Features In Active Regions Research Articles

Solar active region evolution and imminent flaring activity through color-coded visualization of photospheric vector magnetograms

Context. The emergence of magnetic flux, its transition to complex configurations, and the pre-eruptive state of active regions are probed using photospheric magnetograms. Aims. Our aim is to pinpoint different evolutionary stages in emerging active regions, explore their differences, and produce parameters that could advance flare prediction using color-coded maps of the photospheric magnetic field. Methods. The three components of the photospheric magnetic field vector are combined to create color-combined magnetograms (COCOMAGs). From these, the areas occupied by different color hues are extracted, creating appropriate time series (color curves). These COCOMAGs and color curves are used as proxies of the active region evolution and its complexity. Results. The morphology of COCOMAGs showcases typical features of active regions, such as sunspots, plages, and sheared polarity inversion lines. The color curves represent the area occupied by photospheric magnetic field of different orientation and contain information pertaining to the evolutionary stages of active regions. During emergence, most of the region area is dominated by horizontal or highly inclined magnetic field, which is gradually replaced by more vertical magnetic field. In complex regions, large parts are covered by highly inclined magnetic fields, appearing as abrupt color changes in COCOMAGs. The decay of a region is signified by a domination of vertical magnetic field, indicating a gradual relaxation of the magnetic field configuration. The color curves exhibit a varying degree of correlation with active region complexity. Particularly the red and magenta color curves, which represent strong, purely horizontal magnetic field, are good indicators of future flaring activity. Conclusions. Color-combined magnetograms facilitate a comprehensive view of the evolution of active regions and their complexity. They offer a framework for the treatment of complex observations and can be used in pattern recognition, feature extraction, and flare-prediction schemes.

Statistical Analyses of Solar Prominences and Active Region Features in 304 Å Filtergrams Detected via Deep Learning

Solar active regions (ARs) are areas on the Sun with very strong magnetic fields where various activities take place. Prominences are one of the typical solar features in the solar atmosphere, whose eruptions often lead to solar flares and coronal mass ejections. Therefore, studying their morphological features and their relationship with solar activity is useful in predicting eruptive events and in understanding the long-term evolution of solar activities. A huge amount of data have been collected from various ground-based telescopes and satellites. The massive amounts of data make human inspection difficult. For this purpose, we developed an automated detection method for prominences and ARs above the solar limb based on deep-learning techniques. We applied it to process the 304 Å data obtained by SDO/AIA from 2010 May 13 to 2020 December 31. Besides the butterfly diagrams and latitudinal migrations of the prominences and ARs during solar cycle 24, the variations of their morphological features (such as the locations, areas, heights, and widths) with the calendar years and the latitude bands were analyzed. Most of these statistical results based on our new method are in agreement with previous studies, which also guarantees the validity of our method. The N–S asymmetry indices of the prominences and ARs show that the northern hemisphere is the dominant hemisphere in solar cycle 24, except for 2012–2015, and 2020 for ARs. The high-latitude prominences show much stronger N–S asymmetry, where the northern hemisphere is dominant in ∼2011 and ∼2015, and the southern hemisphere is dominant from 2016–2019.

A Strong-flare Prediction Model Developed Using a Machine-learning Algorithm Based on the Video Data Sets of the Solar Magnetic Field of Active Regions

It is well accepted that the physical properties obtained from the solar magnetic field observations of active regions (ARs) are related to solar eruptions. These properties consist of temporal features that might reflect the evolution process of ARs, and spatial features that might reflect the graphic properties of ARs. In this study, we generated video data sets with timescales of 1 day and image data sets of the SHARP radial magnetic field of the ARs from 2010 May to 2020 December. For the ARs that evolved from “quiet” to “active” and erupted the first strong flares in 4 days, we extract and investigate both the temporal and spatial features of ARs from videos, aiming to capture the evolution properties of their magnetic field structures during their transition process from “quiet” (non–strong flaring) to “active” (strong flaring). We then conduct a comparative analysis of the model performance by video input and single-image input, as well as of the effect of the model performance variation with the prediction window up to 3 days. We find that for those ARs that erupted the first strong flares in 4 days, the temporal features that reflect their evolution from “quiet” to “active” before the first strong flares can be recognized and extracted from the video data sets by our network. These features turn out to be important predictors that can effectively improve strong-flare prediction, especially by reducing the false alarms in a nearly 2 day prediction window.

