Helioseismic And Magnetic Imager Research Articles

Analysis of modeled 3D solar magnetic field during 30 X/M-class solar flares

Using non-linear force free field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-min cadence Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of 1 hour before through 1 hour after the start of 18 X-class and 12 M-class solar flares. Several magnetic field parameters were calculated from the modeled fields directly, as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis, for two different regions: areas with photospheric |Bz|≥ 300 G (active region—AR) and areas above the photosphere with the magnitude of the non-potential field (BNP) greater than three standard deviations above |BNP|̄ of the AR field and either the unsigned twist number |Tw| ≥ 1 turn or the shear angle Ψ ≥ 80° (non-potential region—NPR). Superposed epoch (SPE) plots of the magnetic field parameters were analyzed to investigate the evolution of the 3D solar field during the solar flare events and discern consistent trends across all solar flare events in the dataset, as well as across subsets of flare events categorized by their magnetic and sunspot classifications. The relationship between different flare properties and the magnetic field parameters was quantitatively described by the Spearman ranking correlation coefficient, rs. The parameters that showed the most consistent and discernable trends among the flare events, particularly for the hour leading up to the eruption, were the total unsigned flux ϕ), free magnetic energy (EFree), total unsigned magnetic twist (τTot), and total unsigned free magnetic twist (ρTot). Strong (|rs| ∈ [0.6, 0.8)) to very strong (|rs| ∈ [0.8, 1.0]) correlations were found between the magnetic field parameters and the following flare properties: peak X-ray flux, duration, rise time, decay time, impulsiveness, and integrated flux; the strongest correlation coefficient calculated for each flare property was 0.62, 0.85, 0.73, 0.82, −0.81, and 0.82, respectively.

Improving the spatial resolution of solar images using super-resolution diffusion generative adversarial networks

High-spatial-resolution solar images contribute to the study of small-scale structures on the Sun. The Helioseismic and Magnetic Imager (HMI) conducts continuous full-disk observations of the Sun at a fixed cadence, accumulating a wealth of observational data. However, the spatial resolution of HMI images is not sufficient to analyze the small-scale structures of solar activity. We present a new super-resolution (SR) method based on generative adversarial networks (GANs) and denoising diffusion probabilistic models (DDPMs) that can increase the spatial resolution of HMI images by a factor four. We propose a method called super-resolution diffusion GANs (SDGAN), which combines GANs and DDPMs for the SR reconstruction of HMI images. SDGAN progressively maps low-resolution (LR) images to high-resolution (HR) images through a conditional denoising process. It employs conditional GANs to simulate the denoising distribution and optimizes model results using nonsaturating adversarial loss and perceptual loss. This approach enables fast and high-quality reconstruction of solar images. We used high-spatial-resolution images from the Goode Solar Telescope (GST) as HR images and created a data set consisting of paired images from HMI and GST. We then used this data set to train SDGAN for the purpose of reconstructing HMI images with four times the original spatial resolution. The experimental results demonstrate that SDGAN can obtain high-quality HMI reconstructed images with just four denoising steps.

An Experimental Study on EUV‐To‐Magnetogram Image Translation Using Conditional Generative Adversarial Networks

AbstractDeep generative models have recently become popular in heliophysics for their capacity to fill in gaps in solar observational data sets, thereby helping mitigating the data scarcity issue faced in space weather forecasting. A particular type of deep generative models, called conditional Generative Adversarial Networks (cGAN), has been used since a few years in the context of image‐to‐image (I2I) translation on solar observations. These algorithms have however hyperparameters whose values might influence the quality of the synthetic image. In this work, we use magnetograms produced by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) and EUV images from the Atmospheric Imaging Assembly (AIA) for the problem of generating Artificial Intelligence (AI) synthetic magnetograms from multiple SDO/AIA channels using cGAN, and more precisely the Pix2PixCC algorithm. We perform a systematic study of the most important hyperparameters to investigate which hyperparameter might generate magnetograms of highest quality with respect to the Structural Similarity Index. We propose a structured way to perform training with various hyperparameter values, and provide diagnostic and visualization tools of the generated versus targeted image. Our results shows that when using a larger number of filters in the convolution blocks of the cGAN, the fine details in the generated magnetogram are better reconstructed. Adding several input channels besides the 304 Å channel does not improve the quality of generated magnetogram, but the hyperparameters controlling the relative importance of the different loss functions in the optimization process have an influence on the quality of the results.

