Solar Observations Research Articles

Connecting energetic electrons at the Sun and in the heliosphere through X-ray and radio diagnostics

Solar flares release huge amounts of energy, a considerable part of which is channeled into particle acceleration in the lower corona. Hard X-ray (HXR) emissions are used to diagnose the accelerated electrons that bombard the chromosphere, while type III radio bursts result from energetic electron beams propagating through the corona and into interplanetary space. The Solar Orbiter mission, launched in 2020, aims to link solar flare remote observations with heliospheric events, thus producing useful observations for our understanding of particle acceleration and propagation from the Sun to the heliosphere. While both hard X-Ray and radio emissions result from flare-accelerated electrons, their relationship is not straightforward. By comparing the evolution of the X-ray emitting sites and the timing of type III bursts, our aim is to determine the conditions for associations between X-ray flares and interplanetary (IP) type III bursts. We analyzed 15 interplanetary type III bursts that are associated with HXR bursts in the first available period for simultaneous X-ray/radio observations of type III bursts from Solar Orbiter (using the RPW and STIX instruments). X-ray imaging was performed around the onset of the type III bursts, complemented by EUI 174 A images to assess the magnetic configuration of the corona. All 15 X-ray flares originated from the same active region on the west limb as observed by Solar Orbiter. In each of the events, a change in X-ray source morphology occurred shortly (<6 minutes) before the onset of type III radio bursts, indicating a change in the electron acceleration region preceding the radio emission. Considering the delays observed between the two emissions, these findings describe complex scenarios with multiple reconnection episodes, some of which may allow accelerated electrons to escape into IP space when open magnetic field lines are involved (interchange reconnection). In some cases, X-ray source elongations toward open field lines in the UV were observed, reinforcing this idea.

PAStar : A model for stellar surface from the Sun to active stars

The characterisation of exoplanets requires a good description of the host star. Stellar activity acts as a source of noise, which can alter planet radii as derived from the transit depth or atmospheric characterisation. Here, we propose PAStar a model to describe photospheric activity in the form of spots and faculae, which could be applied to a wide range of stellar observations, from photometric to spectroscopic time series, making it possible to correctly extract planetary and stellar properties. The adopted stellar atmosphere is a combination of three components: the quiet photosphere, spots, and faculae. The model takes into account the effects of star inclination and Doppler shifts due to stellar rotation and limb darkening, which is independent for each component. Several synthetic products have been presented to show the capabilities of the model. The model is able to retrieve the input surface-inhomogeneity configuration through photometric or spectroscopic observations. The model has been validated against optical solar data and compared to alternative stellar surface activity models; for example SOAP code . The Sun is a unique laboratory to test stellar models because of the possibility to unambiguously relate flux variations to surface inhomogeneities' configuration. This validation has been done by analysing a photometric time series from the Variability of Solar Irradiance and Gravity Oscillations (VIRGO) photometer on-board Solar and Heliospheric Observatory (SOHO) mission. Results have been compared to real solar images from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) to confirm the goodness of the results in terms of surface inhomogeneities' positions and dimensions. The description of stellar activity is a fundamental step in several astrophysical contexts and it is covered by the method we present. Our model offers a flexible and valuable tool to describe the activity of stars when it is dominated by spots and faculae.

Research on the Earth Reflected Solar Spectral Radiation Observation System Based on the Lagrange L1 Point of the Earth–Moon System

We propose an observation system based on the Lagrange L1 point of the Earth–Moon system to observe solar spectral radiation reflected from the Earth, enabling continuous hyperspectral observation of the Earth’s hemisphere. The system can observe the solar spectral radiation reflected by the Moon, with its data applicable to on-orbit spectral radiation calibration. In this paper, the spectral irradiance at the entrance pupil of the Earth spectral radiation observation system (ESROS) is analyzed, and the optical design of the ESROS is introduced. An off-axis two-mirror telescope system, a coupling system of a microlens array and a fiber bundle, and an optical splitting system based on concave grating are used to achieve the full field of view hyperspectral splitting and miniaturization of the instrument. Finally, the stray radiation suppression of the instrument is introduced. The results show that the spectral resolution of the system is better than 5 nm in the 380–1000 nm band, and the spectral resolution is better than 10 nm in the 1000–1700 nm band. When observing the Earth, the signal-to-noise ratio is greater than 200. The external stray radiation suppression reaches the order of 10−9. The ESROS will provide crucial data support for researching global energy balance, climate change, and the spectral characteristics of exoplanets, facilitating planetary science and the exploration of extraterrestrial life.

