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AutoTAB: Automatic Tracking Algorithm for Bipolar Magnetic Regions
Banerjee, Dipankar; Sreedevi, Anu; Jha, Bibhuti Kumar +1 more
Bipolar magnetic regions (BMRs) provide crucial information about solar magnetism. They exhibit varying morphology and magnetic properties throughout their lifetime, and studying these properties can provide valuable insights into the workings of the solar dynamo. The majority of previous studies have counted every detected BMR as a new one and ha…
A Data-driven, Physics-based Transport Model of Solar Energetic Particles Accelerated by Coronal Mass Ejection Shocks Propagating through the Solar Coronal and Heliospheric Magnetic Fields
Riley, Pete; Zhang, Ming; Lario, David +5 more
In an effort to develop computational tools for predicting radiation hazards from solar energetic particles (SEPs), we have created a data-driven physics-based particle transport model to calculate the injection, acceleration, and propagation of SEPs from coronal mass ejection (CME) shocks traversing through the solar corona and interplanetary mag…
Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Yang, Y.; Feng, X. S.; Chen, P. F. +2 more
Coronal mass ejections (CMEs), a kind of violent solar eruptive activity, can exert a significant impact on space weather. When arriving at the Earth, they interact with the geomagnetic field, which can boost the energy supply to the geomagnetic field and may further result in geomagnetic storms, thus having potentially catastrophic effects on hum…
A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Pant, Vaibhav; Banerjee, Dipankar; Patel, Ritesh +4 more
The primary objective of this study is to connect coronal mass ejections (CMEs) to their source regions, primarily to create a CME source region catalog, and secondarily to probe the influence that the source regions have on the different statistical properties of CMEs. We create a source region catalog for 3327 CMEs from 1998 to 2017, thus captur…
Toward a Live Homogeneous Database of Solar Active Regions Based on SOHO/MDI and SDO/HMI Synoptic Magnetograms. I. Automatic Detection and Calibration
Wang, Ruihui; Jiang, Jie; Luo, Yukun
Recent studies indicate that a small number of rogue solar active regions (ARs) may have a significant impact on the end-of-cycle polar field and the long-term behavior of solar activity. The impact of individual ARs can be qualified based on their magnetic field distribution. This motivates us to build a live homogeneous AR database in a series o…
Application of Deep Reinforcement Learning to Major Solar Flare Forecasting
Moon, Yong-Jae; Yi, Kangwoo; Jeong, Hyun-Jin
In this study, we present the application of deep reinforcement learning to the forecasting of major solar flares. For this, we consider full-disk magnetograms at 00:00 UT from the Solar and Heliospheric Observatory/Michelson Doppler Imager (1996-2010) and the Solar Dynamics Observatory/Helioseismic and Magnetic Imager (2011-2019), as well as Geos…
Quasiperiodic Variations of Coronal Mass Ejections with Different Angular Widths
Mei, Ying; Wang, Feng; Deng, Hui +2 more
Coronal mass ejections (CMEs) are energetic expulsions of organized magnetic features from the Sun. The study of CME quasiperiodicity helps establish a possible relationship between CMEs, solar flares, and geomagnetic disturbances. We used the angular width of CMEs as a criterion for classifying the CMEs in the study. Based on 25 yr of observation…
Homogenizing SOHO/EIT and SDO/AIA 171 Å Images: A Deep-learning Approach
Chatterjee, Subhamoy; Dayeh, Maher A.; Bain, Hazel M. +2 more
Extreme-ultraviolet (EUV) images of the Sun are becoming an integral part of space weather prediction tasks. However, having different surveys requires the development of instrument-specific prediction algorithms. As an alternative, it is possible to combine multiple surveys to create a homogeneous data set. In this study, we utilize the temporal …