Asymmetry of the spectral lines of the coronal hole and quiet Sun in the transition region

ABSTRACT The asymmetry of line profiles, i.e. the secondary component, is crucial to understanding the energy release of coronal holes (CH), quiet Sun (QS), and bright points (BPs). We investigate the asymmetry of Si iv 1393.75 Å of the transition-region (TR) line recorded by Interface Region Imaging Spectrograph (IRIS) and co-spatial-temporal Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI) data onboard Solar Dynamics Observatory (SDO) for three time series on 2015 April 26, 2014 July 24, and 2014 July 26. Most asymmetric profiles are in the complex magnetic field regions of the networks. The asymmetric profiles are fitted with both single and double Gaussian models. The mean value of Doppler velocity of the second component is almost zero (with a significant standard deviation) in QS/CH, which may indicate that the physical process to trigger the secondary Gaussian originates at the formation height of Si iv. While the mean Doppler velocity from secondary Gaussian in BPs is around +4.0 km s−1 (redshifted). The non-thermal velocities of the secondary Gaussian in all three regions are slightly higher than the single Gaussian. The statistical investigation leads to the prevalence of blueshifted secondary components in QS/CH. However, secondary Gaussian in the BPs redshifted, i.e. the BPs redshift behaviour could be interpreted due to the site of reconnection located above the formation height of the Si iv line. The peak intensity of the second component for all three regions is likely to follow a power law that is a signature of the small-scale flaring-like trigger mechanism.

Transport of the magnetic flux away from a decaying sunspot via convective motions

The interaction between magnetic fields and convection in sunspots during their decay process remains poorly understood,， whereas the formation of sunspots is relatively well studied and fully modeled. Works on the velocity scales at the solar surface have pointed to the existence of the family of granules, whose interaction with the magnetic field leads to the formation of supergranules and their networks, which are visible at the solar surface. The aim of this paper is to consider relationship between the decay of sunspots and convection via the motion of the family of granules and how the diffusion mechanism of magnetic field operates in a decaying sunspot. We report the decay of a sunspot observed by the 1.6m Goode Solar Telescope (GST) with the TiO Broadband Filter Imager (BFI) and the Near-InfraRed Imaging Spectropolarimeter (NIRIS). The analysis was aided by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamic Observatory (SDO). In the first step, we followed the decay of the sunspot with HMI data over three days by constructing its evolving area and total magnetic flux. In the second step, the high spatial and temporal resolution of the GST instruments allowed us to analyze the causes of the decay of the sunspot. Afterward, we followed the emergence of granules in the moat region around the sunspot over six hours. The evolution of the trees of fragmenting granules (TFGs) was derived based on their relationship with the horizontal surface flows. We find that the area and total magnetic flux display an exponential decrease over the course of the sunspot decay. We identified 22 moving magnetic features (MMFs) in the moats of pores, which is a signature of sunspot decay through diffusion. We note that the MMFs were constrained to follow the borders of TFGs during their journey away from the sunspot. The TFGs and their development contribute to the diffusion of the magnetic field outside the sunspot. The conclusion of our analysis shows the important role of the TFGs in sunspot decay. Finally, the the family of granules evacuates the magnetic field.

