Weak Coronal Mass Ejections Research Articles

Coronal Signatures of Flare Generated Fast-Mode Wave at EUV and Radio Wavelengths

This paper presents a detailed study of the type II solar radio burst that occurred on 06 March 2014 using combined data analysis. It is a classical radio event consisting of type III radio burst and a following type II radio burst in the dynamic spectrum. The type II radio burst is observed between 235 – 130 MHz (120 – 60 MHz) in harmonic (fundamental) bands with the life time of 5 minutes between 09:26 – 09:31 UT. The estimated speed of type II burst by applying two-fold Saito model is ∼ 650 km s−1. An extreme ultraviolet (EUV) wave is observed with Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO). The very close temporal onset association of the EUV wave and flare energy release indicates that the EUV wave is likely produced by a flare pressure pulse. The eruption is also accompanied by a weak coronal mass ejection (CME) observed with the coronagraphs onboard the Solar and Heliospheric Observatory (SOHO) and the twin Solar Terrestrial Relations Observatory (STEREO). The plane of sky speed of the CME was ∼ 252 km s−1 in the SOHO/LASCO-C2 and ∼ 280 km s−1 in the STEREO-B/SECCHI-COR1 images. The EUV wave has two wave fronts, one expanding radially outward and the other one moving along the flare loop arcade. The source position of the type II burst imaged by the Nançay Radio Heliograph (NRH) shows that it was associated with the outward moving EUV wave. The CME is independent of the shock wave as confirmed by the location of NRH radio sources below the CME’s leading edge. Therefore the type II radio burst is probably ignited by the flare. This study shows the possibility of EUV wave and coronal shock triggered by flare pressure pulse, generating the observed type II radio burst.

Simulation of the Solar Energetic Particle Event on 2020 May 29 Observed by Parker Solar Probe

This paper presents a stochastic three-dimensional focused transport simulation of solar energetic particles (SEPs) produced by a data-driven coronal mass ejection (CME) shock propagating through a data-driven model of coronal and heliospheric magnetic fields. The injection of SEPs at the CME shock is treated using diffusive shock acceleration of post-shock suprathermal solar wind ions. A time-backward stochastic simulation is employed to solve the transport equation to obtain the SEP time–intensity profile at any location, energy, and pitch angle. The model is applied to a SEP event on 2020 May 29, observed by STEREO-A close to ∼1 au and by Parker Solar Probe (PSP) when it was about 0.33 au away from the Sun. The SEP event was associated with a very slow CME with a plane-of-sky speed of 337 km s−1 at a height below 6 R S as reported in the SOHO/LASCO CME catalog. We compute the time profiles of particle flux at PSP and STEREO-A locations, and estimate both the spectral index of the proton energy spectrum for energies between ∼2 and 16 MeV and the equivalent path length of the magnetic field lines experienced by the first arriving SEPs. We find that the simulation results are well correlated with observations. The SEP event could be explained by the acceleration of particles by a weak CME shock in the low solar corona that is not magnetically connected to the observers.

A Comparison of Solar X-Ray Flare Timescales and Peak Temperatures with Associated Coronal Mass Ejections

Recent work has shown that plots of solar flare X-ray peak temperatures, Tm, versus log peak fluxes, Fp, show statistically significant separations of lower Tm flares with fast (Vcme ≥ 1000 km s−1) and wide (Wcme = 360°) strong coronal mass ejections (CMEs) from higher Tm flares with no CMEs or slow (Vcme < 1000 km s−1) or narrow (<360°) weak CMEs. We extend that statistical separation to CME kinetic energies, Ecme. Flares with long-duration timescales also have well-known associations with fast CMEs and solar energetic (E > 10 MeV) particle events. Using a data set of 585 ≥ M3.0 GOES X-ray flares, we ask whether longer flare timescales (rise times, TR; durations from onset to half-power decay, TD; decay times to half power, Td; and decay times to C2, TC2) also statistically discriminate among the three groups of CMEs for speeds, widths, and energies. All log–log plots of flare timescales versus Fp produce significant separations of the three groups of CMEs generally better than those of Tm versus log Fp. We use separations of CME distribution medians to sort the four flare timescales as effective discriminants among the three CME groups. Separations between the confined flares (no-CMEs) and weak CMEs are generally smaller than those between the weak CMEs and strong CMEs. A combination of Tm and TC2 provides optimum group separations, but Tm and log TD or log Td appears best for CME forecasting purposes.