Spectral resolution effects on the information content in solar spectra

When interpreting spectropolarimetric observations of the solar atmosphere, wavelength variations in the emergent intensity and polarization translate into information on the depth stratification of physical parameters such as the temperature, velocity, and magnetic field. Resolving the fine details in the shapes of the spectral lines and their polarization gives us the capability to resolve small-scale depth variations in these physical parameters. With the advent of large-aperture solar telescopes and the development of state-of-the-art instrumentation, the requirements on spectral resolution have become a prominent question. We aim to quantify how the information content contained in a representative set of polarized spectra of photospheric spectral lines depends on the spectral resolution and spectral sampling of that spectrum. We used a state-of-the-art numerical simulation of a sunspot and the neighboring quiet Sun photosphere to synthesize polarized spectra of magnetically sensitive neutral iron lines. We then applied various degrees of spectral degradation to the synthetic spectra and analyzed the impact on its dimensionality using principal component analysis and the wavelength power spectrum using wavelet decomposition. Finally, we applied the Stokes Inversion based on Response functions (SIR) code to the degraded synthetic data to assess the effect of spectral resolution on the inferred parameters. We find that the dimensionality of the Stokes spectra and the power contained in the small spectral scales significantly change with the spectral resolution. We find that regions with strong magnetic fields where convection is suppressed have more homogeneous atmospheres and produce less complex Stokes profiles. On the other hand, regions with strong gradients in the physical quantities give rise to more complex Stokes profiles that are more affected by spectral degradation. The degradation also makes the inversion problem more ill-defined, so inversion models with a larger number of free parameters overfit and give wrong estimates. The impact of spectral degradation in the interpretation of solar spectropolarimetric observations depends on multiple factors, including the spectral resolution, noise level, line spread function (LSF) shape, complexity of the solar atmosphere, and degrees of freedom in our inversion methods. To mitigate this impact, incorporating a good estimation of the LSF into the inversion process is recommended. Having a finely sampled spectrum may be more beneficial than achieving a higher signal-to-noise ratio per wavelength bin. Considering the inclusion of different spectral lines that can counter these effects, and calibrating the effective degrees of freedom in modeling strategies, are also important considerations. These strategies are crucial for the accurate interpretation of such observations and have the potential to offer more cost-effective solutions.

Fine structuring of slow magnetoacoustic wave periods in a solar coronal fan

Abstract Propagating slow magnetoacoustic waves have long been observed in the corona and their use for magnetohydrodynamic seismology is growing. While these waves are thought to be generated by lower atmospheric oscillations, the exact mechanisms behind their generation and propagation remain unclear. This study aims to investigate the fine structure and drivers of slow waves through high-resolution solar observations. We observed slow magnetoacoustic waves with three distinct periodicities along sunspot-anchored coronal fan feathers using data from the Atmospheric Imaging Assembly. The waves were tracked for three hours in active region 13100 on September 19, 2022. Time-distance analysis was used to determine wave periods and projected phase speeds, and Fourier analysis for period intensity maps. We detect distinct periods of 3.06 ± 0.04, 2.47 ± 0.02, and 2.82 ± 0.02 minutes in three feathers of a coronal fan. Increased intensity of chromospheric oscillations with the same distinct periods was observed in the 304 Å channel in the umbral region where the feathers are anchored, which suggests that those locations could be footpoints of the specific feathers. These results indicate that propagating slow waves exhibit fine structuring in their oscillation periods. The specific period is a unique signature of each feather, which can be utilised for seismological diagnostics of the local coronal magnetic geometry, in stereoscopic observations.