Uncovering the heterogeneity of a solar flare mechanism with mixture models

The physics of solar flares occurring on the Sun is highly complex and far from fully understood. However, observations show that solar eruptions are associated with the intense kilogauss fields of active regions, where free energies are stored with field-aligned electric currents. With the advent of high-quality data sources such as the Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), recent works on solar flare forecasting have been focusing on data-driven methods. In particular, black box machine learning and deep learning models are increasingly being adopted in which underlying data structures are not modeled explicitly. If the active regions indeed follow the same laws of physics, similar patterns should be shared among them, reflected by the observations. Yet, these black box models currently used in the literature do not explicitly characterize the heterogeneous nature of the solar flare data within and between active regions. In this paper, we propose two finite mixture models designed to capture the heterogeneous patterns of active regions and their associated solar flare events. With extensive numerical studies, we demonstrate the usefulness of our proposed method for both resolving the sample imbalance issue and modeling the heterogeneity for rare energetic solar flare events.

Comparison of magnetic data products from Solar Orbiter SO/PHI-FDT and SDO/HMI

The Polarimetric and Helioseismic Imager (SO/PHI), on board the Solar Orbiter mission, is the first photospheric magnetograph and tachograph to observe the Sun from outside the Sun-Earth line. The Full Disc Telescope (FDT) of SO/PHI, images the whole solar disk with a spatial resolution that varies with the distance between the Sun and the spacecraft. To check for consistency between the magnetic field strength ($B$), the field inclination (gamma ), the line-of-sight (LoS) magnetic component ($B_ LoS $) and the field azimuth (phi ), inferred by SO/PHI-FDT and the Helioseismic and Magnetic Imager (HMI), on board Solar Dynamics Observatory (SDO), and obtain linear correlation coefficients among them. We use data from both instruments obtained on 8 March 2022, when the angle between SDO and Solar Orbiter was $3.4^ circ $ and the solar disk showed four developed active regions. Before comparing the magnetic field products of both instruments we perform a precise alignment of the data, including a matching of the plate scale. Further, in order to improve the homogeneity of the compared data products, the SDO/HMI data were convolved with the SO/PHI-FDT point spread function (PSF). The linear correlation coefficients are obtained through a linear regression of SDO/HMI to SO/PHI-FDT. The two instruments yield comparable magnetic field data products. The slope coefficients for a linear fit are 1.37 for $B$, 1.11 for gamma , 1.35 for $B_ LoS $ and 1 for the azimuth. The corresponding fit offsets are $-94$ G, $-9.8^ circ $, $5.2$ G and $0.1^ circ $, respectively. The agreement between both instruments is significantly better when we take into account the different spatial resolution of both instruments. The fitting results vary slightly depending on the analyzed active region except for one of the four active regions, which shows larger differences and has been excluded from the comparison. The comparison of the LoS magnetic field products from SDO/HMI at 45 s and 720 s with SO/PHI-FDT shows a slope value of 1.17, with the offset less than $6$ G, in both cases.

Solar cycle variation in the properties of photospheric magnetic concentrations

It is widely accepted that eruptive phenomena on the Sun are related to the solar magnetic field, which is closely tied to the observed magnetic concentrations (MCs). Therefore, studying MCs is critical in order to understand the origin and evolution of all forms of solar activity. In this paper, we investigate the statistics of characteristic physical parameters of MCs during a whole solar cycle by analyzing magnetograms from 2010 to 2021 observed by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). We discover that there are differences between large- and small-scale MCs in diffenent phases of the solar cycle. By analyzing the distributions of the magnetic flux, area, and magnetic energy of MCs, we find that the small-scale MCs obey a power-law distribution, and that the power indices vary very little with the phases of the solar cycle. However, for the large-scale MCs, although they also obey the power-law distribution, the power indices are clearly modulated by the different phases of the solar cycle. We also investigate the relation between the maximum magnetic field strength (Bmax) and the area of MCs (S) and find the same property. The relation for the large-scale MCs is modulated by the phases of the solar cycle, while it is still independent of the phases of the solar cycle for the small-scale MCs. Our results suggest that small- and large-scale MCs could be generated by different physical mechanisms.

