Coronagraph Data Research Articles

CAMEL. II. A 3D Coronal Mass Ejection Catalog Based on Coronal Mass Ejection Automatic Detection with Deep Learning

Coronal mass ejections (CMEs) are major drivers of geomagnetic storms, which may cause severe space weather effects. Automating the detection, tracking, and three-dimensional (3D) reconstruction of CMEs is important for operational predictions of CME arrivals. The COR1 coronagraphs on board the Solar Terrestrial Relations Observatory spacecraft have facilitated extensive polarization observations, which are very suitable for the establishment of a 3D CME system. We have developed such a 3D system comprising four modules: classification, segmentation, tracking, and 3D reconstructions. We generalize our previously pretrained classification model to classify COR1 coronagraph images. Subsequently, as there are no publicly available CME segmentation data sets, we manually annotate the structural regions of CMEs using Large Angle and Spectrometric Coronagraph C2 observations. Leveraging transformer-based models, we achieve state-of-the-art results in CME segmentation. Furthermore, we improve the tracking algorithm to solve the difficult separation task of multiple CMEs. In the final module, tracking results, combined with the polarization ratio technique, are used to develop the first single-view 3D CME catalog without requiring manual mask annotation. Our method provides higher precision in automatic 2D CME catalog and more reliable physical parameters of CMEs, including 3D propagation direction and speed. The aforementioned 3D CME system can be applied to any coronagraph data with the capability of polarization measurements.

Imaging detection of the inner dust belt and the four exoplanets in the HR 8799 system with JWST's MIRI coronagraph

The MIRI instrument on board JWST is now offering high-contrast imaging capacity at mid-IR wavelengths, thereby opening a completely new field of investigation for characterizing young exoplanetary systems. The multiplanet system HR\,8799 is the first target observed with MIRI's coronagraph as part of the MIRI-EC Guaranteed Time Observations (GTO) exoplanet program, launched in November 2022. We obtained deep observations in three coronagraphic filters, from $ 10$ to 15\,muup m (F1065C, F1140C, F1550C), and one standard imaging filter at $ (F2100W). The goal of this work is to extract photometry for the four planets and to detect and investigate the distribution of circumstellar dust. Using dedicated observations of a reference star, we tested several algorithms to subtract the stellar diffraction pattern, while preserving the fluxes of planets, which can be significantly affected by over-subtraction. To obtain correct measurements of the planet's flux values, the attenuation by the coronagraphs as a function of their position must be accounted for, as well as an estimation of the normalisation with respect to the central star. We tested several procedures to derive averaged photometric values and error bars. These observations have enabled us to obtain two main results. First, the four planets in the system are well recovered and we were able to compare their mid-IR fluxes, combined with near-IR flux values from the literature, to two exoplanet atmosphere models: ATMO and Exo-REM . As a main outcome, the MIRI photometric data points imply larger radii ( 1.04 or 1.17\,$R_ J for planet b) and cooler temperatures ( 950 or 1000\,K for planet b), especially for planet b, in better agreement with evolutionary models. Second, these JWST/MIRI coronagraphic data also deliver the first spatially resolved detection of the inner warm debris disk, the radius of which is constrained to about 15\,au, with flux densities that are comparable to (but lower than) former unresolved spectroscopic measurements with Spitzer. The coronagraphs coming from MIRI ushers in a new vision of known exoplanetary systems that differs significantly from shorter wavelength, high-contrast images delivered by extreme adaptive optics from the ground. Inner dust belts and background galaxies become dominant at some mid-IR wavelengths, potentially causing confusion in detecting exoplanets. Future observing strategies and data reductions ought to take such features into account.