CRIRES+ and ESPRESSO Reveal an Atmosphere Enriched in Volatiles Relative to Refractories on the Ultrahot Jupiter WASP-121b

One of the outstanding goals of the planetary science community is to measure the present-day atmospheric composition of planets and link this back to formation. As giant planets are formed by accreting gas, ices, and rocks, constraining the relative amounts of these components is critical to understand their formation and evolution. For most known planets, including the solar system giants, this is difficult as they reside in a temperature regime where only volatile elements (e.g., C, O) can be measured, while refractories (e.g., Fe, Ni) are condensed to deep layers of the atmosphere where they cannot be remotely probed. With temperatures allowing for even rock-forming elements to be in the gas phase, ultrahot Jupiter atmospheres provide a unique opportunity to simultaneously probe the volatile and refractory content of giant planets. Here, we directly measure and obtain bounded constraints on the abundances of volatile C and O as well as refractory Fe and Ni on the ultrahot giant exoplanet WASP-121b. We find that ice-forming elements are comparatively enriched relative to rock-forming elements, potentially indicating that WASP-121b formed in a volatile-rich environment much farther away from the star than where it is currently located. The simultaneous constraint of ice and rock elements in the atmosphere of WASP-121b provides insights into the composition of giant planets otherwise unattainable from solar system observations.

Radial evolution of interplanetary coronal mass ejection-associated particle acceleration observed by Solar Orbiter and ACE

On 2022 March 10 a coronal mass ejection erupted from the Sun, resulting in Solar Orbiter observations at 0.45 au of both dispersive solar energetic particles arriving prior to the interplanetary coronal mass ejection (ICME) and locally accelerated particles near the ICME-associated shock structure as it passed the spacecraft on 2022 March 11. This interplanetary shock was later detected on 2022 March 14 by the Advanced Composition Explorer (ACE), which was radially aligned with Solar Orbiter, at 1 au. Ion composition data from both spacecraft — via the Solar Orbiter Energetic Particle Detector/ Suprathermal Ion Spectrograph (EPD/SIS) and the Ultra Low Energy Isotope Spectrometer (ULEIS) on ACE — allowed for an in-depth analysis of the radial evolution of species-dependent ICME-driven shock-associated acceleration processes for this event. We present a study of the ion spectra observed at 0.45 and 1 au during both the gradual solar energetic particle and energetic storm particle phases of the event. The shapes of the spectra seen at each spacecraft differ significantly, likely due to the varying shock geometry: Solar Orbiter spectra tend to lack spectral breaks, and the higher-energy portions of the ACE spectra have a comparable average flux to the Solar Orbiter spectra. Through an analysis of rigidity effects on the spectral breaks observed by ACE, we conclude that the 1 au observations were largely influenced by a suprathermal pool of $ He $ ions that were enhanced due to propagation along a stream interaction region that was interacting with the ICME at the times of observation.

Solar shape variations across cycles 24 and 25: Observations from 2010 to 2023

The longest continuous time-series of solar oblateness measurements, initiated in 2010 and still ongoing, has been obtained from data collected by the Helioseismic Magnetic Imager (HMI) aboard NASA's Solar Dynamics Observatory (SDO). Based on HMI data, we developed two methods for determining the solar oblateness at 617.33\,nm in the continuum . The first method involves determining solar oblateness using HMI solar disk images and limb observations from twenty-three SDO satellite roll calibration maneuvers between 2010 and 2023 . Through meticulous analysis of these observation sequences, we obtained a precise measurement of solar oblateness using this technique, yielding a value of 9.02 (pm 0.72)times 10$^ $ (6.28pm 0.50\,kilometers), unaffected by brightness contamination from sunspots and magnetically induced excess emission. We also verified the polarization independence of light, showing consistent HMI solar oblateness measurements across Stokes states. Interestingly, our solar oblateness time-series, based on HMI solar disk images and limb observations, seems to be in anti-phase with solar activity. The second method we used relies on determining solar oblateness from HMI helioseismic inference of internal rotation. With this approach, we obtained a solar oblateness of 8.40 (pm 0.02)times 10$^ $ (5.85pm 0.01 kilometers) with a variation in phase with solar activity (0.05times 10$^ $ (0.04\,kilometers at 1\,sigma ) over an 11--year sunspot cycle). This outcome is troubling as it conflicts with our results obtained from the HMI solar limb observations