Recurrent Solar Energetic Particle Flux Enhancements Observed near Earth and Mars

Abstract The period 2016 August 1 to November 15 was characterized by the presence of corotating interaction regions (CIRs) and a few weak coronal mass ejections (CMEs) in the heliosphere. In this study we show recurrent energetic electron and proton enhancements observed near Earth (1 au) and Mars (1.43–1.38 au) during this period. The observations near Earth use data from instruments on board the Advanced Composition Explorer, the Solar and Heliospheric Observatory, and Solar Dynamics Observatory and those near Mars are from the Solar Energetic Particle, Solar Wind Ion Analyzer, and Magnetometer instruments on board the Mars Atmosphere and Volatile EvolutioN (MAVEN). During this period, the energetic electron fluxes observed near Earth and Mars showed prominent periodic enhancements over four solar rotations, with major periodicities of ∼27 days and ∼13 days. Periodic radar blackouts/weakenings of radar signals at Mars were observed by the Mars Advanced Radar for Subsurface and Ionosphere Sounding/Mars Express, and are associated with these solar energetic electron enhancements. During this period, a weak CME and a high-speed stream (HSS)-related interplanetary shock could have interacted with the CIR and enhance energetic proton fluxes near 1.43–1.38 au, causing ∼27 days periodicity in proton fluxes to be significantly diminished at 1.43–1.38 au. These events also have an unexpected impact on the Martian topside ionosphere, such as topside ionospheric depletion and compression observed by the Langmuir Probe and Waves and Neutral Gas and Ion Mass Spectrometer on board MAVEN. These observations are unique not only because of the recurring nature of electron enhancements seen at two vantage points, but also because they reveal the unexpected impact of the weak CME and interplanetary shock on the Martian ionosphere, which provides new insights into the impact of CME–HSS interactions on the Martian plasma environment.

Automatic Coronagraph Image Classification with Machine Learning Methods

The detection of Coronal Mass Ejections (CMEs) is an important prerequisite for establishing a CME event database and realizing the prediction of CME interplanetary propagation. The Lyman-alpha Solar Telescope (LST) aboard the ASO-S (Advanced Space-based Solar Observatory) satellite will be equipped with a white-light coronagraph. The images with CME detected will be contributed to various space weather prediction centers in China for CME early warning. The Visual Geometry Group (VGG) 16 convolutional neural network method is applied by us to automatically and effectively classify coronagraph images. Firstly, based on the image of the white light coronagraph of Large Angle and Spectrometric Coronagraph Experiment (LASCO) C2, we labeled the images according to whether a CME is observed. Then, the data set was used for training the VGG model. We find that the accuracy of the model in the test set classification reaches 92.5%. Next, according to the obtained classification results and combined with the space-time continuity rules, we corrected the mislabeling of images, and derived our final CME image sequences. Compared with the manual CME catalog of Coordinated Data Analysis Workshops (CDAW), the classified CME image sequences can include CME data more completely, and have higher detection sensitivity for weak CME structures.

Detection of the Weak CMEs by CALLISTO System

CALLISTO (Compound Astronomical Low Frequency Low Cost Instrument for Spectroscopy and Transportable Observatory) is one of the projects from ISWI and initiative of United Nation and NASA as a support to help developing countries to monitor activities of the Sun for the whole day. Today, more than 164 instruments at more than 100 locations use this system to do research on the Sun. The objective of this paper is to show that even the activity from the Sun is not too intense and large, the CALLISTO system can detect the signal, hence the importance of this system is acknowledged. This is as a hint for us to use the antenna as the part of the CALLISTO system to get the full coverage all day long with the contributed data from around the world. A weak Coronal Mass Ejection (CME) with the median velocity of 231 km/s was observed on 9th March 2019 by SOHO coronagraph and detected by CALLISTO system from multiple sites of UK, Switzerland and Italy. This faint CME was not giving the high impact to the Earth’s magnetosphere and thus no minor occurrence of the geomagnetic storm.