Coronagraphic Data Post-processing Using Projections on Instrumental Modes

Directly observing exoplanets with coronagraphs is impeded by the presence of speckles from aberrations in the optical path, which can be mitigated in hardware with wave front control, as well as in post-processing. This work explores using an instrument model in post-processing to separate astrophysical signals from residual aberrations in coronagraphic data. The effect of wave front error (WFE) on the coronagraphic intensity consists of a linear contribution and a quadratic contribution. When either of the terms is much larger than the other, the instrument response can be approximated by a transfer matrix mapping WFE to detector plane intensity. From this transfer matrix, a useful projection onto instrumental modes that removes the dominant error modes can be derived. We apply this approach to synthetically generated Roman Space Telescope hybrid Lyot coronagraph data to extract “robust observables,” which can be used instead of raw data for applications such as detection testing. The projection improves planet flux ratio detection limits by about 28% in the linear regime and by over a factor of 2 in the quadratic regime, illustrating that robust observables can increase sensitivity to astrophysical signals and improve the scientific yield from coronagraphic data. While this approach does not require additional information such as observations of reference stars or modulations of a deformable mirror, it can and should be combined with these other techniques, acting as a model-informed prior in an overall post-processing strategy.

Exploring the impact of imaging cadence on inferring CME kinematics

The kinematics of coronal mass ejections (CMEs) are crucial for understanding their initiation mechanism and predicting their impact on Earth and other planets. With most of the acceleration and deceleration occurring below 4 R⊙, capturing this phase is vital to better understand their initiation mechanism. Furthermore, the kinematics of CMEs in the inner corona (< 3 R⊙) are closely related to their propagation in the outer corona and their eventual impact on Earth. Since the kinematics of CMEs are mainly probed using coronagraph data, it is crucial to investigate the impact of imaging cadence on the precision of data analysis and the conclusions drawn from it and also for determining the flexibility of designing observational campaigns with upcoming coronagraphs. This study investigates the impact of imaging cadence on the kinematics of ten CMEs observed by the K-Coronagraph of the Mauna Loa Solar Observatory. We manually track the CMEs using high cadence (15 s) white-light observations of K-Cor and vary the cadence as 30 s, 1, 2, and 5 min to study the impact of cadence on the kinematics. We also employed the bootstrapping method to estimate the confidence interval of the fitting parameters. Our results indicate that the average velocity of the CMEs does not have a high dependence on the imaging cadence, while the average acceleration shows significant dependence on the same, with the confidence interval showing significant shifts for the average acceleration for different cadences. The impact of degraded cadence is also seen in the estimation of the time of onset of acceleration. We further find that it is difficult to find an optimum cadence to study all CMEs, as it is also influenced by the pixel resolution of the instrument and the speed of the CME. However, except for very slow CMEs (speeds less than 300 km−1), our results indicate a cadence of 1 min to be reasonable for the study of their kinematics. The results of this work will be important in the planning of observational campaigns for the existing and upcoming missions that will observe the inner corona.

Applying a temporal systematics model to vector Apodizing Phase Plate coronagraphic data: TRAP4vAPP

Context. The vector Apodizing Phase Plate (vAPP) is a pupil plane coronagraph that suppresses starlight by forming a dark hole in its point spread function (PSF). The unconventional and non-axisymmetrical PSF arising from the phase modification applied by this coronagraph presents a special challenge to post-processing techniques. Aims. We aim to implement a recently developed post-processing algorithm, temporal reference analysis of planets (TRAP) on vAPP coronagraphic data. The property of TRAP that uses non-local training pixels, combined with the unconventional PSF of vAPP, allows for more flexibility than previous spatial algorithms in selecting reference pixels to model systematic noise. Methods. Datasets from two types of vAPPs are analysed: a double grating-vAPP (dgvAPP360) that produces a single symmetric PSF and a grating-vAPP (gvAPP180) that produces two D-shaped PSFs. We explore how to choose reference pixels to build temporal systematic noise models in TRAP for them. We then compare the performance of TRAP with previously implemented algorithms that produced the best signal-to-noise ratio (S/N) in companion detections in these datasets. Results. We find that the systematic noise between the two D-shaped PSFs is not as temporally associated as expected. Conversely, there is still a significant number of systematic noise sources that are shared by the dark hole and the bright side in the same PSF. We should choose reference pixels from the same PSF when reducing the dgvAPP360 dataset or the gvAPP180 dataset with TRAP. In these datasets, TRAP achieves results consistent with previous best detections, with an improved S/N for the gvAPP180 dataset.

