Individual Active Regions Research Articles

The MODEST catalog of depth-dependent spatially coupled inversions of sunspots observed by Hinode/SOT-SP

We present a catalog that contains depth-dependent information about the atmospheric conditions inside sunspot groups of all types. The catalog, which we named MODEST, is currently composed of 944 observations of 117 individual active regions with sunspots and covers all types of features observed in the solar photosphere. We used the SPINOR-2D code to perform spatially coupled inversions of the Stokes profiles observed by Hinode/SOT-SP at high spatial resolution. SPINOR-2D accounts for the unavoidable degradation of the spatial information due to the point spread function of the telescope. The sunspot sample focuses on complex sunspot groups, but simple sunspots are also part of the catalog for completeness. Sunspots were observed from 2006 to 2019, covering parts of solar cycles 23 and 24. The catalog is a living resource, as with time, more sunspot groups will be included.

Algebraic quantification of the contribution of active regions to the Sun’s dipole moment: applications to century-scale polar field estimates and solar cycle forecasting

ABSTRACT The solar cycle is generated by a magnetohydrodynamic dynamo mechanism which involves the induction and recycling of the toroidal and poloidal components of the Sun’s magnetic field. Recent observations indicate that the Babcock–Leighton (BL) mechanism – mediated via the emergence and evolution of tilted bipolar active regions – is the primary contributor to the Sun’s large-scale dipolar field. Surface flux transport models and dynamo models have been employed to simulate this mechanism, which also allows for physics-based solar cycle forecasts. Recently, an alternative analytic method has been proposed to quantify the contribution of individual active regions to the Sun’s dipole moment (DM). Utilizing solar cycle observations spanning a century, here, we test the efficacy of this algebraic approach. Our results demonstrate that the algebraic quantification approach is reasonably successful in estimating DMs at solar minima over the past century – providing a verification of the BL mechanism as the primary contributor to the Sun’s dipole field variations. We highlight that this algebraic methodology serves as an independent approach for estimating DMs at the minima of solar cycles, relying on characteristics of bipolar solar active regions. We also show how this method may be utilized for solar cycle predictions; our estimate of the Sun’s dipole field at the end of cycle 24 using this approach indicates that solar cycle 25 would be a moderately weak cycle, ranging between solar cycle 20 and cycle 24.

A Statistical Search for a Uniform Trigger Threshold in Solar Flares from Individual Active Regions

Solar flares result from the sudden release of energy deposited by subphotospheric motions into the magnetic field of the corona. The deposited energy accumulates secularly between events. One may interpret the observed event statistics as resulting from a state-dependent Poisson process in which the instantaneous flare rate is a function of the stress in the system and a flare becomes certain as the stress approaches a threshold set by the microphysics of the flare trigger. If the system is driven fast, and if the threshold is static and uniform globally, a cross-correlation is predicted between the size of a flare and the forward waiting time to the next flare. This cross-correlation is broadly absent from the Geostationary Operational Environmental Satellite (GOES) soft X-ray flare database. One also predicts higher cross-correlations in active regions where the shapes of the waiting time and size distributions match. Again, there is no evidence for such an association in the GOES data. The data imply at least one of the following: (i) the threshold at which a flare is triggered varies in time; (ii) the rate at which energy is driven into active regions varies in time; (iii) historical flare catalogs are incomplete; or (iv) the description of solar flares as resulting from a buildup and release of energy, once a threshold is reached, is incomplete.