A Transfer Learning Method to Generate Synthetic Synoptic Magnetograms

AbstractCurrent magnetohydrodynamics (MHD) models largely rely on synoptic magnetograms, such as the ones produced by the Global Oscillation Network Group (GONG). Magnetograms are currently available mostly from the front side of the Sun, which significantly reduces the accuracy of MHD modeling. Extreme Ultraviolet (EUV) images can instead be obtained from other vantage points. To investigate the potential, we explore the possibility of using EUV information from the Atmospheric Imaging Assembly (AIA) to directly generate the input for the state‐of‐the‐art 3D MHD model European Heliospheric FORecasting Information Asset (EUHFORIA). Toward this goal, we develop a method called Transfer‐Solar‐GAN which combines a conditional generative adversarial network with a transfer learning approach to overcome training data set limitations. The source domain data set is constructed from multiple pairs of the central portion of co‐registered AIA and Helioseismic and Magnetic Imager (HMI) line of sight (LOS) full‐disk images, while the target domain is constructed from pairs of portions of AIA and GONG sine‐latitude synoptic maps that we call segments. We evaluate Transfer‐Solar‐GAN by comparing modeled and measured solar wind velocity and magnetic field density parameters at the L1 Lagrange point and along the Parker Solar Probe (PSP) trajectory which were determined with EUHFORIA using both empirical GONG and artificial‐intelligence (AI)‐synthetic synoptic magnetograms as inputs. Our results demonstrate that the Transfer‐Solar‐GAN model can provide the necessary information to run solar physics models by EUV information. Our proposed model is trained with only 528 paired image segments and enforces a reliable data division strategy.

Can Proton Beam Heating Flare Models Explain Sunquakes?

Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) observations reveal a class of solar flares with substantial energy and momentum impacts in the photosphere, concurrent with white-light emission and helioseismic responses, known as sunquakes. Previous radiative hydrodynamic modeling has demonstrated the challenges of explaining sunquakes in the framework of the standard flare model of “electron beam” heating. One of the possibilities to explain the sunquakes and other signatures of the photospheric impact is to consider additional heating mechanisms involved in solar flares, for example via flare-accelerated protons. In this work, we analyze a set of single-loop Fokker–Planck and radiative hydrodynamics RADYN+FP simulations where the atmosphere is heated by nonthermal power-law-distributed proton beams which can penetrate deeper than the electron beams into the low atmospheric layers. Using the output of the RADYN models, we calculate synthetic Fe i 6173 Å line Stokes profiles and from those the line-of-sight observables of the SDO/HMI instrument, as well as the 3D helioseismic response, and compare them with the corresponding observational characteristics. These initial results show that the models with proton beam heating can produce the enhancement of the HMI continuum observable and explain qualitatively the generation of sunquakes. The continuum observable enhancement is evident in all models but is more prominent in ones with E c ≥ 500 keV. In contrast, the models with E c ≤ 100 keV provide a stronger sunquake-like helioseismic impact according to the 3D acoustic modeling, suggesting that low-energy (deka- and hecto-keV) protons have an important role in the generation of sunquakes.

Solar active region magnetogram image dataset for studies of space weather

In this dataset we provide a comprehensive collection of line-of-sight (LOS) solar photospheric magnetograms (images quantifying the strength of the photospheric magnetic field) from the National Aeronautics and Space Administration’s (NASA’s) Solar Dynamics Observatory (SDO). The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Imager (HMI) magnetograms of solar active regions (regions of large magnetic flux, generally the source of eruptive events) as well as labels of corresponding flaring activity. This dataset will be useful for image analysis or solar physics research related to magnetic structure, its evolution over time, and its relation to solar flares. The dataset will be of interest to those researchers investigating automated solar flare prediction methods, including supervised and unsupervised machine learning (classical and deep), binary and multi-class classification, and regression. This dataset is a minimally processed, user configurable dataset of consistently sized images of solar active regions that can serve as a comprehensive image dataset of LOS photospheric magnetograms for solar flare prediction research.