Fast Reconstruction of 3D Density Distribution around the Sun Based on the MAS by Deep Learning

This study is the first attempt to generate a three-dimensional (3D) coronal electron density distribution based on the pix2pixHD model, whose computing time is much shorter than that of the magnetohydrodynamic (MHD) simulation. For this, we consider photospheric solar magnetic fields as input, and electron density distribution simulated with the MHD Algorithm outside a Sphere (MAS) at a given solar radius is taken as output. We consider 155 pairs of Carrington rotations as inputs and outputs from 2010 June to 2022 April for training and testing. We train 152 deep-learning models for 152 solar radii, which are taken up to 30 solar radii. The artificial intelligence (AI) generated 3D electron densities from this study are quite consistent with the simulated ones from lower radii to higher radii, with an average correlation coefficient 0.97. The computing time of testing data sets up to 30 solar radii of 152 deep-learning models is about 45.2 s using the NVIDIA TITAN XP graphics-processing unit, which is much less than the typical simulation time of MAS. We find that the synthetic coronagraphic images estimated from the deep-learning models are similar to the Solar Heliospheric Observatory (SOHO)/Large Angle and Spectroscopic Coronagraph C3 coronagraph data, especially during the solar minimum period. The AI-generated coronal density distribution from this study can be used for space weather models on a near-real-time basis.

An Empirical Relationship Between Coronal Density and Solar Wind Velocity in the Middle Corona With Applications to Space Weather

AbstractAccurate predictions of ambient solar wind conditions are a central component of space weather forecasting. A recent advancement is to use the distribution of electron density at a heliocentric distance of 8 R⊙, gained by applying coronal rotational tomography to coronagraph data, as an inner boundary condition for the time‐dependent Heliospheric Upwind eXtrapolation solar wind model. This approach requires conversion of densities into solar wind velocity at the inner boundary. Based on comparison of the distribution of in situ measurements of density and velocities, this work finds a scaled exponential equation relating the density and outflow velocity at 8 R⊙, with three key parameters found as a function of time between years 2007–2021. Based on this relationship, comparison of modeled and in situ measurements of velocities at Earth, STEREO A and STEREO B over the past solar cycle give a mean absolute error of 61.2, 69.0, and 66.1 km s−1 respectively. An analysis of thousands of events (defined as solar wind streams above 450 km s−1) gives an accuracy score of 76%. This agreement validates the density‐velocity relationship, and shows that an inner boundary based on coronagraph observations is a robust complement, or alternative, to commonly‐used magnetic model constraints for solar wind modeling and forecasting.

Advances in 3D Reconstruction of Coronal Mass Ejections

Coronal mass ejection (CME) is the large scale magnetized plasmoid ejected from the Sun, which brings huge amount of magnetic flux and plasma into interplanetary space. An earthward CME will interact with the magnetosphere of the Earth, and invokes the substorm and the other phenomena of the space weather as it approaches to the Earth. The 2-dimensional data provided by the current observational techniques cannot describe the true magnetic structure and the plasma distribution of CMEs comprehensively. We need to look into the 3-dimensional structure and the associated three components of CME speeds in order to predict the time when an ICME (Interplanetary CME) reaches the Earth, and the potential consequent impact on the Earth and the nearby environment. In this paper, 3D reconstruction methods of CME based on existing imaging observations are introduced, including two kinds of reconstruction methods based on coronagraph data and heliosphere imager data, and CME-driven shock wave 3D reconstruction methods with high correlation with CME imaging reconstruction. Each method shows apparent advantages in dealing with specific events, but its weakness and necessary constrains to its applications exist as well. Results obtained via various methods are compared in this work, and we found that CME velocities and moving directions deduced from these methods are fairly close to one another, which shows high reliability of these methods. Finally, the hot topics related to the 3-dimensional reconstruction of CME (ICME) and the relevant development in reconstructing methods are also discussed.