A Stealth CME Bracketed between Slow and Fast Wind Producing Unexpected Geoeffectiveness

Abstract We investigate how a weak coronal mass ejection (CME) launched on 2016 October 8 without obvious signatures in the low corona produced a relatively intense geomagnetic storm. Remote sensing observations from SDO, STEREO, and SOHO and in situ measurements from Wind are employed to track the CME from the Sun to the Earth. Using a graduated cylindrical shell model, we estimate the propagation direction and the morphology of the CME near the Sun. CME kinematics are determined from the wide-angle imaging observations of STEREO A and are used to predict the CME arrival time and speed at the Earth. We compare ENLIL MHD simulation results with in situ measurements to illustrate the background solar wind where the CME was propagating. We also apply a Grad–Shafranov technique to reconstruct the flux-rope structure from in situ measurements in order to understand the geoeffectiveness associated with the CME magnetic field structure. Key results are obtained concerning how a weak CME can generate a relatively intense geomagnetic storm: (1) there were coronal holes at low latitudes, which could produce high speed streams (HSSs) to interact with the CME in interplanetary space; (2) the CME was bracketed between a slow wind ahead and an HSS behind, which enhanced the southward magnetic field inside the CME and gave rise to the unexpected geomagnetic storm.

Propagation of Coronal Mass Ejections Observed During the Rising Phase of Solar Cycle 24

In this study, we investigate the interplanetary consequences and travel time details of 58 coronal mass ejections (CMEs) in the Sun–Earth distance. The CMEs considered are halo and partial halo events of width \({>}\,120\)°. These CMEs occurred during 2009 – 2013, in the ascending phase of the Solar Cycle 24. Moreover, they are Earth-directed events that originated close to the centre of the solar disk (within about \(\pm30\)° from the Sun’s centre) and propagated approximately along the Sun–Earth line. For each CME, the onset time and the initial speed have been estimated from the white-light images observed by the LASCO coronagraphs onboard the SOHO space mission. These CMEs cover an initial speed range of \({\sim}\,260\,\mbox{--}\,2700~\mbox{km}\,\mbox{s}^{-1}\). For these CMEs, the associated interplanetary shocks (IP shocks) and interplanetary CMEs (ICMEs) at the near-Earth environment have been identified from in-situ solar wind measurements available at the OMNI data base. Most of these events have been associated with moderate to intense IP shocks. However, these events have caused only weak to moderate geomagnetic storms in the Earth’s magnetosphere. The relationship of the travel time with the initial speed of the CME has been compared with the observations made in the previous Cycle 23, during 1996 – 2004. In the present study, for a given initial speed of the CME, the travel time and the speed at 1 AU suggest that the CME was most likely not much affected by the drag caused by the slow-speed dominated heliosphere. Additionally, the weak geomagnetic storms and moderate IP shocks associated with the current set of Earth-directed CMEs indicate magnetically weak CME events of Cycle 24. The magnetic energy that is available to propagate CME and cause geomagnetic storm could be significantly low.

