Equatorial Rossby waves are detected using the HMI’s time-distance subsurface flow fields. It is also found that the power of the Rossby waves show a positive correlation with the sunspot number, while the frequency of the waves shows an anti-correlation with the sunspot number.
It is well known that many active regions (ARs) last longer than one solar rotation, however, they are often assigned one NOAA AR number for each rotation. This work lists most, if not all, of the ARs that are a same AR but with different AR numbers.
HMI magnetic field synoptic maps are used to evaluate the magnetic field structures’ organization and propagation as a function of time and latitude. It is demonstrated that the organization of longitudinal structures observed on synoptic maps is proportional to the level of activity at given latitudes.
This study reveals correlations between the motion of pores and the maximum magnetic pressure difference at their opposite edges, but no causal relationship between the two is found.
An analysis of two active regions shows that differently evolving ARs may produce major eruptive flares even when, in addition to the accumulation of significant free magnetic energy budgets, they accumulate large amounts of both left- and right-handed helicity without a strong dominance of one handedness over the other.
Magnetic flux loss from the solar interior due to flux emergence explains why all solar cycles decline in the same way.
The CGEM team identified and corrected two artifacts that had affected the electric field calculation for a small number of active regions.
Spectral analysis of the spatial structure of solar subphotospheric convection is carried out for subsurface flow maps. It is found that the horizontal flow scales increase rapidly with depth, from supergranulation to giant-cell values. The total power of the convective flows is found to be anticorrelated with the sunspot number variation over the solar activity cycle in shallow subsurface layers and positively correlated at larger depths.
Forward modeling is applied to numerous global hydrodynamic solar models, and helioseismic measurements on the meridional circulation are made using the forward modeling results. Comparison against the observational measurements shows significant differences, indicating our insufficient knowledge on either the global hydrodynamic modeling or the helioseismic inversions.
Some magnetic features in active regions, related to strong solar flares, are considered as “anomaly” features in a machine learning algorithm. An unsupervised auto-encoder network has been trained to identify such anomalies and is used to predict occurrence of strong flares.