A deep learning code is trained using the Sun’s front-side observations, HMI’s magnetograms and AIA’s 304Å EUV images, to establish a relation between magnetic field and EUV flux. Then the code is applied on the STEREO/EUVI 304Å data to obtain the Sun’s far-side magnetic field.
Both magnetic flux emergence and shearing flows occurred before the X9.3 flare on 2017 September 6. This analysis shows that shearing flows played a more significant role in leading to the helicity and electric currents buildup before the major eruption.
Heat flux delivered by magnetic reconnection is calculated based on a model using magnetic field observations, and the calculation is then compared with AIA EUV observations.
Shearing motions and sunspot rotations found in NOAA AR 12673 are believed to lead the free energy buildup and flux rope formation, which are responsible for the two successive X-class flares.
A set of parameters that characterize the complexity and energy potential of solar active-regions is fed through several Machine Learning and conventional statistics algorithms to forecast solar flares.
The majority of flare forecasting methods rely on observations of magnetic field on the Sun’s surface, but which observable, Br or Blos, is a better predictor? Through comparing a few magnetic properties derived from both observables, this nugget gives some suggestion.
The dipole, quadrupole, and octupole components of the Sun’s magnetic field are calculated and visualized, covering the last 22 years of the Sun’s activities.
The Sun’s meridional flow varies with the solar cycle, and this is possibly caused by the back-reaction of the dynamo-generated magnetic field on the meridional flow due to the Lorentz force.
Two homologous circular-ribbon flares associated with two filament eruptions were observed and analyzed. The emergence of magnetic flux ropes helped to inject free energy into the region and drive the magnetic reconnection above it.
Using a combination of the magnetograms, we find signs of the beginning of the 25th cycle from both HMI and WSO by calculating the inclination angles determined from the variation in line of sight field during a disk passage.