An end-to-end method of Coronal Mass Ejections detection

Coronal Mass Ejections (CMEs) impact heavily on coronal activity, space weather and many interplanetary disturbance, so the detection of CMEs are important for space weather disaster prevention and reduction. The traditional methods use man-made features or predefined threshold to solve this problem. Despite the great progress in the detection of CMEs, it is still a challenging problem due to the following three aspects: Firstly, the early and late stage of the CMEs phenomenon is very weak, and the traditional image processing based method can not detect this weak CMEs well. Secondly, the noises from comet, planets and other stars can affect the detection of CMEs. Thirdly, the CMEs are complex and amorphous, and they are different in shapes, textures, grayscales, scales and so on. Because of these difficulties, it is difficult to detect CMEs well by the traditional image processing method without modeling the CMEs. With the development of convolutional neural networks (CNNs), it is possible to develop deep neural networks based CMEs detection models to better solve this problem. For realizing this, this paper presents an end-to-end detection method of Coronal Mass Ejections detection: We design a deep neural network with 4 convolution layers, 1 full connection layer and 1 output layer. This deep neural network can automatically extract the image features that are suitable to describe the Coronal Mass Ejections, and can establish the CMEs detection model based on the extracted features. In order to achieve good performance, we construct two datasets, one is mainly made up of strong CMEs, and the other is made up of weak or dark CMEs. Training is first done on the strong CMEs to obtain the initial CMEs detection model. Based on the initial model established on the strong CMEs, finetuning is used on the weak CMEs to acquire the final CMEs detection model. By using this scheme, training efficiency and good performance can be guaranteed. In addition, the process is able to achieve selection of features and setting of classification rules, which can realize conveniently the end-to-end detection from data to results. The experimental results show that this method can effectively detect CMEs. The accuracy of our method is 100% on the strong CME dataset, and 91.54% on the weak CME dataset. The overall accuracy on our dataset is 98.05%. Finally, we test our method with the real data on May 2007 using LASCO catalog as the groudtruth. Experimental results show that our method achieves state-of-the art performance comparing with the usually used catalog, SEEDS, CACTUS. The significance of our work is two-fold. On one hand, our method is end-to-end method which can select optimal features for the detection task. According to the theory of deep neural networks, the selected features are usually those that the human vision uses. Therefore, the obtained features can depicts CMEs well and can be used by other methods. On the other hand, the good performance of our method proves the depiction ability of the CNN for CME. So it is natural that CNN based description for the CME can also have good performance for the study of the modeling of the evolution of the CMEs.

Coronal mass ejections and type II radio bursts in cycles 23 and 24

The parameters of type II radio bursts (RBII) and related coronal mass ejections (CMEs), with regard to the class of the accompanying flares that occurred from 1997 to 2012, as well as the influence of the global solar magnetic field (GSMF) strength and structure on these phenomena, were studied. It was shown that RBII tend to form when the GSMF is stable and are more numerous when the GSMF sector structure predominates. The GSMF reorganization instants are characterized by a decrease in the magnetic field strength and electron density, which can explain why the number of weak CMEs increases at these instants. The CMEs related to RBII compose a distinct CME population. The parameters of these CMEs are quite different from those of all CMEs observed during the same period.

AN EXTREME-ULTRAVIOLET WAVE ASSOCIATED WITH A SURGE

Taking advantage of the high temporal and spatial resolution observations from the Solar Dynamics Observatory, we present an extreme-ultraviolet (EUV) wave associated with a surge on 2010 November 13. Due to the magnetic flux cancelation, some surges formed in the source active region (AR). The strongest surge produced our studied event. The surge was deflected by the nearby loops that connected to another AR, and disrupted the overlying loops that slowly expanded and eventually evolved into a weak coronal mass ejection (CME). The surge was likely associated with the core of the CME. The EUV wave happened after the surge deflected. The wave departed far from the flare center and showed a close location relative to the deflected surge. The wave propagated in a narrow angular extent, mainly in the ejection direction of the surge. The close timing and location relations between the EUV wave and the surge indicate that the wave was closely associated with the CME. The wave had a velocity of 310-350 km s(-1), while the speeds of the surge and the expanding loops were about 130 and 150 km s(-1), respectively. All of the results suggest that the EUV wave was a fast-mode wave and was most likely triggered by the weak CME.