Precursor identification for strong flares based on anomaly detection algorithm

In this study, we assume that the magnetic configuration of active regions (ARs) in quiet periods has certain similarities and can be considered “normal” features. While there are some other magnetic features of active regions that are related to strong flares, they can be considered the precursor of strong flares and “anomaly” features. Our study aims to identify those “anomalies” and apply them in strong-flare forecasting. An unsupervised auto-encoder network has been used to understand and memorize these “normal” features, and then, based on the mean squared errors between the pictures of the ARs and the corresponding reconstructed pictures derived by the network, an anomaly detection algorithm has been adopted to identify the precursor for strong flares and develop a strong-flare classification model. The strong-flare classification model reaches an F1 score of 0.8139, an accuracy of 0.8954, a recall of 0.8785, and a precision of 0.7581. Moreover, for those correctly predicted strong-flare events (94 M-class flares and above), the model reaches an average first warning time of 45.24 h. The results indicate that the anomaly detection algorithm can be used in precursor identification for strong flares and help in both improving strong-flare prediction accuracy and enlarging the time in advance. Also, the obtained average maximum warning period for strong-flare prediction (nearly 2 days) will be useful for future applications for space-weather solar flare prediction.

Flux emergence and generation of flare-productive active regions

Solar flares and coronal mass ejections are among the most prominent manifestations of the magnetic activity of the Sun. The strongest events of them tend to occur in active regions (ARs) that are large, complex, and dynamically evolving. However, it is not clear what the key observational features of such ARs are, and how these features are produced. This article answers these fundamental questions based on morphological and magnetic characteristics of flare-productive ARs and their evolutionary processes, i.e., large-scale flux emergence and subsequent AR formation, which have been revealed in observational and theoretical studies. We also present the latest modeling of flare-productive ARs achieved using the most realistic flux emergence simulations in a very deep computational domain. Finally, this review discusses the future perspective pertaining to relationships of flaring solar ARs with the global-scale dynamo and stellar superflares.

Bright Network, UVA, and the Physical Modeling of Solar Spectral and Total Irradiance in Recent Solar Cycles

Abstract In this paper we study the total solar irradiance (TSI) and the spectral solar irradiance (SSI) by applying the solar disk image decomposition algorithm (SDIDA) and solar irradiance synthesis algorithm (SISA) methods. These methods were applied to space-based observations in previous works, but in this work, they are applied to ground-based observations from various observatories, which allows for a long-term determination of TSI and SSI. We discuss the results of the SDIDA and SISA methods for the areas of solar features and the synthesized TSI and SSI. We find that SDIDA decompositions based on Ca ii K line images from various sources are all in good agreement between them and with previous space results when cross-calibration is performed, and consequently yield essentially the same TSI and SSI when SISA is applied. This paper shows the synthesized TSI and SSI, as well as the contributions from various feature types, during the recent solar cycles 23 and 24 and suggest further work can provide historical extended coverage using archival ground-based observations. The results demonstrate the presence of a significant variable bright network contribution during the cycle maximum, and of a reduced one at solar minimum, and that such a presence and variability affect both the SSI and TSI. We also find that all activity features are loosely correlated over solar cycle variations, but this correlation is nonlinear, and we show differences between cycles 23 and 24. Furthermore, we find that the SISA method can be successfully applied to determine the TSI and SSI for any particular state of the solar disk, and that the results depend not only on the total areas on the disk for each feature, but also on the relative distances from disk center of the active region features.

PREDICTING CORONAL MASS EJECTIONS USING MACHINE LEARNING METHODS

ABSTRACT Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections (CMEs). Usually, solar active regions that produce large flares will also produce a CME, but this is not always true. Despite advances in numerical modeling, it is still unclear which circumstances will produce a CME. Therefore, it is worthwhile to empirically determine which features distinguish flares associated with CMEs from flares that are not. At this time, no extensive study has used physically meaningful features of active regions to distinguish between these two populations. As such, we attempt to do so by using features derived from (1) photospheric vector magnetic field data taken by the Solar Dynamics Observatory’s Helioseismic and Magnetic Imager instrument and (2) X-ray flux data from the Geostationary Operational Environmental Satellite’s X-ray Flux instrument. We build a catalog of active regions that either produced both a flare and a CME (the positive class) or simply a flare (the negative class). We then use machine-learning algorithms to (1) determine which features distinguish these two populations, and (2) forecast whether an active region that produces an M- or X-class flare will also produce a CME. We compute the True Skill Statistic, a forecast verification metric, and find that it is a relatively high value of ∼0.8 ± 0.2. We conclude that a combination of six parameters, which are all intensive in nature, will capture most of the relevant information contained in the photospheric magnetic field.