HESPERIA REleASE+: Improving Solar Proton Event Forecasting by Means of Automated Recognition of Type‐III Radio Bursts

AbstractThis work reports on an attempt toward improving the Relativistic Electron Alert System for Exploration (REleASE): the occurrence of a type‐III radio burst as a precondition for a REleASE forecast. REleASE forecasts are based on the detection of early arrival of near‐relativistic electrons ahead of more hazardous protons from Solar Energetic Particle (SEP) events. The goal is to allow astronauts on a Lunar or Mars mission sufficient advance warning to reach a radiation shelter to minimize radiation dose exposure. We test a new system that sets a condition of the occurrence of a type‐III radio burst, thus adding independent evidence of particle escape from the Sun, with the aim of reducing known sources of false‐alarms of the existing REleASE system. The High Energy Solar Particle Events foRecastIng and Analysis (HESPERIA) REleASE+ system, which takes advantage of availability of real‐time solar radio observations during the passage of STEREO‐A by Earth in 2023, has now been incorporated in the HESPERIA framework. We discuss the techniques used for automatic detection of type‐III radio bursts preparing for its real‐time implementation, the determination of selection criteria for type‐III bursts that are candidates for solar proton events in the Earth‐moon system, and first results of the combined system.

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

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

Cosmic-Ray North–South Anisotropy: Rigidity Spectrum and Solar Cycle Variations Observed by Ground-based Muon Detectors

The north–south (NS) anisotropy of galactic cosmic rays (GCRs) is dominated by a diamagnetic drift flow of GCRs in the interplanetary magnetic field (IMF), allowing us to derive key parameters of cosmic-ray propagation, such as the density gradient and diffusion coefficient. We propose a new method to analyze the rigidity spectrum of GCR anisotropy and reveal a solar cycle variation of the NS anisotropy’s spectrum using ground-based muon detectors in Nagoya, Japan, and Hobart, Australia. The physics-based correction method for the atmospheric temperature effect on muons is used to combine the different-site detectors free from local atmospheric effects. NS channel pairs in the multidirectional muon detectors are formed to enhance sensitivity to the NS anisotropy, and in this process, general graph matching in graph theory is introduced to survey optimized pairs. Moreover, Bayesian estimation with the Gaussian process allows us to unfold the rigidity spectrum without supposing any analytical function for the spectral shape. Thanks to these novel approaches, it has been discovered that the rigidity spectrum of the NS anisotropy is dynamically varying with solar activity every year. It is attributed to a rigidity-dependent variation of the radial density gradient of GCRs based on the nature of the diamagnetic drift in the IMF. The diffusion coefficient and mean free path length of GCRs as functions of the rigidity are also derived from the diffusion–convection flow balance. This analysis expands the estimation limit of the mean free path length into the ≤200 GV rigidity region from the <10 GV region achieved by solar energetic particle observations.

