric model Icarus. The resulting coronal model has significant advantages compared to the pre-existing polytropic alternative, as it models a more realistic bi-modal wind, which is crucial for heliospheric studies. In this study, only thermal conduction, radiative losses, and approximated coronal heating function were considered in the energy equation. A realistic specific heat ratio was applied. The output of the coronal model was used to onset the 3D MHD heliospheric model Icarus. A minimum solar activity case was chosen as the first test case for the full MHD model. The numerically simulated data in the corona and the heliosphere were compared to observational products. We present a first attempt to obtain the full MHD chain from the Sun to Earth with COCONUT and Icarus. The coronal model has been upgraded to a full MHD model for a realistic bi-modal solar wind configuration. The approximated heating functions have modelled the wind reasonably well, but simple approximations are not enough to obtain a realistic density-speed balance or realistic features in the low corona and farther, near the outer boundary. The full MHD model was computed in 1.06 h on 180 cores of the Genius cluster of the Vlaams Supercomputing Center, which is only 1.8 times longer than the polytropic simulation.

astro-ph.SR↗

arXiv2024

Multi spacecraft study with the Icarus model: Modelling the propagation of CMEs to Mercury and Earth

Coronal Mass Ejections (CMEs) are the main drivers of the disturbances in interplanetary space. Understanding the CME interior magnetic structure is crucial for advancing space weather studies. Assessing the capabilities of a numerical heliospheric model is crucial, as understanding the nature and extent of its limitations can be used for improving the model and the space weather predictions based on it. The present paper aims to test the capabilities of the recently developed heliospheric model Icarus and the linear force-free spheromak model that has been implemented in it. To validate the Icarus space weather modeling tool, two CME events were selected that were observed by two spacecraft located near Mercury and Earth, respectively. This enables testing the heliospheric model computed with Icarus at two distant locations. The source regions for the CMEs were identified, and the CME parameters were determined and later optimized. Different adaptive mesh refinement levels were applied in the simulations to assess its performance by comparing the simulation results to in-situ measurements. The first CME event erupted on SOL2013-07-09T15:24. The modeled time series were in good agreement with the observations both at MESSENGER and ACE. The second CME event started on SOL2014-02-16T10:24 and was more complicated, as three CME interactions occurred in this event. It was impossible to recover the observed profiles without modeling the other two CMEs that were observed, one before the main CME and one afterward. For both CME studies, AMR level 3 was sufficient to reconstruct small-scale features near Mercury, while at Earth, AMR level 4 was necessary due to the radially stretched grid that was used.

astro-ph.SR↗