Active Region Model Research Articles

Energetic particle activity in AD Leo: Detection of a solar-like type-IV burst

Context. AD Leo is a young and active M dwarf with high flaring rates across the X-ray-to-radio bands. Flares accelerate particles in the outer coronal layers and often impact exo-space weather. Wide-band radio dynamic spectra let us explore the evolution of particle acceleration activity across the corona. Identifying the emission features and modelling the mechanisms can provide insights into the possible physical scenarios driving the particle acceleration processes.Aims. We performed an 8 h monitoring of AD Leo across the 550-850 MHz band using upgraded-Giant Metrewave Radio Telescope (uGMRT). The possible flare and post-flare emission mechanisms are explored based on the evolution of flux density and polarisation.Methods. The python-based module, Visibility Averaged Dynamic spectrum (VISAD), was developed to obtain the visibility-averaged wide-band dynamic spectra. Direct imaging was also performed with different frequency-time averaging. Based on existing observational results on AD Leo and on solar active region models, radial profiles of electron density and magnetic fields were derived. Applying these models, we explored the possible emission mechanisms and magnetic field profile of the flaring active region.Results. The star displayed a high brightness temperature (TB≈ 1010−1011K) throughout the observation. The emission was also nearly 100% left circularly polarised during bursts. The post-flare phase was characterised by a highly polarised (60–80%) solar-like type IV burst confined above 700 MHz.Conclusions. The flare emission favours a Z-mode or a higher harmonic X-mode electron cyclotron maser emission mechanism. The >700 MHz post-flare activity is consistent with a type-IV radio burst from flare-accelerated particles trapped in magnetic loops, which could be a coronal mass ejection (CME) signature. This is the first solar-like type-IV burst reported on a young active M dwarf belonging to a different age-related activity population (‘C’ branch) compared to the Sun (‘I’ branch). We also find that a multipole expansion model of the active region magnetic field better accounts for the observed radio emission than a solar-like active region profile.

First Insights into the Applicability and Importance of Different 3D Magnetic Field Extrapolation Approaches for Studying the Preeruptive Conditions of Solar Active Regions

The three-dimensional (3D) coronal magnetic field has not yet been directly observed. However, for a better understanding and prediction of magnetically driven solar eruptions, 3D models of solar active regions are required. This work aims to provide insight into the significance of different extrapolation models for analyzing the preeruptive conditions of active regions with morphological parameters in 3D. Here, we employed potential field (PF), linear force-free field (LFFF), and nonlinear force-free field (NLFFF) models and a neural network-based method integrating observational data and NLFFF physics (NF2). The 3D coronal magnetic field structure of a “flaring” (AR11166) and “flare-quiet” (AR12645) active region, in terms of their flare productivity, is constructed via the four extrapolation methods. To analyze the evolution of the field, six prediction parameters were employed throughout, from the photosphere up to the base of the lower corona. First, we find that the evolution of the adopted morphological parameters exhibits similarity across the investigated time period when considering the four types of extrapolations. Second, all the parameters exhibited preeruptive conditions not only at the photosphere but also at higher altitudes in the case of active region (AR) 11166, while three out of the six proxies also exhibited preeruptive conditions in the case of AR12645. We conclude that: (i) the combined application of several different precursor parameters is important in the lower solar atmosphere to improve eruption predictions, and (ii) to gain a quick yet reliable insight into the preflare evolution of active regions in 3D, the PF and LFFF are acceptable; however, the NF2 method is likely the more suitable option.

Coronal Abundances in an Active Region: Evolution and Underlying Chromospheric and Transition Region Properties

The element abundances in the solar corona and solar wind are often different from those of the solar photosphere, typically with a relative enrichment of elements with low first ionization potential (FIP effect). Here, we study the spatial distribution and temporal evolution of the coronal chemical composition in an active region (AR) over about 10 days, using Hinode/EIS spectra, and we also analyze coordinated IRIS observations of the chromospheric and transition region emission to investigate any evidence of the footprints of the FIP effect in the lower atmosphere. To derive the coronal abundances, we use a spectral inversion method recently developed for the MUSE investigation. We find that, in the studied active region (AR 12738), the coronal FIP bias, as diagnosed by the Si/S abundance ratio, presents significant spatial variations, with its highest values (∼2.5–3.5) in the outflow regions at the boundary of the AR, but typically modest temporal variability. Some moss regions and some regions around the AR sunspot show enhanced FIP bias (∼2–2.5) with respect to the AR core, which has only a small FIP bias of ∼1.5. The FIP bias appears most variable in these moss regions. The IRIS observations reveal that the chromospheric turbulence, as derived from IRIS2 inversions of the Mg ii spectra, is enhanced in the outflow regions characterized by the high FIP bias, providing significant new constraints to both models aimed at explaining the formation of AR outflows and models of chemical fractionation.