Deep Learning Insights Into Ionospheric Sporadic E Irregularities Under Different Solar Activity Conditions

AbstractSolar activity profoundly modulates many atmospheric coupling systems, particularly the morphology of the ionospheric irregularities, which is crucial for reliable radio communication. However, the understanding of its long‐term response behavior under different solar activity conditions remains limited, and the exact evolutionary mechanisms of global scale ionospheric coupling system remain poorly constrained. Here we initially show from 2007 to 2018, the weak ionospheric sporadic E scintillation in high latitude regions experienced intensification corresponding with periods of high solar activity. Subsequently, we extend a deep learning model framework called SELF‐ANN proposed by Tian to further clarify the underlying relationship between solar activity and ionospheric irregularities. Compared to SELF‐ANN, we expand the scope of analysis to include data spanning from 2007 to 2018, thus broadening the investigation into the impacts of solar variability. Using long‐term solar activity data and observations of the ionospheric E region irregularity from COSMIC RO, this model was trained to provide solar‐dependent ionospheric morphology. Based on the model, we have successfully achieved high‐precision modeling of weak ionospheric E region irregularities, which commonly occur and are challenging to detect with ionosondes, under different solar activity conditions. Quantitatively, the model achieves a mean absolute error of 0.004, coupled with a Spearman's R value of 0.589 for weak scintillation. Ionospheric reconstructions under different solar activity conditions can improve the understanding of ionospheric evolutionary mechanisms and underscore the importance of incorporating solar variations into ionosphere changes forecasting to ensure the development of future reliable communications.

Butterfly Diagram and Other Properties of Plage Areas from Kodaikanal Ca ii K Photographs Covering 1904 – 2007

Ca ii K observations of the Sun have a great potential for probing the Sun’s magnetism and activity, as well as for reconstructing solar irradiance. The Kodaikanal Solar Observatory (KoSO) in India, houses one of the most prominent Ca ii K archives, spanning from 1904 to 2007, obtained under the same experimental conditions over a century, a feat very few other sites have achieved. However, the KoSO Ca ii K archive suffers from several inconsistencies (e.g., missing/incorrect timestamps of observations and orientation of some images) which have limited the use of the archive. This study is a step towards bringing the KoSO archive to its full potential. We did this by developing an automatic method to orient the images more accurately than in previous studies. Furthermore, we included more data than in earlier studies (considering images that could not previously be analyzed by other techniques, as well as 2845 newly digitized images), while also accounting for mistakes in the observational date/time. These images were accurately processed to identify plage regions along with their locations, enabling us to construct the butterfly diagram of plage areas from the entire KoSO Ca ii K archive covering 1904 – 2007. Our butterfly diagram shows significantly fewer data gaps compared to earlier versions due to the larger set of data used in this study. Moreover, our butterfly diagram is consistent with Spörer’s law for sunspots, validating our automatic image orientation method. Additionally, we found that the mean latitude of plage areas calculated over the entire period is 20.5%±2.0 higher than that of sunspots, irrespective of the phase or the strength of the solar cycle. We also studied the north–south asymmetry showing that the northern hemisphere dominated plage areas during solar cycles 19 and 20, while the southern hemisphere dominated during Solar Cycles 21 – 23.

Wavefront sensing based on large guide region in solar ground layer adaptive optics

In ground-based high-resolution solar observation, ground-layer adaptive optics (GLAO) offers a significant advancement by compensating for wavefront aberrations caused by near-ground atmospheric turbulence. GLAO overcomes the field-of-view limitations of conventional adaptive optics (AO), which is constrained by turbulence anisoplanatism. In conventional solar AO, wavefront sensing requires correlation calculations across an extended guide region to extract wavefront information. However, the cross correlation algorithm with a larger guide region size smooths the wavefront distortions caused by high-altitude turbulence, reducing the accuracy of single-line wavefront detection. This effect is particularly pronounced in GLAO systems that utilize large guide regions for ground layer wavefront sensing. This paper proposed a theoretical model for GLAO wavefront sensing using correlating Shack-Hartmann wavefront sensors targeting extended objects. We quantitatively analyze the impact of the guide region size on wavefront detection accuracy and validate our findings through simulation experiments. Simulation results indicate that for a 1-meter telescope, the difference between the root mean square (RMS) of detected aberrations differs from the RMS of ground-layer aberrations by less than 1/30 wavelength when using the CP7 model at 60" and the MK8 model at 140". Results also indicate that increasing the guide region effectively enables the detection of ground-layer wavefront aberrations. This finding not only provides valuable guidance for achieving accurate ground-layer wavefront sensing in GLAO systems, but also offers what we believe to be new solutions for optimizing GLAO system performance.