Imaging individual active regions on the Sun’s far side with improved helioseismic holography

Context.Helioseismic holography is a useful method for detecting active regions on the Sun’s far side and improving space weather forecasts.Aims.We aim to improve helioseismic holography using a clear formulation of the problem, an accurate forward solver in the frequency domain, and a better understanding of the noise properties.Methods.Building on the work of Lindsey et al. we define the forward- and backward-propagated wave fields (ingression and egression) in terms of a Green’s function. This Green’s function is computed using an accurate forward solver in the frequency domain. We analyse overlapping segments of 31 h of SDO/HMI dopplergrams, with a cadence of 24 h. Phase shifts between the ingression and the egression are measured and averaged to detect active regions on the far side.Results.The phase maps are compared with direct extreme-ultraviolet (EUV) intensity maps from STEREO/EUVI. We confirm that medium-sized active regions can be detected on the far side with high confidence. Their evolution (and possible emergence) can be monitored on a daily time scale. Seismic maps averaged over 3 days provide an active-region detection rate as high as 75% and a false-discovery rate as low as 7% for active regions with areas above one thousandth of a hemisphere. For a large part, these improvements can be attributed to the use of a complete Green’s function (all skips) and the use of all available observations on the front side (full pupil).Conclusions.Improved helioseismic holography enables the study of the evolution of medium-sized active regions on the Sun’s far side.

Ultrabroadband Heterogeneous THz Quantum Cascade Laser.

Broadband emission in the terahertz spectral region is a prerequisite for applications such as spectroscopy or white light sources. Appropriate signal powers and a compact design are advantageous for this use. A technology which meets these requirements are terahertz quantum cascade lasers. These electrically pumped, on-chip semiconductor lasers provide high output powers and the freedom of tailoring their emission wavelength by bandstructure engineering. By combining multiple active region designs emitting at different wavelengths in a single structure, one can obtain broadband emission from a single device. Here, we present a heterogeneous terahertz quantum cascade laser consisting of five individual active regions based on a three-well, LO-phonon depopulation design. The devices lase in pulsed and continuous-wave operation and emit in a spectral range from 1.9 to 4.5 THz, covering a bandwidth of 1.37 octaves. The use of the three-well design, which was optimized for high temperature operation, leads to a maximum operating temperature in the pulsed operation of 143 K.

Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting

Solar flare prediction is a central problem in space weather forecasting and has captivated the attention of a wide spectrum of researchers due to recent advances in both remote sensing as well as machine learning and deep learning approaches. The experimental findings based on both machine and deep learning models reveal significant performance improvements for task specific datasets. Along with building models, the practice of deploying such models to production environments under operational settings is a more complex and often time-consuming process which is often not addressed directly in research settings. We present a set of new heuristic approaches to train and deploy an operational solar flare prediction system for ≥M1.0-class flares with two prediction modes: full-disk and active region-based. In full-disk mode, predictions are performed on full-disk line-of-sight magnetograms using deep learning models whereas in active region-based models, predictions are issued for each active region individually using multivariate time series data instances. The outputs from individual active region forecasts and full-disk predictors are combined to a final full-disk prediction result with a meta-model. We utilized an equal weighted average ensemble of two base learners’ flare probabilities as our baseline meta learner and improved the capabilities of our two base learners by training a logistic regression model. The major findings of this study are: 1) We successfully coupled two heterogeneous flare prediction models trained with different datasets and model architecture to predict a full-disk flare probability for next 24 h, 2) Our proposed ensembling model, i.e., logistic regression, improves on the predictive performance of two base learners and the baseline meta learner measured in terms of two widely used metrics True Skill Statistic (TSS) and Heidke Skill Score (HSS), and 3) Our result analysis suggests that the logistic regression-based ensemble (Meta-FP) improves on the full-disk model (base learner) by ∼9% in terms TSS and ∼10% in terms of HSS. Similarly, it improves on the AR-based model (base learner) by ∼17% and ∼20% in terms of TSS and HSS respectively. Finally, when compared to the baseline meta model, it improves on TSS by ∼10% and HSS by ∼15%.