Spectro-polarimetric Properties of Sunquake Sources in X1.5 Flare and Evidence for Electron and Proton Beam Impacts

The first significant sunquake event of Solar Cycle 25 was observed during the X1.5 flare of 2022 May 10, by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory. We perform a detailed spectro-polarimetric analysis of the sunquake photospheric sources, using the Stokes profiles of the Fe i 6173 Å line, reconstructed from the HMI linear and circular polarized filtergrams. The results show fast variations of the continuum emission with rapid growth and slower decay lasting 3–4 minutes, coinciding in time with the hard X-ray impulses observed by the Konus instrument on board the Wind spacecraft. The variations in the line core appeared slightly ahead of the variations in the line wings, showing that the heating started in the higher atmospheric layers and propagated downward. The most significant feature of the line profile variations is the transient emission in the line core in three of the four sources, indicating intense, impulsive heating in the lower chromosphere and photosphere. In addition, the observed variations of the Stokes profiles reflect transient and permanent changes in the magnetic field strength and geometry in the sunquake sources. Comparison with the radiative hydrodynamics models shows that the physical processes in the impulsive flare phase are substantially more complex than those predicted by proton and electron beam flare models currently presented in the literature.

A Comparison of Co-temporal Vector Magnetograms Obtained with HMI/SDO and SP/Hinode

Accurate measurement of magnetic fields is very important for understanding the formation and evolution of solar magnetic fields. Currently, there are two types of solar magnetic field measurement instruments: filter-based magnetographs and Stokes polarimeters. The former gives high temporal resolution magnetograms and the latter provides more accurate measurements of magnetic fields. Calibrating the magnetograms obtained by filter-based magnetographs with those obtained by Stokes polarimeters is a good way to combine the advantages of the two types. Our previous studies have shown that, compared to the magnetograms obtained by the Spectro-Polarimeter (SP) on board Hinode, those magnetograms obtained by both the filter-based Solar Magnetic Field Telescope (SMFT) of the Huairou Solar Observing Station and by the filter-based Michelson Doppler Imager (MDI) aboard SOHO have underestimated the flux densities in their magnetograms and systematic center-to-limb variations present in the magnetograms of both instruments. Here, using a sample of 75 vector magnetograms of stable alpha sunspots, we compare the vector magnetograms obtained by the Helioseismic and Magnetic Imager (HMI) aboard Solar Dynamics Observatory (SDO) with co-temporal vector magnetograms acquired by SP/Hinode. Our analysis shows that both the longitudinal and transverse flux densities in the HMI/SDO magnetograms are very close to those in the SP/Hinode magnetograms and the systematic center-to-limb variations in the HMI/SDO magnetograms are very minor. Our study suggests that using a filter-based magnetograph to construct a low spectral resolution Stokes profile, as done by HMI/SDO, can largely remove the disadvantages of the filter-type measurements and yet still possess the advantage of high temporal resolution.

Large Photospheric Doppler Shift in Solar Active Region 12673. I. Field-aligned Flows

Delta (δ) sunspots sometimes host fast photospheric flows along the central magnetic polarity inversion line (PIL). Here we study the strong Doppler shift signature in the central penumbral light bridge of solar active region NOAA 12673. Observations from the Helioseismic and Magnetic Imager (HMI) indicate highly sheared and strong magnetic fields. Large Doppler shifts up to 3.2 km s−1 appeared during the formation of the light bridge and persisted for about 16 hr. A new velocity estimator, called DAVE4VMwDV, reveals fast converging and shearing motion along the PIL from HMI vector magnetograms, and recovers the observed Doppler signal much better than an old version of the algorithm. The inferred velocity vectors are largely (anti-)parallel to the inclined magnetic fields, suggesting that the observed Doppler shift contains a significant contribution from the projected field-aligned flows. High-resolution observations from the Hinode/Spectro-Polarimeter further exhibit a clear correlation between the Doppler velocity and the cosine of the magnetic inclination, which is in agreement with HMI results and consistent with a field-aligned flow of about 9.6 km s−1. The complex Stokes profiles suggest significant gradients of physical variables along the line of sight. We discuss the implications on the δ-spot magnetic structure and the flow-driving mechanism.

