Related papers: Predicting the Emergence of Solar Active Regions U…

We developed Long Short-Term Memory (LSTM) models to predict the formation of active regions (ARs) on the solar surface. Using the Doppler shift velocity, the continuum intensity, and the magnetic field observations from the Solar Dynamics…

Solar active regions (ARs) are the primary drivers of space weather events, making their early prediction crucial for operational forecasting systems. We develop machine learning models capable of predicting the evolution of magnetic flux…

The continuous observation of the magnetic field by Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) produces numerous image sequences in time and space. These sequences provide data support for predicting the…

Early and accurate prediction of solar active region (AR) emergence is crucial for space weather forecasting. Building on established Long Short-Term Memory (LSTM) based approaches for forecasting the continuum intensity decrease associated…

The development of accurate forecasts of solar eruptive activity has become increasingly important for preventing potential impacts on space technologies and exploration. Therefore, it is crucial to detect Active Regions (ARs) before they…

We use observations of line-of-sight magnetograms from Helioseismic and Magnetic Imager (HMI) on board of Solar Dynamics Observatory (SDO) to investigate polarity separation, magnetic flux, flux emergence rate, twist and tilt of solar…

A deep learning network, Long-Short Term Memory (LSTM) network, is used in this work to predict whether the maximum flare class an active region (AR) will produce in the next 24 hours is class $\Gamma$. We considered $\Gamma$ are $\ge M$,…

We show that under certain conditions, subsurface structures in the solar interior can alter the average acoustic power observed at the photosphere above them. By using numerical simulations of wave propagation, we show that this effect is…

Magnetic flux generated within the solar interior emerges to the surface, forming active regions (ARs) and sunspots. Flux emergence may trigger explosive events, such as flares and coronal mass ejections and therefore understanding…

Magnetic active regions on the Sun are harbingers of space weather events. Understanding the physics of how they form and evolve will improve space weather forecasting. Our aim is to characterise the surface magnetic field and flows for a…

The complex dynamics that lead to the emergence of active regions on the sun are poorly understood. One possibility is that magnetic structures (flux tubes, etc.) rise from below the surface by self induction and convection that lead to the…

Identifying solar active regions (ARs), which consist of one or more pairs of magnetic patches with opposite polarities, is essential due to their significant role in dynamic solar atmospheric phenomena. In this study, we analyze ARs during…

Observations from the Solar Dynamics Observatory (SDO) have the potential for allowing the helioseismic study of the formation of hundreds of active regions, which would enable us to perform statistical analyses. Our goal is to collate a…

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking…

Investigating the properties of magnetic flux emergence is one of the most important problems of solar physics. In this study we present a newly developed deep-focus time-distance measurement scheme which is able to detect strong emerging…

Local helioseismology provides a unique opportunity to investigate the subsurface structure and dynamics of active regions and their effect on the large-scale flows and global circulation of the Sun. We use measurements of plasma flows in…

In this dataset we provide a comprehensive collection of magnetograms (images quantifying the strength of the magnetic field) from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO). The dataset…

We investigate the emergence of Active Region NOAA 10790 by means of time--distance helioseismology. Shallow regions of increased sound speed at the location of increased magnetic activity are observed, with regions becoming deeper at the…

We present a long short-term memory (LSTM) network for predicting whether an active region (AR) would produce a gamma-class flare within the next 24 hours. We consider three gamma classes, namely >=M5.0 class, >=M class, and >=C class, and…

Solar energetic particles (SEPs) are an essential source of space radiation, which are hazards for humans in space, spacecraft, and technology in general. In this paper we propose a deep learning method, specifically a bidirectional long…