Chromospheric jets around the edges of sunspots

Evidence is beginning to be put forward that demonstrates the role of the chromosphere in supplying energy and mass to the corona. We aim to assess the role of chromospheric jets in active region dynamics. Using a combination of the Hinode/SOT Ca II H and TRACE 1550 {\AA} and 1600 {\AA} filters we examine chromospheric jets situated at the edge of a sunspot. Analysis reveals a near continuous series of jets, that raise chromospheric material into the low corona above a sunspot. The jets have average rise speeds of 30 km\,s^{-1} and a range of 10-100km\,s^{-1}. Enhanced emission observed at the jets leading edge suggests the formation of a shock front. Increased emission in TRACE bandpasses above the sunspot and the disappearance of the jets from the Ca II filter suggests that some of the chromospheric jet material is at least heated to \sim0.1MK. The evidence suggests that the jets could be a mechanism which provides a steady, low-level heating for active region features.

South Korea's renewed focus on space weather

South Korea's renewed focus on space weather

Large‐Scale Dynamics of Active Regions and Small Photospheric Magnetic Features

This paper presents an analysis of the dynamics of magnetic features within and outside active regions using full-disk magnetograms obtained by the MDI (Michelson Doppler Imager) instrument on the SOHO spacecraft. The absence of distortion and the short time interval (96 minutes) between images allow us to calculate high-quality cross-correlations between regions on each magnetogram. Therefore, each cross-correlation can be studied individually, which provides information with resolution in longitude as well as good temporal resolution. Rotation rates and meridional motions are simultaneously derived from an analysis of the cross-correlation functions. This analysis shows that the meridional motions are very different during the quiet period and the active period. In the former case, a poleward meridional circulation is observed, which increases with latitude. In the latter case, the meridional motions of magnetic features in active regions are smaller by a factor of 2 than those exhibited by small magnetic structures outside active regions. The rotation rate seems slightly larger in active regions, while the rotation rate decreases as the activity level rises. Some differences in the meridional circulation of different polarities are found.

Statistical Study of Solar X-Ray Jets Observed with the Yohkoh Soft X-Ray Telescope

Abstract We have found 100 X-ray jets in the database of full Sun images taken with the Soft X-ray Telescope (SXT) aboard Yohkoh during the period from 1991 November through 1992 April. A statistical study for these jets results in the following characteristics: 1) Most are associated with small flares (microflaressubflares) at their footpoints. 2) The lengths lie in the range of a few × 104−4 × 105 km. 3) The widths are 5 × 103–105 km. 4) The apparent velocities are 10–1000 km s−1 with an average velocity of about 200 km s−1 . 5) The lifetime of the jet extends to ˜ 10 hours and the distribution of the observed lifetime is a power law with an index of ˜ 1.2. 6) 76% of the jets show constant or converging shapes; the width of the jet is constant or decreases with distance from the foot point. The converging type tends to be generated with an energetic foot point event and the constant type by a wide energy range of the footpoint event. 7) Many jets (˜ 68%) appear in or near to active regions (AR). Among the jets ejected from bright-point like features in ARs, most (˜ 86%) are observed to the west of the active region. 8) 27% of the jets show a gap ( > 104 km) between the exact footpoint of the jet and the brightest part of the associated flare. 9) The X-ray intensity distribution along an X-ray jet often shows an exponential decrease with distance from the footpoint. This exponential intensity distribution holds from the early phase to the decay phase.

The source regions of solar coronal mass ejections

Knowledge of the origin of the solar coronal mass ejection (CME) may be crucial to our understanding of several active solar phenomena, such as flares, as well as to the structure and stability of the corona and the prediction of interplanetary disturbances. In recent years, two camps of opinion have emerged, based on the belief that CMEs either commonly originate from structures intimately linked to active regions or they originate from coronal hole regions. This present study investigates the locations of 95 CME events observed during 1984–1986 relative to coronal hole and active region features. We find no evidence to support the coronal hole hypothesis and many indications that active regions are indeed associated with the source regions of CMEs.

An investigation of the linear polarization in emission features of active regions

A study has been made of linear polarization in ‘moustaches’ using the Hα and Hβ lines. A Wollaston prism and an achromatic λ/2-plate were employed in the study. In the course of the observations, the major axis of the plate was placed at 0° and 22°.5 with respect to the horizontal axis of the installation. The Stokes parameters J, Q, and U were recorded, thus enabling the degree of polarization and the field azimuth to be determined. During the first three minutes of the existence of the moustaches, the two lines revealed a linear polarization of about 7% located at the center of the lines. No polarization was found during the later stage of the moustaches' lifetimes. Whenever the linear polarization is present, there is a tendency for the polarization to decrease rapidly, in accompaniment of a turning of the azimuth. Several mechanisms for interpreting the polarization observed in the moustaches are examined. Some suggestions are made in support of the excitation of hydrogen atoms in the moustaches initiated by a high-energy electron flux or vertical heat conduction.