Automated Driving for Global Nonpotential Simulations of the Solar Corona

We describe a new automated technique for active region emergence in coronal magnetic field models, based on the inversion of the electric field locally from a single line-of-sight magnetogram for each region. The technique preserves the arbitrary shapes of magnetic field distribution associated with individual active regions and incorporates emerging magnetic helicity (twist) in a parametrized manner through a noninductive electric field component. We test the technique with global magnetofrictional simulations of the coronal magnetic field during Solar Cycle 24 Maximum from 2011 June 1 to 2011 December 31. The active regions are determined in a fully automated and objective way using Spaceweather HMI Active Region Patch (SHARP) data. Our primary aim is to constrain two free parameters in the emergence algorithm: the duration of emergence and the twist parameter for each individual active region. While the duration has a limited effect on the resulting coronal magnetic field, changing the sign and amplitude of the twist parameters profoundly influences the amount of nonpotentiality generated in the global coronal magnetic field. We explore the possibility of constraining both the magnitude and sign of the twist parameter using estimates of the current helicity derived from vector magnetograms and supplied in the SHARP metadata for each region. Using the observed sign of twist for each region reduces the overall nonpotentiality in the corona, highlighting the importance of scatter in the emerging active region helicities.

Solar Energetic-Particle Ground-Level Enhancements and the Solar Cycle

Severe geomagnetic storms appear to be ordered by the solar cycle in a number of ways. They occur more frequently close to solar maximum and the declining phase, are more common in larger solar cycles, and show different patterns of occurrence in odd- and even-numbered solar cycles. Our knowledge of the most extreme space-weather events, however, comes from spikes in cosmogenic-isotope (14C, 10Be, and 36Cl) records that are attributed to significantly larger solar energetic-particle (SEP) events than have been observed during the space age. Despite both storms and SEPs being driven by solar-eruptive phenomena, the event-by-event correspondence between extreme storms and extreme SEPs is low. Thus, it should not be assumed a priori that the solar-cycle patterns found for storms also hold for SEPs and the cosmogenic-isotope events. In this study, we investigate the solar-cycle trends in the timing and magnitude of the 67 SEP ground-level enhancements (GLEs) recorded by neutron monitors since the mid-1950s. Using a number of models of GLE-occurrence probability, we show that GLEs are around a factor of four more likely around solar maximum than around solar minimum, and that they preferentially occur earlier in even-numbered solar cycles than in odd-numbered cycles. There are insufficient data to conclusively determine whether larger solar cycles produce more GLEs. Implications for putative space-weather events in the cosmogenic-isotope records are discussed. We find that GLEs tend to cluster within a few tens of days, likely due to particularly productive individual active regions, and with approximately 11-year separations, owing to the solar-cycle ordering. However, these timescales would not explain any cosmogenic-isotope spikes requiring multiple extreme SEP events over consecutive years.

Modeling Stellar Surface Features on a Subgiant Star with an M-dwarf Companion

Understanding magnetic activity on the surface of stars other than the Sun is important for exoplanet analyses to properly characterize an exoplanet’s atmosphere and to further characterize stellar activity on a wide range of stars. Modeling stellar surface features of a variety of spectral types and rotation rates is key to understanding the magnetic activity of these stars. Using data from Kepler, we use the starspot modeling program STarSPot (STSP) to measure the position and size of spots for KOI-340, which is an eclipsing binary consisting of a subgiant star (T eff = 5593 ± 27 K, R ⋆ = 1.98 ± 0.05 R ⊙) with an M-dwarf companion (M ⋆ = 0.214 ± 0.006 M ⊙). STSP uses a novel technique to measure the spot positions and radii by using the transiting secondary to study and model individual active regions on the stellar surface using high-precision photometry. We find that the average size of spot features on KOI-340's primary is ∼10% the radius of the star, i.e., two times larger than the mean size of solar-maximum sunspots. The spots on KOI-340 are present at every longitude and show possible signs of differential rotation. The minimum fractional spotted area of KOI-340's primary is , while the spotted area of the Sun is at most 0.2%. One transit of KOI-340 shows a signal in the transit consistent with a plage; this plage occurs right before a dark spot, indicating that the plage and spot might be colocated on the surface of the star.