Predicting the Geoeffectiveness of CMEs Using Machine Learning

Coronal mass ejections (CMEs) are the most geoeffective space weather phenomena, being associated with large geomagnetic storms, and having the potential to cause disturbances to telecommunications, satellite network disruptions, and power grid damage and failures. Thus, considering these storms’ potential effects on human activities, accurate forecasts of the geoeffectiveness of CMEs are paramount. This work focuses on experimenting with different machine-learning methods trained on white-light coronagraph data sets of close-to-Sun CMEs, to estimate whether such a newly erupting ejection has the potential to induce geomagnetic activity. We developed binary classification models using logistic regression, k-nearest neighbors, support vector machines, feed-forward artificial neural networks, and ensemble models. At this time, we limited our forecast to exclusively use solar onset parameters, to ensure extended warning times. We discuss the main challenges of this task, namely, the extreme imbalance between the number of geoeffective and ineffective events in our data set, along with their numerous similarities and the limited number of available variables. We show that even in such conditions adequate hit rates can be achieved with these models.

Investigating Remote-Sensing Techniques to Reveal Stealth Coronal Mass Ejections

Eruptions of coronal mass ejections (CMEs) from the Sun are usually associated with a number of signatures that can be identified in solar disc imagery. However, there are cases in which a CME that is well observed in coronagraph data is missing a clear low-coronal counterpart. These events have received attention during recent years, mainly as a result of the increased availability of multi-point observations, and are now known as “stealth CMEs.” In this work, we analyze examples of stealth CMEs featuring various levels of ambiguity. All the selected case studies produced a large-scale CME detected by coronagraphs and were observed from at least one secondary viewpoint, enabling a priori knowledge of their approximate source region. To each event, we apply several image processing and geometric techniques with the aim to evaluate whether such methods can provide additional information compared to the study of “normal” intensity images. We are able to identify at least weak eruptive signatures for all events upon careful investigation of remote-sensing data, noting that differently processed images may be needed to properly interpret and analyze elusive observations. We also find that the effectiveness of geometric techniques strongly depends on the CME propagation direction with respect to the observers and the relative spacecraft separation. Being able to observe and therefore forecast stealth CMEs is of great importance in the context of space weather, since such events are occasionally the solar counterparts of so-called “problem geomagnetic storms.”

The Magnetic Environment of a Stealth Coronal Mass Ejection

Abstract Interest in stealth coronal mass ejections (CMEs) is increasing due to their relatively high occurrence rate and space weather impact. However, typical CME signatures such as extreme-ultraviolet dimmings and post-eruptive arcades are hard to identify and require extensive image processing techniques. These weak observational signatures mean that little is currently understood about the physics of these events. We present an extensive study of the magnetic field configuration in which the stealth CME of 2011 March 3 occurred. Three distinct episodes of flare ribbon formation are observed in the stealth CME source active region (AR). Two occurred prior to the eruption and suggest the occurrence of magnetic reconnection that builds the structure that will become eruptive. The third occurs in a time close to the eruption of a cavity that is observed in STEREO-B 171 Å data; this subsequently becomes part of the propagating CME observed in coronagraph data. We use both local (Cartesian) and global (spherical) models of the coronal magnetic field, which are complemented and verified by the observational analysis. We find evidence of a coronal null point, with field lines computed from its neighborhood connecting the stealth CME source region to two ARs in the northern hemisphere. We conclude that reconnection at the null point aids the eruption of the stealth CME by removing the field that acted to stabilize the preeruptive structure. This stealth CME, despite its weak signatures, has the main characteristics of other CMEs, and its eruption is driven by similar mechanisms.