Latitude Dependence of the Variations of Sunspot Group Numbers (SGN) and Coronal Mass Ejections (CMEs) in Cycle 23

The 12-month running means of the conventional sunspot number Rz, the sunspot group numbers (SGN) and the frequency of occurrence of Coronal Mass Ejections (CMEs) were examined for cycle 23 (1996 – 2006). For the whole disc, the SGN and Rz plots were almost identical. Hence, SGN could be used as a proxy for Rz, for which latitude data are not available. SGN values were used for 5° latitude belts 0° – 5°, 5° – 10°, 10° – 15°, 15° – 20°, 20° – 25°, 25° – 30° and > 30°, separately in each hemisphere north and south. Roughly, from latitudes 25° – 30° N to 20° – 25° N, the peaks seem to have occurred later for lower latitudes, from latitudes 20° – 25° N to 15° – 20° N, the peaks are stagnant or occur slightly earlier, and then from latitudes 15° – 20° N to 0° – 5° N, the peaks seem to have occurred again later for lower latitudes. Thus, some latitudinal migration is suggested, clearly in the northern hemisphere, not very clearly in the southern hemisphere, first to the equator in 1998, stagnant or slightly poleward in 1999, and then to the equator again from 2000 onwards, the latter reminiscent of the Maunder butterfly diagrams. Similar plots for CME occurrence frequency also showed multiple peaks (two or three) in almost all latitude belts, but the peaks were almost simultaneous at all latitudes, indicating no latitudinal migration. For similar latitude belts, SGN and CME plots were dissimilar in almost all latitude belts except 10° – 20° S. The CME plots had in general more peaks than the SGN plots, and the peaks of SGN often did not match with those of CME. In the CME data, it was noticed that whereas the values declined from 2002 to 2003, there was no further decline during 2003 – 2006 as one would have expected to occur during the declining phase of sunspots, where 2007 is almost a year of sunspot minimum. An inquiry at GSFC-NASA revealed that the person who creates the preliminary list was changed in 2004 and the new person picks out more weak CMEs. Thus a subjectivity (overestimates after 2002) seems to be involved and hence, values obtained before and during 2002 are not directly comparable to values recorded after 2002, except for CMEs with widths exceeding 60°.

Similarities and Dissimilarities between the Variations of CME and Other Solar Parameters at Different Heliographic Latitudes and Time Scales

From the LASCO CME (Coronal Mass Ejection) catalog, the occurrence frequencies of all CMEs (all strong and weak CMEs, irrespective of their widths) were calculated for 3-month intervals and their 12-month running means determined for cycle 23 (1996 – 2007) and were compared with those of other solar parameters. The annual values of all-CME frequency were very well correlated (+ 0.97) with sunspot numbers, but several other parameters also had similarly high correlations. Comparisons of 12-month running means indicated that the sunspot numbers were very well correlated with solar electromagnetic radiations (Lyman-α, 2800-MHz flux, coronal green line index, solar flare indices, and X-ray background); but for corpuscular radiations [proton fluxes, solar energetic particles (SEP), CMEs, interplanetary CMEs (ICMEs), and stream interaction regions (SIR)] and solar open magnetic fields, the correlations were lower. A notable feature was the appearance of two peaks during 2000 – 2002, and those double peaks in different parameters matched approximately except for proton fluxes and SEP and SIR frequencies. When hemispheric intensities were considered, north – south asymmetries appeared, more in some parameters than in others. When intensities in smaller latitude belts (10°) were compared, sunspot group numbers (SGN) were found to be confined mostly to latitudes within ± 30° of the solar equator, showing two peaks in all latitude belts, and during the course of the 11-year cycle, the double peaks shifted from middle to equatorial solar latitudes, just as seen in the Maunder butterfly diagrams. In contrast, CME frequency was comparable at all latitude belts (including high, near-polar latitudes), having more than two peaks in almost all latitude belts, and the peaks were almost simultaneous in all latitude belts. Thus, the matching of SGN peaks with those of CME peaks was poor. Incidentally, the CME frequency data for all events (all widths) after 2003 are not comparable to earlier data, owing to inclusion of very weak (narrow) CMEs in later years. The frequencies are comparable with earlier data only for widths exceeding about 70°.