High-resolution spectroscopy of active regions

We describe an observing program designed to obtain spectra of sunspots, pores, and other features in active regions using the Vacuum Tower Telescope and Echelle Spectrograph at Sacramento Peak Observatory. The spectral lines used in this study have been especially chosen to allow pointed studies of fine structure in the intensity distribution, and in the velocity and magnetic fields in the photospheric levels of active regions, and to relate this structure to chromospheric observations made in the Caii H line. We demonstrate the capacities of the observing program by two examples: umbral fine structure, and an emerging active region. Although the umbral spectrograms resolve the brightness structure down to less than one arc sec we do not find clear-cut relations in the spatial variations of brightness, magnetic field strength and line-of-sight velocity across the umbral structure. In the emerging active region several processes are observed in their relationship: the rising and draining of an arch-filament system, the convective collapse of flux tubes, and the growth of a sunspot pore by coalescing fluxtubes.

The energy balance and pressure in the solar transition zone for network and active region features

The electron pressure and energy balance in the solar transition zone are determined for about 125 network and active region features on the basis of high spectral and spatial resolution extreme ultraviolet spectra. Si III line intensity ratios obtained from the Naval Research Laboratory high-resolution telescope and spectrograph during a rocket flight are used as diagnostics of electron density and pressure for solar features near 3.5 x 10 to the 4th K. Observed ratios are compared with the calculated dependence of the 1301 A/1312 A and 1301 A/1296 A line intensity ratios on electron density, temperature and pressure. Electron densities ranging from 2 x 10 to the 10th/cu cm to 10 to the 12th/cu cm and active region pressures from 3 x 10 to the 15th to 10 to the 16th/cu cm K are obtained. Energy balance calculations reveal the balance of the divergence of the conductive flux and turbulent energy dissipation by radiative energy losses in a plane-parallel homogeneous transition zone (fill factor of 1), and an energy source requirement for a cylindrical zone geometry (fill factor less than 0.04).

Coronal Manifestations of Eruptive Prominences, Observation and Interpretation

To appreciate the curious nature of the coronal manifestations of eruptive prominences, we must first recall how the corona around a quiescent prominence appears. The cool prominence material threads arcades of coronal loops, but is invisible in coronal lines. If one defines the corona as a million-degree gas above the chromosphere, then one must admit that there is no detectable corona where there is a filament. Simultaneous limb photographs in Ha and in coronal lines show that filaments outside of active regions reside in dark cavities in the corona. Active region filament cavities would be difficult to see because of the compact loop systems that characterize the corona there, but extrapolating from our experience with non-active region filaments, we can say, at least, that the loop arcade pattern inside active regions is the same as outside and that there is no evidence for any high-temperature, filament-shaped features in active regions.

A note on chromospheric fine structure at active region polarity boundaries

High resolution Hα filtergrams from Big Bear Solar Observatory reveal that some filamentary features in active regions have fine structure and hence magnetic field transverse to the gross structure and the zero longitudinal field line. These features are distinct from the usual active region filament, in which fine structure, magnetic field and filament are all parallel to the zero longitudinal field line. The latter occur on boundaries between regions of weaker fields while the former occur at boundaries between regions of stronger field.

The connection of fine-structure photospheric features in active regions with magnetic fields

1.The fine structure of the proton sunspot group of July 4–8, 1966 was studied on the basis of high-resolution heliograms. The comparison of the orientation between penumbral filaments and the transverse magnetic fields (observed by A.B. Severny and T.T. Tsap) shows that the direction of the filaments coincides in general with that of the magnetic field.2.Measurements of the magnetic fields of smallest pores (1·5″-2″) showed that the pores are always connected with strong magnetic field (in average 1400 gauss), which is localized at the same small area as the pore.3.Magnetic fields of faculae are concentrated in small elements with the dimension not exceeding 1·5″-3″. Magnetic-field strength H|| of about 45% of facular granules is within the limits of photographic measuring errors (approximately 25 gauss). For a quarter of all facular granules the strength H|| is from 25–50 gauss; about 30% of facular granules have H|| > 50 gauss, and sometimes there appear faculae with field strength of about 200 gauss. The magnetic-field strength of facular granules, which are found directly above spots, is 10–20 times less than the field strength of spots. This field is 80–210 gauss only.4.All observational data mentioned above show that the appearance of the fine-structure features in active regions is directly connected with the fine structure of magnetic field of different strength and different orientation. The study of high-resolution heliograms gives additional information about the fine structure of the magnetic field.