The Sun’s Magnetic Power Spectra over Two Solar Cycles. I. Calibration between SDO/HMI and SOHO/MDI Magnetograms

The Sun’s magnetic field is strongly structured over a broad range of scales. Magnetic spatial power spectral analysis provides a powerful tool for understanding the various scales of magnetic fields and their interactions with plasma motions. We aim to investigate the power spectra using spherical harmonic decomposition of high-resolution Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) synoptic magnetograms covering three consecutive solar cycle minima, in a series of papers. As the first of the series, we calibrate and analyze the power spectra based on cotemporal SDO/HMI and SOHO/MDI data in this paper. For the first time, we find that the calibration factor r between SOHO/MDI and SDO/HMI varies with the spatial scale l of the magnetic field, where l is the degree of the spherical harmonic. The calibration factor satisfies . With the calibration function, most contemporaneous SOHO/MDI and SDO/HMI magnetograms show consistent power spectra from about 8 Mm to the global scales over about three orders of magnitude. Moreover, magnetic power spectra from SOHO/MDI and SDO/HMI maps show peaks/knees at l ≈ 120, corresponding to the typical supergranular scale (about 35 Mm) constrained from direct velocimetric measurements. This study paves the way for investigating the solar cycle dependence of supergranulation and magnetic power spectra in subsequent studies.

High-resolution imaging of solar pores

Context. Light bridges are bright, long, and narrow features that are typically connected to the formation or decay processes of sunspots and pores. Aims. The interaction of magnetic fields and plasma flows is investigated in the trailing part of an active region, where pores and magnetic knots evolve into a complex sunspot. The goal is to identify the photospheric and chromospheric processes, which transform the mainly vertical magnetic fields of pores into a sunspot with multiple umbral cores, light bridges, and rudimentary penumbrae. Methods. Conducting observations with a broad variety of telescopes and instruments provides access to different atmospheric layers and the changing morphology of features connected to strong magnetic fields. While the Helioseismic and Magnetic Imager (HMI) of the Solar Dynamics Observatory (SDO) provides full-disk continuum images and line-of-sight magnetograms, the fine structure and flows around a pore can be deduced from high-resolution observations in various wavelengths as provided by the Goode Solar Telescope (GST) at the Big Bear Solar Observatory (BBSO). Horizontal proper motions are evaluated applying local correlation tracking (LCT) to the available time series, whereas the connectivity of sunspot features can be established using the background-subtracted activity maps (BaSAMs). Results. Photospheric flow maps indicate radial outflows, where the light bridge connects to the surrounding granulation, whereas inflows are present at the border of the pores. In contrast, the chromospheric flow maps show strong radial outflows at superpenumbral scales, even in the absence of a penumbra in the photosphere. The region in between the two polarities is characterized by expanding granules creating strong divergence centers. Variations in BaSAMs follow locations of significant and persistent changes in and around pores. The resulting maps indicate low variations along the light bridge, as well as thin hairlines connecting the light bridge to the pores and strong variations at the border of pores. Various BaSAMs demonstrate the interaction of pores with the surrounding supergranular cell. The Hα line-of-sight velocity maps provide further insights into the flow structure, with twisted motions along some of the radial filaments around the pore with the light bridge. Furthermore, flows along filaments connecting the two polarities of the active region are pronounced in the line-of-sight velocity maps. Conclusions. The present observations reveal that even small-scale changes of plasma motions in and around pores are conducive to transform pores into sunspots. In addition, chromospheric counterparts of penumbral filaments appear much earlier than the penumbral filaments in the photosphere. Penumbra formation is aided by a stable magnetic feature that anchors the advection of magnetic flux and provides a connection to the surrounding supergranular cell, whereas continuously emerging flux and strong light bridges are counteragents that affect the appearance and complexity of sunspots and their penumbrae.