Development of an optical method to align a high-flux solar furnace.

High-flux solar furnaces are valuable tools for applied research and development in solar energy. However, misalignment of concentrator facets can produce optical losses and lower the concentration ratio of these systems. This study proposes a practical method to align a faceted solar furnace. The optical method uses a computer projector that illuminates the facets with a well-defined light pattern to quantitatively and qualitatively determine any misalignment associated with the mirrors. Through the Monte Carlo ray-tracing technique, the complete solar furnace, projector, and observation plane are optically modeled for the development of the methodology. A theoretical sensitivity analysis of the technique is reported, along with the experimental validation of the determined mirror misalignments, which results in a detection accuracy of 0.32mrad.

Deep learning image burst stacking to reconstruct high-resolution ground-based solar observations

Large aperture ground-based solar telescopes allow the solar atmosphere to be resolved in unprecedented detail. However, ground-based observations are inherently limited due to Earth's turbulent atmosphere, requiring image correction techniques. Recent post-image reconstruction techniques are based on using information from bursts of short-exposure images. Shortcomings of such approaches are the limited success, in case of stronger atmospheric seeing conditions, and computational demand. Real-time post-image reconstruction is of high importance to enabling automatic processing pipelines and accelerating scientific research. In an attempt to overcome these limitations, we provide a deep learning approach to reconstruct an original image burst into a single high-resolution high-quality image in real time. We present a novel deep learning tool for image burst reconstruction based on image stacking methods. Here, an image burst of 100 short-exposure observations is reconstructed to obtain a single high-resolution image. Our approach builds on unpaired image-to-image translation. We trained our neural network with seeing degraded image bursts and used speckle reconstructed observations as a reference. With the unpaired image translation, we aim to achieve a better generalization and increased robustness in case of increased image degradations. We demonstrate that our deep learning model has the ability to effectively reconstruct an image burst in real time with an average of 0.5 s of processing time while providing similar results to standard reconstruction methods. We evaluated the results on an independent test set consisting of high- and low-quality speckle reconstructions. Our method shows an improved robustness in terms of perceptual quality, especially when speckle reconstruction methods show artifacts. An evaluation with a varying number of images per burst demonstrates that our method makes efficient use of the combined image information and achieves the best reconstructions when provided with the full-image burst.

Design requirements of a spectropolarimeter for solar extreme-ultraviolet observations and characterization of a K-mirror based on Brewster's angle.

Measuring the linear polarization signal in extreme-ultraviolet (EUV) spectral lines, produced by the Hanle effect, offers a promising technique for studying magnetic fields in the solar corona. The required signal-to-noise ratio for detecting the Hanle polarization signals is on the order of 101 (off-limb) to 106 (disk center). Measuring such low signals in the photon starved observations demands highly efficient instruments. In this paper, we present the design of an instrument, SpectroPOLarimeter for Extreme-ultraviolet Observations (SPOLEO), which utilizes reflective components with suitable mirror coatings and thicknesses to minimize the throughput losses. We analyze the system performance within the spectral range from 740 to 800Å. The K-mirror-based polarimeter model provides a polarizing power of 20%-40% in this wavelength range. Based on the system throughput and polarizing power, we discuss various possibilities for achieving the required signal-to-noise ratio, along with their limitations. Due to lack of facilities for fabrication and testing in the EUV, we have calibrated a prototype of the reflection-based polarimeter setup in the laboratory at the visible wavelength of 700nm.