The effect of spatial sampling on magnetic field modeling and helicity computation

Context. Nonlinear force-free (NLFF) modeling is regularly used to indirectly infer the 3D geometry of the coronal magnetic field, which is not otherwise accessible on a regular basis by means of direct measurements. Aims. We study the effect of binning in time-series NLFF modeling of individual active regions (ARs) in order to quantify the effect of a different underlying spatial sampling on the quality of modeling as well as on the derived physical parameters. Methods. We apply an optimization method to sequences of Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI) vector magnetogram data at three different plate scales for three solar active regions to obtain nine NLFF model time series. From the NLFF models, we deduce active-region magnetic fluxes, electric currents, magnetic energies, and relative helicities, and analyze those with respect to the underlying spatial sampling. We calculate various metrics to quantify the quality of the derived NLFF models and apply a Helmholtz decomposition to characterize solenoidal errors. Results. At a given spatial sampling, the quality of NLFF modeling is different for different ARs, and the quality varies along the individual model time series. For a given AR, modeling at a certain spatial sampling is not necessarily of superior quality compared to that performed with a different plate scale. Generally, the NLFF model quality tends to be higher for larger pixel sizes with the solenoidal quality being the ultimate cause for systematic variations in model-deduced physical quantities. Conclusions. Optimization-based modeling using SDO/HMI vector data binned to larger pixel sizes yields variations in magnetic energy and helicity estimates of ≲30% on overall, given that concise checks ensure the physical plausibility and high solenoidal quality of the tested model. Spatial-sampling-induced differences are relatively small compared to those arising from other sources of uncertainty, including the effects of applying different data calibration methods, those of using vector data from different instruments, or those arising from application of different NLFF methods to identical input data.

Avalanches of magnetic flux rope in the state of self-organized criticality

ABSTRACT The self-organized criticality (SOC) is a universal theory to explain the ubiquitous power-law size distributions of astrophysical instabilities such as solar eruptions. One way to understand the dynamical processes of an SOC system is through cellular automaton (CA) simulations. Here, we develop a three-dimensional solar CA model that assumes a twisted magnetic flux rope (MFR), in which the avalanche takes place when a local magnetic vector potential exceeds a Gaussian distributed instability criterion, triggered by a global and space-dependent energy driving mechanism. To avoid non-physical released energies, an energy screening mechanism is applied to calculate the avalanche energies of each time-step. Our results show that the statistics of the CA simulated flaring events are comparable to the frequency distributions of observed solar flares originating from an individual active region. Due to the fact of the universality of MFRs, the CA model can be applied to many other astrophysical SOC systems.

Do the solar flares originating from an individual active region follow a random process or a memory-dependent correlation?

ABSTRACT We investigate the waiting time statistics of solar flares both in a flare-productive active region (AR 12673) of the solar cycle 24 and in a three-dimensional magnetohydrodynamic (MHD) simulated AR. The statistical models of a discrete random process and a continuous memory-dependent process are applied to interpret the waiting time distributions (WTDs) of solar flares. Our results indicate that the occurrence of a solar flare in an individual AR maintains a certain amount of memory, and probably arises from MHD turbulence rather than from intermittent avalanches in a self-organized criticality system. It differs from the occurrence of ‘super flares’ when treating the star/Sun as a single non-linear system.

Pathogenic substantiation of application of erythropoietin modified forms and peptide analogues as cytotprotectors

Provides a review of the evidence from experimental and clinical studies on the blood-forming and non-blood-forming tissue protective effects of erythropoietin. Information on its side effects (stimulation of tumor growth, autoimmune reactions, arterial hypertension, etc.), limiting the clinical use as a cytoprotector, is summarized. Well-known modifications of the erythropoietin molecule with a tissue protective effect are considered, in particular, desialylated (asialoEPO), carboxylated (CEPO) and glutaraldehyde (GEPO) cytokine analogues.
 The results of biomedical studies describing the tissue protective effects of these compounds, as well as possible mechanisms of their receptor action, are presented. The article discusses the main short-chain erythropoietin mimetics that reproduce individual active regions of cytokine amino acid sequence and contain from 11 to 25 amino acids: Helix B, ARA290, Eportis, Epopeptide-ab, MK-X, Epobis, NL100.
 The biochemical mechanisms of cytoprotective action of erythropoietin and its derivatives are considered, including binding to the heterodimeric receptor of non-blood-forming tissues and activation of intracellular signaling molecules possessing properties of apopotosis inhibitors.
 It was noted that the tissue protective effect of erythropoietin in vivo is observed in hemostimulating doses and is accompanied by side effects. At the same time, the use of modified forms of erythropoietin and its short-chain peptide analogues, which have a high affinity for the isoform of the erythropoietin receptor of non-blood-forming tissues and do not have hematopoietic properties, allows avoiding the development of side effects and reducing effective doses by 10-20 times.