Observation of Disturbed Plasma Structures in the Environment of the Sun and Near-Earth Space with Radio Sounding and Local Measurements

An experiment on radio sounding of the circumsolar plasma by signals from the Mars Express spacecraft in 2013 was carried out in the period from March 4 through May 31. The investigated characteristics were the frequency of signals in the centimeter and decimeter ranges and the differential frequency. A number of events were recorded in which the intensity of the frequency fluctuations of the signals probing the plasma was several times higher than the background values. As shown by the analysis of observations of solar activity, such as an increase in the flux of X-rays and SOHO LASCO coronagraph data, this is explained by the passage of disturbed plasma streams generated in the solar corona through the spacecraft radio communication path with the Earth. The comparison of the radio transmission data with the results of measurements of the parameters of the near-Earth plasma using the Wind spacecraft in adjacent periods of time. As a result of the analysis of the data on the proton concentration, it became clear that sharp increases in both the average values and fluctuations of this characteristic were also observed near the Earth. The time lag between the events observed in the circumsolar and near-Earth plasma shows that the cause of the disturbances is the increased activity of the same coronal region rotating with the Sun.

Electron Density Reconstruction of Solar Coronal Mass Ejections Based on a Genetic Algorithm: Method and Application

Abstract We present a new method to reconstruct the three-dimensional electron density of coronal mass ejections (CMEs) based on a genetic algorithm, namely the genetic reconstruction method (GRM). GRM is first applied to model CMEs with different orientations and shapes. A set of analytic model CMEs from Gibson and Low is employed to produce synthetic CME images for GRM reconstruction. Model CMEs with longitudes of 0°, 45°, 90°, 135°, and 180° and latitudes of 0°, 15°, 30°, and 45° are used to test the performance of GRM. The model CMEs are obscured with a simulated occulter of a coronagraph to determine the influence of CME brightness incompleteness. We add random noise to some synthetic CME images to test the performance of GRM. The CME reconstructions are carried out using synthetic data from Solar Terrestrial Relations Observatory (STEREO) A and B with a separation angle of 90° and from STEREO A and the Solar and Heliospheric Observatory (SOHO) with a separation angle of 73°. The Pearson correlation coefficient and the mean relative absolute deviation are calculated to analyze the similarities in brightness and electron density between the model and reconstructed CMEs. Comparisons based on the similarity analysis under various conditions stated above give us valuable insights into the advantages and limitations of GRM reconstruction. The method is then applied to real coronagraph data from STEREO A and B, and SOHO on 2013 September 30.

Numerical simulations of shear-induced consecutive coronal mass ejections

Context. It is widely accepted that photospheric shearing motions play an important role in triggering the initiation of coronal mass ejections (CMEs). Even so, there are events for which the source signatures are difficult to locate, while the CMEs can be clearly observed in coronagraph data. These events are therefore called ‘stealth’ CMEs. They are of particular interest to space weather forecasters, since eruptions are usually discarded from arrival predictions if they appear to be backsided, which means not presenting any clear low-coronal signatures on the visible solar disc. Such assumptions are not valid for stealth CMEs since they can originate from the front side of the Sun and be Earth-directed, but they remain undetected and can therefore trigger unpredicted geomagnetic storms. Aims. We numerically model and investigate the effects of shearing motion variations onto the resulting eruptions and we focus in particular on obtaining a stealth CME in the trailing current sheet of a previous ejection. Methods. We used the 2.5D magnetohydrodynamics package of the code MPI-AMRVAC to numerically simulate consecutive CMEs by imposing shearing motions onto the inner boundary, which represents, in our case, the low corona. The initial magnetic configuration consists of a triple arcade structure embedded into a bimodal solar wind, and the sheared polarity inversion line is found in the southern loop system. The mesh was continuously adapted through a refinement method that applies to current carrying structures, allowing us to easily track the CMEs in high resolution, without resolving the grid in the entire domain. We also compared the obtained eruptions with the observed directions of propagation, determined using a forward modelling reconstruction technique based on a graduated cylindrical shell geometry, of an initial multiple coronal mass ejection (MCME) event that occurred in September 2009. We further analysed the simulated ejections by tracking the centre of their flux ropes in latitude and their total speed. Radial Poynting flux computation was employed as well to follow the evolution of electromagnetic energy introduced into the system. Results. Changes within 1% in the shearing speed result in three different scenarios for the second CME, although the preceding eruption seems insusceptible to such small variations. Depending on the applied shearing speed, we thus obtain a failed eruption, a stealth, or a CME driven by the imposed shear, as the second ejection. The dynamics of all eruptions are compared with the observed directions of propagation of an MCME event and a good correlation is achieved. The Poynting flux analysis reveals the temporal variation of the important steps of eruptions. Conclusions. For the first time, a stealth CME is simulated in the aftermath of a first eruption, originating from an asymmetric streamer configuration, through changes in the applied shearing speed, indicating it is not necessary for a closed streamer to exist high in the corona for such an event to occur. We also emphasise the high sensitivity of the corona to small changes in motions at the photosphere, or in our simulations, at the low corona.