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.

A comparative evaluation of soil preferential flow of mulched drip irrigation cotton field in Xinjiang based on dyed image variability versus fractal characteristic parameter

Preferential flow in soil has a potential impact on the maintenance of the agricultural ecosystem. The aim of this study was to quantify and evaluate the characteristics of preferential flow in drip irrigation cotton fields in Xinjiang. We applied the dye tracer method, addressed the variability in stained images, collected soil samples in the excavated soil profile, and calculated the fractal parameters in four key growth stages of cotton in 2021. According to the dyeing mode, the dyed area ratio tended to keep decreasing from the soil surface; a down movement of points which drastically dropped to zero appeared at pace with the growth of the cotton (from −10 cm to −30 cm). Statistics obtained from the staining images showed that the preferential flow degree was highest at the boll opening stage; no significant difference in non-uniformity emerged from different treatments at the same growing stage (p > 0.05). Conversely, the fractal feature parameters in the active region model probed that the preferential flow degree was developed at the flowering & bolling stage in treatments with opaque oxidation-biodegradable film mulching (B,W), and at boll opening stage with plastic film mulching (P). During the same growth period, a significant difference (p < 0.05) existed between different groups. In comparison, the fractal feature parameter was found more adequate and effective in evaluating the characteristics of preferential flow in drip irrigation cotton fields. This research will provide practical information for the local department to adjust some agronomic measures to reduce the risk of low irrigation water utilization efficiency.

Solar Active Region Detection Using Deep Learning

Solar eruptive events could affect radio communication, global positioning systems, and some high-tech equipment in space. Active regions on the Sun are the main source regions of solar eruptive events. Therefore, the automatic detection of active regions is important not only for routine observation, but also for the solar activity forecast. At present, active regions are manually or automatically extracted by using traditional image processing techniques. Because active regions dynamically evolve, it is not easy to design a suitable feature extractor. In this paper, we first overview the commonly used methods for active region detection currently. Then, two representative object detection models, faster R-CNN and YOLO V3, are employed to learn the characteristics of active regions, and finally establish a deep learning–based detection model of active regions. The performance evaluation demonstrates that the high accuracy of active region detection is achieved by both the two models. In addition, YOLO V3 is 4% and 1% better than faster R-CNN in terms of true positive (TP) and true negative (TN) indexes, respectively; meanwhile, the former is eight times faster than the latter.

Solvent Effect on the Stability and Reverse Substituent Effect in Nitropurine Tautomers

The solvent effect on the stability and electron-accepting properties (EA) of the nitro group attached to the C2, C6, or C8 position of nitropurine NH tautomers is investigated. For this purpose, the density functional theory (DFT) and the polarizable continuum model (PCM) of solvation in a wide range of solvents (1 &lt; ε &lt; 109) are used. We show that the EA properties of the NO2 group, described by the charge of the substituent active region (cSAR) model, are linearly dependent on the reciprocal of the solvent dielectric constant; in all cases, solvation enhances the EA properties of this group. Furthermore, the sensitivity of EA properties of the nitro group to the solvent effect depends on the proximity effects. It has been shown that the proximity of two endocyclic N atoms (two repulsive interactions) results in higher sensitivity than the asymmetric proximity of the endocyclic N atom and NH group (one repulsive and one attractive interaction). To explain this phenomenon, the geometry of the nitro group in coplanar form and after forcing its rotation around the CN bond is discussed. Relative stabilities of nitropurine tautomers in different solvents are also presented. Differences in the stabilities and solvation energies are explained by aromaticity, electronic structure, and intramolecular interactions of the nitropurine tautomers.

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.

Active Region Irradiance during Quiescent Periods: New Insights from Sun-as-a-star Spectra

Abstract How much energy do solar active regions (ARs) typically radiate during quiescent periods? This is a fundamental question for storage and release models of flares and ARs, yet it is presently poorly answered by observations. Here we use the “Sun-as-a-point-source” spectra from the EUV Variability Experiment (EVE) on the Solar Dynamics Observatory to provide a novel estimate of radiative energy losses of an evolving AR. Although EVE provides excellent spectral (5–105 nm) and temperature (2–25 MK) coverage for AR analysis, to our knowledge, these data have not been used for this purpose due to the lack of spatial resolution and the likelihood of source confusion. Here we present a way around this problem. We analyze EVE data time series, when only one large AR 11520 was present on the disk. By subtracting the quiet-Sun background, we estimate the radiative contribution in EUV from the AR alone. We estimate the mean AR irradiance and cumulative AR radiative energy losses in the 1–300 Å and astronomical standard ROSAT-PSPC, 3–124 Å, passbands and compare these to the magnetic energy injection rate through the photosphere, and to variations of the solar cycle luminosity. We find that while AR radiative energy losses are ∼100 times smaller than typical magnetic energy injection rates at the photosphere, they are an order of magnitude larger or similar to the bolometric radiated energies associated with large flares. This study is the first detailed analysis of AR thermal properties using EVE Sun-as-a-star observations, opening doors to AR studies on other stars.