Effects of optimisation parameters on data-driven magnetofrictional modelling of active regions

Context. The solar magnetic field plays an essential role in the formation, evolution, and dynamics of large-scale eruptive structures in the corona. The estimation of the coronal magnetic field, the ultimate driver of space weather, particularly in the ‘low’ and ‘middle’ corona, is presently limited due to practical difficulties. Data-driven time-dependent magnetofrictional modelling (TMFM) of active region magnetic fields has been proven to be a useful tool to study the corona. The input to the model is the photospheric electric field that is inverted from a time series of the photospheric magnetic field. Constraining the complete electric field, that is, including the non-inductive component, is critical for capturing the eruption dynamics. We present a detailed study of the effects of optimisation of the non-inductive electric field on the TMFM of AR 12473. Aims. We aim to study the effects of varying the non-inductive electric field on the data-driven coronal simulations, for two alternative parametrisations. By varying parameters controlling the strength of the non-inductive electric field, we wish to explore the changes in flux rope formation and their early evolution and other parameters, for instance, axial flux and magnetic field magnitude. Methods. We used the high temporal and spatial resolution cadence vector magnetograms from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). The non-inductive electric field component in the photosphere is critical for energising and introducing twist to the coronal magnetic field, thereby allowing unstable configurations to be formed. We estimated this component using an approach based on optimising the injection of magnetic energy. Results. Our data show that flux ropes are formed in all of the simulations except for those with the lower values of these optimised parameters. However, the flux rope formation, evolution and eruption time varies depending on the values of the optimisation parameters. The flux rope is formed and has overall similar evolution and properties with a large range of non-inductive electric fields needed to determine the non-inductive electric field component that is critical for energising and introducing twist to the coronal magnetic field. Conclusions. This study shows that irrespective of non-inductive electric field values, flux ropes are formed and erupted, which indicates that data-driven TMFM can be used to estimate flux rope properties early in their evolution without needing to employ a lengthy optimisation process.

Circular ribbon flare triggered from an incomplete fan-spine configuration

Context. Circular ribbon flares are characterised by circular, semi-circular, or elliptical ribbon brightenings. As the physics of such solar events involves a true 3D magnetic topology, they have been extensively studied in contemporary solar research. Aims. In order to understand the triggering processes and the complex magnetic topology involved in circular ribbon flares, we carried out a thorough investigation of an M-class circular ribbon flare that originated within close proximity of a quasi-separatrix layer (QSL). Methods. We combined multi-wavelength Atmospheric Imaging Assembly (AIA) and Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) observations with photospheric Helioseismic and Magnetic Imager (HMI) observations and coronal magnetic field modelling analysis using the non-linear force free field (NLFFF) model. Results. The circular ribbon flare occurred from a complex magnetic configuration characterised by negative magnetic patches surrounded by positive-polarity regions on three sides. As the negative polarity patches were not surrounded by positive-polarity regions on all four sides, the corresponding coronal field was devoid of any null points. This led to the formation of an incomplete fan-spine-like configuration that deviated from classical fan-spine configurations in null-point topology. Further, an observationally identified QSL structure was situated within the active region, very close to the flaring region. The presence of the QSL was verified by the NLFFF modelling. The far end of the spine-like lines terminated very close to one footpoint location of the QSL lines. Our analysis suggests that activities at this location led to the activation of a flux rope situated within the fan-like lines and triggering of the circular ribbon flare via perturbation of the overall fan-spine-like structure. Further, we identified RHESSI X-ray sources from the footpoints of the QSL structure, which suggests that slipping reconnections can also lead to discernible signatures of particle acceleration.