Quasiperiodic Velocity Fluctuations in Eruptive Prominences Observed by AIA/SDO

Abstract The current study presents an investigation of the behavior of prominences during eruptions. Variations in the distribution of their velocities are detected at altitudes <0.6 R ⊙. Detailed analyses are carried out for 304 Å Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) observations. To track the behavior of prominences during eruptions, 41 events in the period 2010–2017 are studied. To follow the rise of a filament on higher altitudes (up to 32 R ⊙), Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph (SOHO/LASCO) data are also inspected. They are used to obtain kinematic profiles of eruptions. Obtained height–time and speed–time plots of the eruptions show velocity fluctuations in 83% of the explored cases, detected only in the SDO/AIA field of view, and not in any of the prominences observed at higher altitudes by SOHO/LASCO. Time intervals between fluctuations and heights at which they are detected are estimated. Strong periodicity cannot be determined.

Studying the relationship of localization parameters of solar sources of magnetic clouds with their characteristics and substorm activity

We propose a method for determining location and orientation of extended solar sources of magnetic clouds, using coronagraph data and SOHO EIT/MDI images of the photosphere. To estimate the probability of formation of magnetic clouds, we use a simple cylindrical force-free model. We have established that more extended sources and those having a slight inclination to the solar equator and located on the solar limb as compared to those that are nonextended and strongly inclined can generate expanding clouds, which with high probability can reach the magnetosphere like clouds from a source near the zero meridian and low latitudes.
 We determine the relationship between extreme values of substorm activity and parameters of solar sources under study during the impact of magnetic clouds on Earth’s magnetosphere from the AL index. We note that there are no substorms associated with extended sources outside the heliolatitude range ~5–20°. The established relationship between solar source coordinates and geomagnetic activity of the magnetic cloud sheath and body are consistent with the most probable distribution of magnetoactive regions over the solar disk.

Исследование связи параметров локализации солнечных источников магнитных облаков с их характеристиками и суббуревой активностью

We propose a method for determining location and orientation of extended solar sources of magnetic clouds, using coronagraph data and SOHO EIT/MDI images of the photosphere. To estimate the probability of formation of magnetic clouds, we use a simple cylindrical force-free model. We have established that more extended sources and those having a slight inclination to the solar equator and located on the solar limb as compared to those that are nonextended and strongly inclined can generate expanding clouds, which with high probability can reach the magnetosphere like clouds from a source near the zero meridian and low latitudes.
 We determine the relationship between extreme values of substorm activity and parameters of solar sources under study during the impact of magnetic clouds on Earth’s magnetosphere from the AL index. We note that there are no substorms associated with extended sources outside the heliolatitude range ~5–20°. The established relationship between solar source coordinates and geomagnetic activity of the magnetic cloud sheath and body are consistent with the most probable distribution of magnetoactive regions over the solar disk.

