The sustained gamma-ray emission (SGRE) from the Sun is a prolonged enhancement of >100 MeV gamma-ray emission that extends beyond the flare impulsive phase. The origin of the >300 MeV protons resulting in SGRE is debated, with both flares and shocks driven by coronal mass ejections (CMEs) being the suggested sites of proton acceleration. We compared the near-Sun acceleration and space speed of CMEs with “Prompt” and “Delayed” (SGRE) gamma-ray components. We found that “Delayed”-component-associated CMEs have higher initial accelerations and space speeds than “Prompt Only”-component-associated CMEs. We selected halo CMEs (HCMEs) associated with type II radio bursts (shock-driving HCMEs) and compared the average acceleration and space speed between HCME populations with or without SGRE events, major solar energetic particle (SEP) events, metric, or decameter-hectometric (DH) type II radio bursts. We found that the SGRE-producing HCMEs associated with a DH type II radio burst and/or a major SEP event have higher space speeds and especially initial accelerations than those without an SGRE event. We estimated the radial distances and speeds of the CME-driven shocks at the end time of the 2012 January 23 and March 7 SGRE events using white-light images of STEREO Heliospheric Imagers and radio dynamic spectra of Wind WAVES. The shocks were at the radial distances of 0.6–0.8 au and their speeds were high enough (≈975 km s−1and ≈750 km s−1, respectively) for high-energy particle acceleration. Therefore, we conclude that our findings support the CME-driven shock as the source of >300 MeV protons.
- Award ID(s):
- NSF-PAR ID:
- Publisher / Repository:
- Harvard Dataverse
- Date Published:
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
quadrature period(2010 December–2011 August) the STEREO-A and B satellites were approximately at right angles to the SOHO satellite. This alignment was particularly advantageous for determining the coronal mass ejection (CME) properties, since the closer a CME propagates to the plane of sky, the smaller the measurement inaccuracies are. Our primary goal was to study dimmings and their relationship to CMEs and flares during this time. We identified 53 coronal dimmings using STEREO/EUVI 195 Å observations, and linked 42 of the dimmings to CMEs (observed with SOHO/LASCO/C2) and 23 to flares. Each dimming in the catalog was processed with the Coronal Dimming Tracker which detects transient dark regions in extreme ultraviolet images directly, without the use of difference images. This approach allowed us to observe footpoint dimmings: the regions of mass depletion at the footpoints of erupting magnetic flux rope structures. Our results show that the CME mass has a linear, moderate correlation with dimming total EUV intensity change, and a monotonic, moderate correlation with dimming area. These results suggest that the more the dimming intensity drops and the larger the erupting region is, the more plasma is evacuated. We also found a strong correlation between the flare duration and the total change in EUV intensity. The correlation between dimming properties showed that larger dimmings tend to be brighter; they go through more intensity loss and generally live longer—supporting the hypothesis that larger transient open regions release more plasma and take longer to close down and refill with plasma.
Abstract Solar flares have been linked to some of the most significant space weather hazards at Earth. These hazards, including radio blackouts and energetic particle events, can start just minutes after the flare onset. Therefore, it is of great importance to identify and predict flare events. In this paper we introduce the Detection and EUV Flare Tracking (DEFT) tool, which allows us to identify flare signatures and their precursors using high spatial and temporal resolution extreme-ultraviolet (EUV) solar observations. The unique advantage of DEFT is its ability to identify small but significant EUV intensity changes that may lead to solar eruptions. Furthermore, the tool can identify the location of the disturbances and distinguish events occurring at the same time in multiple locations. The algorithm analyzes high temporal cadence observations obtained from the Solar Ultraviolet Imager instrument aboard the GOES-R satellite. In a study of 61 flares of various magnitudes observed in 2017, the “main” EUV flare signatures (those closest in time to the X-ray start time) were identified on average 6 minutes early. The “precursor” EUV signatures (second-closest EUV signatures to the X-ray start time) appeared on average 14 minutes early. Our next goal is to develop an operational version of DEFT and to simulate and test its real-time use. A fully operational DEFT has the potential to significantly improve space weather forecast times.more » « less
Abstract In order to bridge the gap between heliospheric and solar observations of coronal mass ejections (CMEs), one of the key steps is to improve the understanding of their corresponding magnetic structures like the magnetic flux ropes (MFRs). But it remains a challenge to confirm the existence of a coherent MFR before or upon the CME eruption on the Sun and to quantitatively characterize the CME-MFR due to the lack of direct magnetic field measurements in the corona. In this study, we investigate MFR structures originating from two active regions (ARs), AR 11719 and AR 12158, and estimate their magnetic properties quantitatively. We perform nonlinear force-free field extrapolations with preprocessed photospheric vector magnetograms. In addition, remote-sensing observations are employed to find indirect evidence of MFRs on the Sun and to analyze the time evolution of magnetic reconnection flux associated with the flare ribbons during the eruption. A coherent “preexisting” MFR structure prior to the flare eruption is identified quantitatively for one event from the combined analysis of the extrapolation and observation. Then the characteristics of MFRs for two events on the Sun before and during the eruption forming the CME-MFR, including the axial magnetic flux, field line twist, and reconnection flux, are estimated and compared with the corresponding in situ modeling results. We find that the magnetic reconnection associated with the accompanying flares for both events injects a significant amount of flux into the erupted CME-MFRs.more » « less
Solar energetic particles (SEPs) are an essential source of space radiation, and are hazardous for humans in space, spacecraft, and technology in general. In this paper, we propose a deep-learning method, specifically a bidirectional long short-term memory (biLSTM) network, to predict if an active region (AR) would produce an SEP event given that (i) the AR will produce an M- or X-class flare and a coronal mass ejection (CME) associated with the flare, or (ii) the AR will produce an M- or X-class flare regardless of whether or not the flare is associated with a CME. The data samples used in this study are collected from the Geostationary Operational Environmental Satellite's X-ray flare catalogs provided by the National Centers for Environmental Information. We select M- and X-class flares with identified ARs in the catalogs for the period between 2010 and 2021, and find the associations of flares, CMEs, and SEPs in the Space Weather Database of Notifications, Knowledge, Information during the same period. Each data sample contains physical parameters collected from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Experimental results based on different performance metrics demonstrate that the proposed biLSTM network is better than related machine-learning algorithms for the two SEP prediction tasks studied here. We also discuss extensions of our approach for probabilistic forecasting and calibration with empirical evaluation.