Small-scale EUV features as the drivers of coronal upflows in the quiet Sun

Context. Coronal upflows in the quiet Sun are seen in a wide range of features, including jets and filament eruptions. The in situ measurements from Parker Solar Probe within ≈0.2 au have demonstrated that the solar wind is highly structured, showing abrupt and near-ubiquitous magnetic field reversals (i.e., switchbacks) on different timescales. The source of these structures has been associated with supergranular structures on the solar disc. This raises the question of whether there are additional small coronal features that contribute energy to the corona and produce plasma that potentially feeds into the solar wind. Aims. During the Solar Orbiter first science perihelion, high-resolution images of the solar corona were recorded using the Extreme Ultraviolet High Resolution Imager (HRIEUV) from the Extreme Ultraviolet Imager (EUI). The Hinode spacecraft was also observing at the same location providing coronal spectroscopic measurements. Combining the two datasets allows us to determine the cause of the weak upflows observed in the quiet Sun and the associated activity. Methods. We used a multi-spacecraft approach to characterise regions of upflows. The upflows were identified in the Fe XII emission line by the Hinode EUV Imaging Spectrometer (EIS). We then used imaging data from the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory (SDO/AIA) and the High Resolution Imagers (HRI) from EUI on board the Solar Orbiter to identify coronal features and magnetic field data from the SDO Helioseismic and Magnetic Imager (HMI). Interface Region Imaging Spectrograph (IRIS) observations were also used to understand the photospheric and chromospheric driving mechanisms. Results. We have identified two regions of coronal upflows in the quiet Sun, with respective sizes and lifetimes of (20 Mm2, 20 min) and (180 Mm2, several hours), which are contrasting dynamic events. Both examples show weak flux cancellation, indicating that the source of the upflows and enhancements is related to the magnetic field changes. The first event, a larger upflow region, shows velocities of up to −8.6 km s−1 at the footpoint of a complex loop structure. We observe several distinct extreme ultraviolet (EUV) features including frequent loop brightenings and plasma blobs travelling along closed coronal loops. The second upflow region has velocities of up to −7.2 km s−1. Within it, a complex EUV feature that lasts for about 20 min can be seen. This main feature has several substructures. During its appearance, a clear mini-filament eruption takes place at its location, before the EUV feature disappears. Conclusions. Two features, with contrasting properties, show upflows with comparable magnitudes. The first event, a complex loop structure, shares several similarities with active region upflows. The second one, a complex small-scale feature that could not have been well resolved with previous instruments, triggered a cascade of events, including a mini-filament that lead to a measurable upflow. This is remarkable for an EUV feature that many instruments can barely resolve. The complexity of the two events, including small loop brightenings and travelling plasma blobs for the first and EUV small-scale loops and mini-filament for the second one would not have been identifiable as the sources of upflow without an instrument with the spatial resolution of HRIEUV at this distance to the Sun. These results reinforce the importance of the smallest-scale features in the Sun and their potential relevance for and impact on the solar corona and the solar wind.

Direct assessment of SDO/HMI helioseismology of active regions on the Sun’s far side using SO/PHI magnetograms

Context. Earth-side observations of solar p modes can be used to image and monitor magnetic activity on the Sun’s far side. In this work, we use magnetograms of the far side obtained by the Polarimetric and Helioseismic Imager (PHI) on board Solar Orbiter (SO) to directly assess the validity of far-side helioseismic holography for the first time. Aims. We wish to co-locate the positions of active regions in helioseismic images and magnetograms and to calibrate the helioseismic measurements in terms of the magnetic field strength. Methods. We identified three magnetograms displaying a total of six active regions on the far side from 18 November 2020, 3 October 2021, and 3 February 2022. The first two dates are from the SO cruise phase and the third is from the beginning of the nominal operation phase. We computed contemporaneous seismic phase maps for these three dates using helioseismic holography applied to the time series of Dopplergrams from the Helioseismic and Magnetic Imager (HMI) at the Solar Dynamics Observatory (SDO). Results. Among the six active regions seen in SO/PHI magnetograms, five of them are identified on the seismic maps at almost the same positions as on the magnetograms. One region is too weak to be detected above the seismic noise. To calibrate the seismic maps, we fit a linear relationship between the seismic phase shifts and the unsigned line-of-sight magnetic field averaged over the active region areas extracted from the SO/PHI magnetograms. Conclusions. SO/PHI provides the strongest evidence so far that helioseismic imaging is able to provide reliable information on active regions on the far side, including their positions, areas, and the mean unsigned magnetic field.