PynPoint: a modular pipeline architecture for processing and analysis of high-contrast imaging data

Context. The direct detection and characterization of planetary and substellar companions at small angular separations is a rapidly advancing field. Dedicated high-contrast imaging instruments deliver unprecedented sensitivity, enabling detailed insights into the atmospheres of young low-mass companions. In addition, improvements in data reduction and point spread function (PSF)-subtraction algorithms are equally relevant for maximizing the scientific yield, both from new and archival data sets. Aims. We aim at developing a generic and modular data-reduction pipeline for processing and analysis of high-contrast imaging data obtained with pupil-stabilized observations. The package should be scalable and robust for future implementations and particularly suitable for the 3–5 μm wavelength range where typically thousands of frames have to be processed and an accurate subtraction of the thermal background emission is critical. Methods. PynPoint is written in Python 2.7 and applies various image-processing techniques, as well as statistical tools for analyzing the data, building on open-source Python packages. The current version of PynPoint has evolved from an earlier version that was developed as a PSF-subtraction tool based on principal component analysis (PCA). Results. The architecture of PynPoint has been redesigned with the core functionalities decoupled from the pipeline modules. Modules have been implemented for dedicated processing and analysis steps, including background subtraction, frame registration, PSF subtraction, photometric and astrometric measurements, and estimation of detection limits. The pipeline package enables end-to-end data reduction of pupil-stabilized data and supports classical dithering and coronagraphic data sets. As an example, we processed archival VLT/NACO L′ and M′ data of β Pic b and reassessed the brightness and position of the planet with a Markov chain Monte Carlo analysis; we also provide a derivation of the photometric error budget.

Global Oscillations of the Sun according to SOHO/LASCO C3 Coronagraph Data

Long-period oscillations in the brightness of the Sun as a star have been analyzed on the basis of measurements of the solar light reflected by planets when they come into the field of view of the Large Angle and Spectrometric Coronagraph (LASCO C3) onboard the Solar and Heliospheric Observatory (SOHO). We took sequences of FITS intensitygrams from the archive of the SOHO/LASCO C3 space observatory for the observational data; they were 1024 × 1024 pixels in size, and they were acquired with the 12-min interval. In 5-day continuous time series of the brightness of Mars and Jupiter, coinciding modes of 8–10 and 36–38 h were found. This coincidence apparently indicates their solar origin. In addition, for Mars, we obtained 25-day series of time variations of the reflected solar radiation, in which a mode with even a lower frequency of 8–10 days was detected.

Three-dimensional Oscillations of 21 Halo Coronal Mass Ejections Using Multi-spacecraft Data

Abstract We investigate the 3D structure of kinematic oscillations of full halo coronal mass ejections (FHCMEs) using multi-spacecraft coronagraph data from two non-parallel lines of sight. For this, we consider 21 FHCMEs which are simultaneously observed by the Solar and Heliospheric Observatory and the Solar TErrestrial RElations Observatory A or B, from 2010 June to 2012 August when the spacecraft were roughly in quadrature. Using sequences of running difference images, we estimate the instantaneous projected speeds of the FHCMEs at 24 different azimuthal angles in the planes of the sky of those coronagraphs. We find that all these FHCMEs have experienced kinematic oscillations characterized by quasi-periodic variations of the instantaneous projected radial velocity with periods ranging from 24 to 48 min. The oscillations detected in the analyzed events are found to show distinct azimuthal wave modes. Thirteen events (about 62%) are found to oscillate with the azimuthal wave number m = 1. The oscillating directions of the nodes of the m = 1 mode for these FHCMEs are consistent with those of their position angles (or the direction of eruption), with a mean difference of about 23°. The oscillation amplitude is found to correlate well with the projected radial speed of the CME. An estimation of Lorentz accelerations shows that they are dominant over other forces, implying that the magnetic force is responsible for the kinematic oscillations of CMEs. However, we cannot rule out other possibilities: a global layer of enhanced current around the CMEs or the nonlinear nature of its driver, for example the effect of vortex shedding.