Mutual Relations between Substituent Effect, Hydrogen Bonding, and Aromaticity in Adenine-Uracil and Adenine-Adenine Base Pairs.

The electronic structure of substituted molecules is governed, to a significant extent, by the substituent effect (SE). In this paper, SEs in selected nucleic acid base pairs (Watson-Crick, Hoogsteen, adenine-adenine) are analyzed, with special emphasis on their influence on intramolecular interactions, aromaticity, and base pair hydrogen bonding. Quantum chemistry methods—DFT calculations, the natural bond orbital (NBO) approach, the Harmonic Oscillator Model of Aromaticity (HOMA) index, the charge of the substituent active region (cSAR) model, and the quantum theory of atoms in molecules (QTAIM)—are used to compare SEs acting on adenine moiety and H-bonds from various substitution positions. Comparisons of classical SEs in adenine with those observed in para- and meta-substituted benzenes allow for the better interpretation of the obtained results. Hydrogen bond stability and its other characteristics (e.g., covalency) can be significantly changed as a result of the SE, and its consequences are dependent on the substitution position. These changes allow us to investigate specific relations between H-bond parameters, leading to conclusions concerning the nature of hydrogen bonding in adenine dimers—e.g., H-bonds formed by five-membered ring nitrogen acceptor atoms have an inferior, less pronounced covalent nature as compared to those formed by six-membered ring nitrogen. The energies of individual H-bonds (obtained by the NBO method) are analyzed and compared to those predicted by the Espinosa-Molins-Lecomte (EML) model. Moreover, both SE and H-bonds can significantly affect the aromaticity of adenine rings; long-distance SEs on π-electron delocalization are also documented.

State-of-the-art AGN SEDs for photoionization models: BLR predictions confront the observations

ABSTRACT The great power offered by photoionization models of active galactic nuclei emission line regions has long been mitigated by the fact that very little is known about the spectral energy distribution (SED) between the Lyman limit, where intervening absorption becomes a problem, and 0.3 keV, where soft X-ray observations become possible. The emission lines themselves can, to some degree, be used to probe the SED, but only in the broadest terms. This paper employs a new generation of theoretical SEDs that are internally self-consistent, energy conserving, and tested against observations, to infer properties of the emission-line regions. The SEDs are given as a function of the Eddington ratio, allowing emission-line correlations to be investigated on a fundamental basis. We apply the simplest possible tests, based on the foundations of photoionization theory, to investigate the implications for the geometry of the emission-line region. The SEDs become more far-ultraviolet bright as the Eddington ratio increases, so the equivalent widths of recombination lines should also become larger, an effect that we quantify. The observed lack of correlation between Eddington ratio and equivalent width shows that the cloud covering factor must decrease as Eddington ratio increases. This would be consistent with recent models proposing that the broad-line region is a failed dusty wind off the accretion disc.

Relative field-line helicity in bounded domains

Models for astrophysical plasmas often have magnetic field lines that leave the boundary rather than closing within the computational domain. Thus, the relative magnetic helicity is frequently used in place of the usual magnetic helicity, so as to restore gauge invariance. We show how to decompose the relative helicity into a relative field-line helicity that is an ideal-magnetohydrodynamic invariant for each individual magnetic field line, and vanishes along any field line where the original field matches the reference field. Physically, this relative field-line helicity is a magnetic flux, whose specific definition depends on the gauge of the reference vector potential on the boundary. We propose a particular ‘minimal’ gauge that depends only on the reference field and minimises this boundary contribution, so as to reveal topological information about the original magnetic field. We illustrate the effect of different gauge choices using the Low–Lou and Titov–Démoulin models of solar active regions. Our numerical code to compute appropriate vector potentials and relative field-line helicity in Cartesian domains is open source and freely available.