Towards an algebraic method of solar cycle prediction

An algebraic method for the reconstruction and potentially prediction of the solar dipole moment value at sunspot minimum (known to be a good predictor of the amplitude of the next solar cycle) was suggested in the first paper in this series. The method sums up the ultimate dipole moment contributions of individual active regions in a solar cycle: for this, detailed and reliable input data would in principle be needed for thousands of active regions in a solar cycle. To reduce the need for detailed input data, here we propose a new active region descriptor called ARDoR (Active Region Degree of Rogueness). In a detailed statistical analysis of a large number of activity cycles simulated with the 2 × 2D dynamo model we demonstrate that ranking active regions by decreasing ARDoR, for a good reproduction of the solar dipole moment at the end of the cycle it is sufficient to consider the top N regions on this list explicitly, where N is a relatively low number, while for the other regions the ARDoR value may be set to zero. For example, with N = 5 the fraction of cycles where the dipole moment is reproduced with an error exceeding ±30% is only 12%, significantly reduced with respect to the case N = 0, i.e. ARDoR set to zero for all active regions, where this fraction is 26%. This indicates that stochastic effects on the intercycle variations of solar activity are dominated by the effect of a low number of large “rogue” active regions, rather than the combined effect of numerous small ARs. The method has a potential for future use in solar cycle prediction.

Towards an algebraic method of solar cycle prediction

We discuss the potential use of an algebraic method to compute the value of the solar axial dipole moment at solar minimum, widely considered to be the most reliable precursor of the activity level in the next solar cycle. The method consists of summing up the ultimate contributions of individual active regions to the solar axial dipole moment at the end of the cycle. A potential limitation of the approach is its dependence on the underlying surface flux transport (SFT) model details. We demonstrate by both analytical and numerical methods that the factor relating the initial and ultimate dipole moment contributions of an active region displays a Gaussian dependence on latitude with parameters that only depend on details of the SFT model through the parameter η/Δu where η is supergranular diffusivity and Δu is the divergence of the meridional flow on the equator. In a comparison with cycles simulated in the 2 × 2D dynamo model we further demonstrate that the inaccuracies associated with the algebraic method are minor and the method may be able to reproduce the dipole moment values in a large majority of cycles.

Asteroseismic Signature of a Large Active Region

Axisymmetric magnetic activity on the Sun and Sun-like stars increases the frequencies of the modes of acoustic oscillation. However, it is unclear how a corotating patch of activity affects the oscillations, since such a perturbation is unsteady in the frame of the observer. In this paper we qualitatively describe the asteroseismic signature of a large active region in the power spectrum of the dipole and quadrupole p modes. In the corotating frame of the active region, the perturbations due to (differential) rotation and the active region completely lift the $(2\ell + 1)$-fold azimuthal degeneracy of the frequency spectrum of modes with harmonic degree $\ell$. In the frame of the observer, the unsteady nature of the perturbation leads to the appearance of $(2\ell+1)^2$ peaks in the power spectrum of a multiplet. These peaks blend into each other to form asymmetric line profiles. In the limit of a small active region, we approximate the power spectrum of a multiplet in terms of $2\times(2\ell+1)$ peaks, whose amplitudes and frequencies depend on the latitude of the active region and the inclination angle of the star's rotation axis. In order to check the results and to explore the nonlinear regime, we also perform numerical simulations using the 3D time-domain pseudo-spectral linear pulsation code GLASS.