Limb Observations of Global Solar Coronal Extreme-ultraviolet Wavefronts: The Inclination, Kinematics, Coupling with the Expanding Coronal Mass Ejections, and Connection with the Coronal Mass Ejection Driven Shocks

We select and investigate six global solar extreme-ultraviolet (EUV) wave events using data from the Solar Dynamics Observatory and the Solar and Heliospheric Observatory. These eruptions are all on the limb but recorded as halo coronal mass ejections (CMEs) because the CME-driven shocks have expanded laterally to the opposite side. With the limb observations avoiding the projection effect, we have measured the inclination and speed of the EUV wavefront from 1.05 to 1.25 R ⊙. We also investigate the coupling and connection of the EUV wavefront with the CME boundary and the CME-driven shock, respectively. The major findings in the six events are: (1) the forward inclination of the primary and coronal-hole-transmitted EUV wavefronts is estimated, respectively, and the origins of these inclinations and their effects on the estimate of actual wavefronts speed are investigated; (2) the wavefront speed can be elevated by loop systems near the coronal base, and the average speed in the low corona has no clear correlation with the lateral expansion of the CME-driven shock in the high corona; (3) the fast magnetosonic Mach number of the wavefront is larger than unity from the coronal base; (4) the EUV wavefront is coupled with the CME driver throughout the propagation in two events; (5) after the EUV wavefront vanishes, the CME-driven shock continues traveling on the opposite side and disconnects from the EUV wavefront in four events. These results and their implications are discussed, which provide insight into the properties of global EUV waves.

CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network

The optical flow algorithm (OF) is one the main methods for calculating image velocity field and has many applications in space weather. Most OF calculations are applied to the motion of labeled rigid objects and are not suitable for velocity detection of high-energy particles, such as in a coronal mass ejection (CME). Fluctuations in exposure time and the influence of space weather will lead to inconsistent brightness of the same feature point at different times. To address this problem, we propose an unsupervised multiscale optical flow network based on Vision Transformer, named UTFlowNet. The network comprises a multiscale feature extraction module and a coarse-to-fine global optical flow calculation module. The movement of high-energy particles emitted during a CME eruption follows certain physical rules. Therefore, we apply fluid motion–based loss functions to analyze the motion of high-energy particles more effectively, addressing the problem of CME motion field extraction. Our method can be applied to the real-time automatic extraction of a CME’s velocity field and performs well with inconsistent brightness, large-scale motion, and strong CME noise. Additionally, we can estimate subpixel level fine-grained velocity. Our model may be affected by overfitting during cross–data set inference, so we encourage performing a small amount of transfer learning on new data sets to mitigate this issue. In order to verify the accuracy of our method, we conducted experiments and verification on the Solar and Heliospheric Observatory LASCO C2 data and the High Altitude Observatory MLSO data. We constructed a large-scale displacement simulation data set based on LASCO C2 data and tested on it, achieving the best results.

Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning

The application of machine learning to the study of coronal mass ejections (CMEs) and their impacts on Earth has seen significant growth recently. Understanding and forecasting CME geoeffectiveness are crucial for protecting infrastructure in space and ensuring the resilience of technological systems on Earth. Here we present GeoCME, a deep-learning framework designed to predict, deterministically or probabilistically, whether a CME event that arrives at Earth will cause a geomagnetic storm. A geomagnetic storm is defined as a disturbance of the Earth’s magnetosphere during which the minimum Dst index value is less than −50 nT. GeoCME is trained on observations from the instruments including LASCO C2, EIT, and MDI on board the Solar and Heliospheric Observatory (SOHO), focusing on a dataset that includes 136 halo/partial halo CMEs in Solar Cycle 23. Using ensemble and transfer learning techniques, GeoCME is capable of extracting features hidden in the SOHO observations and making predictions based on the learned features. Our experimental results demonstrate the good performance of GeoCME, achieving a Matthew’s correlation coefficient of 0.807 and a true skill statistics score of 0.714 when the tool is used as a deterministic prediction model. When the tool is used as a probabilistic forecasting model, it achieves a Brier score of 0.094 and a Brier skill score of 0.493. These results are promising, showing that the proposed GeoCME can help enhance our understanding of CME-triggered solar-terrestrial interactions.