TRACING THE CHROMOSPHERIC AND CORONAL MAGNETIC FIELD WITH AIA, IRIS, IBIS, AND ROSA DATA

ABSTRACT The aim of this study is to explore the suitability of chromospheric images for magnetic modeling of active regions. We use high-resolution images ( ), from the Interferometric Bidimensional Spectrometer in the Ca ii 8542 Å line, the Rapid Oscillations in the Solar Atmosphere instrument in the Hα 6563 Å line, the Interface Region Imaging Spectrograph in the 2796 Å line, and compare non-potential magnetic field models obtained from those chromospheric images with those obtained from images of the Atmospheric Imaging Assembly in coronal (171 Å, etc.) and in chromospheric (304 Å) wavelengths. Curvi-linear structures are automatically traced in those images with the OCCULT-2 code, to which we forward-fitted magnetic field lines computed with the Vertical-current Approximation Nonlinear Force Free Field code. We find that the chromospheric images: (1) reveal crisp curvi-linear structures (fibrils, loop segments, spicules) that are extremely well-suited for constraining magnetic modeling; (2) that these curvi-linear structures are field-aligned with the best-fit solution by a median misalignment angle of –7°; (3) the free energy computed from coronal data may underestimate that obtained from cromospheric data by a factor of –4, (4) the height range of chromospheric features is confined to km, while coronal features are detected up to h = 35,000 km; and (5) the plasma-β parameter is for all traced features. We conclude that chromospheric images reveal important magnetic structures that are complementary to coronal images and need to be included in comprehensive magnetic field models, something that is currently not accomodated in standard NLFFF codes.

Particle dynamics in a non-flaring solar active region model

The aim of this work is to investigate and characterise particle behaviour in an (observationally-driven) 3D MHD model of the solar atmosphere above a slowly evolving, non-flaring active region. We use a relativistic guiding-centre particle code to investigate the behaviour of selected particle orbits, distributed throughout a single snapshot of the 3D MHD simulation. Two distinct particle acceleration behaviours are recovered, which affect both electrons and protons: (i) direct acceleration along field lines and (ii) tangential drifting of guiding centres with respect to local magnetic field. However, up to 40\% of all particles actually experience a form of (high energy) particle trap, because of changes in the direction of the electric field and unrelated to the strength of the magnetic field; such particles are included in the first category. Additionally, category (i) electron and proton orbits undergo surprisingly strong acceleration to non-thermal energies ($\lesssim42$MeV), because of the strength and extent of super-Dreicer electric fields created by the MHD simulation. Reducing the electric field strength of the MHD model does not significantly affect the efficiency of the (electric field-based) trapping mechanism, but does reduce the peak energies gained by orbits. We discuss the implications for future experiments, which aim to simulate non-flaring active region heating and reconnection.

Modeling bacterial attenuation in on-site wastewater treatment systems using the active region model and column-scale data

Bacterial attenuation in porous media is often higher in columns than in the field. This study investigates whether this inconsistency could be attributed to finger flow, as assessed by the active ...

CORONAL MAGNETOGRAPHY OF A SIMULATED SOLAR ACTIVE REGION FROM MICROWAVE IMAGING SPECTROPOLARIMETRY

We have simulated the Expanded Owens Valley Solar Array (EOVSA) radio images generated at multiple frequencies from a model solar active region, embedded in a realistic solar disk model, and explored the resulting datacube for different spectral analysis schemes to evaluate the potential for realizing one of EOVSA's most important scientific goals--coronal magnetography. In this paper, we focus on modeling the gyroresonance and free-free emission from an on-disk solar active region model with realistic complexities in electron density, temperature and magnetic field distribution. We compare the magnetic field parameters extrapolated from the image datacube along each line of sight after folding through the EOVSA instrumental profile with the original (unfolded) parameters used in the model. We find that even the most easily automated, image-based analysis approach (Level 0) provides reasonable quantitative results, although they are affected by systematic effects due to finite sampling in the Fourier (uv) plane. Finally, we note the potential for errors due to misidentified harmonics of the gyrofrequency, and discuss the prospects for applying a more sophisticated spectrally-based analysis scheme (Level 1) to resolve the issue in cases where improved uv coverage and spatial resolution are available.

Experimental study and simulations of infiltration in evapotranspiration landfill covers

Various cover systems have been designed for landfill sites in order to minimize infiltration (percolation) into the underlying waste. This study evaluated the soil water balance performance of evapotranspiration covers (ET covers) and simulated percolation in the systems using the active region model (ARM). Experiments were conducted to measure water flow processes and water balance components in a bare soil cover and different ET covers. Results showed that vegetation played a critical role in controlling the water balance of the ET covers. In soil profiles of 60-cm depth with and without vegetation cover, the maximum soil water storage capacities were 97.2 mm and 62.8 mm, respectively. The percolation amount in the bare soil was 2.1 times that in the vegetation-covered soil. The ARM simulated percolation more accurately than the continuum model because it considered preferential flow. Numerical simulation results also indicated that using the ET cover system was an effective way of removing water through evapotranspiration, thus reducing percolation.