Spectral Magnetic Helicity of Solar Active Regions between 2006 and 2017

Abstract We compute magnetic helicity and energy spectra from about 2485 patches of about 100 Mm side length on the solar surface using data from Hinode during 2006–2017. An extensive database is assembled where we list the magnetic energy and helicity, large- and small-scale magnetic helicity, mean current helicity density, fractional magnetic helicity, and correlation length along with the Hinode map identification number (MapID), as well as the Carrington latitude and longitude for each MapID. While there are departures from the hemispheric sign rule for magnetic and current helicities, the weak trend reported here is in agreement with the previous results. This is argued to be a physical effect associated with the dominance of individual active regions that contribute more strongly in the better-resolved Hinode maps. In comparison with earlier work, the typical correlation length is found to be 6– , while the length scale relating the magnetic and current helicities to each other is around .

The Effect of “Rogue” Active Regions on the Solar Cycle

The origin of cycle-to-cycle variations in solar activity is currently the focus of much interest. It has recently been pointed out that large individual active regions with atypical properties can have a significant impact on the long term behaviour of solar activity. We investigate this possibility in more detail using a recently developed 2$\times$2D dynamo model of the solar magnetic cycle. We find that even a single "rogue" bipolar magnetic region (BMR) in the simulations can have a major effect on the further development of solar activity cycles, boosting or suppressing the amplitude of subsequent cycles. In extreme cases an individual BMR can completely halt the dynamo, triggering a grand minimum. Rogue BMRs also have the potential to induce significant hemispheric asymmetries in the solar cycle. To study the effect of rogue BMRs in a more systematic manner, a series of dynamo simulations were conducted, in which a large test BMR was manually introduced in the model at various phases of cycles of different amplitudes. BMRs emerging in the rising phase of a cycle can modify the amplitude of the ongoing cycle while BMRs emerging in later phases will only impact subsequent cycles. In this model, the strongest impact on the subsequent cycle occurs when the rogue BMR emerges around cycle maximum at low latitudes but the BMR does not need to be strictly cross-equatorial. Active regions emerging as far as $20^{\circ}$ from the equator can still have a significant impact. We demonstrate that the combined effect of the magnetic flux, tilt angle and polarity separation of the BMR on the dynamo is via their contribution to the dipole moment, $\delta D_{\mathrm{BMR}}$. Our results indicate that prediction of the amplitude, starting epoch and duration of a cycle requires an accurate accounting of a broad range of active regions emerging in the previous cycle.

Measuring solar active region inflows with local correlation tracking of granulation

Context. Local helioseismology has detected spatially extended converging surface flows into solar active regions. These play an important role in flux-transport models of the solar dynamo. Aims. We aim to validate the existence of the inflows by deriving horizontal flow velocities around active regions with local correlation tracking of granulation. Methods. We generate a six-year long-time series of full-disk maps of the horizontal velocity at the solar surface by tracking granules in continuum intensity images provided by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). Results. On average, active regions are surrounded by inflows extending up to 10 deg from the center of the active region of magnitudes of 20-30 m/s, reaching locally up to 40 m/s, which is in agreement with results from local helioseismology. By computing an ensemble average consisting of 243 individual active regions, we show that the inflows are not azimuthally symmetric but converge predominantly towards the trailing polarity of the active region with respect to the longitudinally and temporally averaged flow field.

Statistical Analysis of Individual Solar Active Regions

AbstractIn the last decades, numerous observational and computational studies have shown that the global flare distribution is a power-law with a slope less than 2. In these studies, active regions are treated as statistically indistinguishable. To test this, we identify and separately analyze the flares produced by ten individual active regions (2006-2016). In five regions, we find a single power-law distribution, with a slope of a < 2. In the other five, we find a broken double power-law distribution, with slopes a1 < 2 and a2 > 2.