DETERMINING HEATING TIMESCALES IN SOLAR ACTIVE REGION CORES FROM AIA/SDOFe XVIII IMAGES

We present a study of the frequency of transient brightenings in the core of solar active regions as observed in the Fe XVIII line component of AIA/SDO 94 A filter images. The Fe XVIII emission is isolated using an empirical correction to remove the contribution of "warm" emission to this channel. Comparing with simultaneous observations from EIS/Hinode, we find that the variability observed in Fe XVIII is strongly correlated with the emission from lines formed at similar temperatures. We examine the evolution of loops in the cores of active regions at various stages of evolution. Using a newly developed event detection algorithm we characterize the distribution of event frequency, duration, and magnitude in these active regions. These distributions are similar for regions of similar age and show a consistent pattern as the regions age. This suggests that these characteristics are important constraints for models of solar active regions. We find that the typical frequency of the intensity fluctuations is about 1400s for any given line-of-sight, i.e. about 2-3 events per hour. Using the EBTEL 0D hydrodynamic model, however, we show that this only sets a lower limit on the heating frequency along that line-of-sight.

Investigation into preferential flow in natural unsaturated soils with field multiple-tracer infiltration experiments and the active region model

Preferential flow in natural unsaturated soils is common, but difficult to characterize and predict. The major objective of this research is to investigate the preferential flow patterns with field-scale multiple-tracer infiltration experiments and to evaluate the capability of the active region model (ARM) in predicting the field-scale preferential flow and transport processes. For this purpose, the mixture solutions of iodine and bromide, iodine and nitrate, and again iodine and bromide, as the tracing solutes, were applied sequentially in two plots in natural unsaturated loam soil to illustrate the flow and transport processes. The distributions of soil water content and concentrations of applied tracing solutes (NO3- and Br−) were measured after experiments and predicted using ARM and the mobile–immobile region model (MIM). The relative root mean square errors (RRMSE) between those predictions (from ARM and MIM) and measured results were calculated for quantitatively evaluating the prediction accuracy and comparing the modeling efficiency of the two models. Both field observations and the ARM predictions indicated that there were macropores in Plot 1 but not in Plot 2, and the macropores in Plot 1 were mainly in the top 20cm soil layer. The mixture solutions transported in the top 20cm soil layer in Plot 1 were mainly from the soil surface directly and less affected by the macropore flow, while the preferential flow in the soil layer below 20cm was considerably affected by the macropores and more applied mixture solutions were delivered into the deep soil layer quickly. Compared to the mixture solutions applied in the first and third steps, more mixture solution applied in the second step was transported to the deep soil layer by macropores, corresponding to obvious peaks of soil water content and NO3- concentration distributions observed in the deep soil layer in Plot 1. On the other hand, unstable flow was the major preferential flow behavior in Plot 2, inducing no obvious peaks of soil water content and solutes (NO3- and Br−) concentrations observed in the infiltrated soil profile. The comparisons between predicted and observed results in Plot 2 indicated that the ARM captured the overall behavior of unstable flow and associated tracer transport better than the MIM; however, to well characterize the macropore flow process, the ARM needs to be improved to include the effects of macropores.

Exploration of the spatial-Composite Risk Index (CRI) for the characterization of toxicokinetics in petrochemical active areas

The spatial modeling of the petrochemical active regions in the Niger Delta (ND), Nigeria was carried out through the analysis exploration and extraction of geospatial data and resultant risk maps were generated. The pollutants assessed include; heavy metals, polychlorinated aromatic hydrocarbons (PAHs), benzene–toluene–ethylene–xylene (BTEX), and total petroleum hydrocarbons (TPHs) and properties of the pollutants such as bioaccumulation, persistence and toxicity were used to calculate the Hazard Index (HI) and thus created a ranking system. The Composite Risk Index (CRI) was developed successively considering the concentrations of all pollutants and the computed HI using the samples collected in ND areas of Nigeria. The carcinogenic PAHs showed spatial abundance in the areas sampled and elevated levels of soil heavy metals were also observed. In this study, mathematical tool such as the artificial neural network (ANN) self-organizing map (SOM) and geostatistical analysis such as kriging were applied to develop the risk map of the areas which represent the spatial spread of the CRI. The results show that the application of spatially developed integral risk map for pollutant assessment is effective and facilitates with decision making with regards the environment and humans exposed in this region.