Photospheric Magnetic Field Research Articles

Large-scale Spatial Cross-calibration of Hinode/SOT-SP and SDO/HMI

We investigate the cross-calibration of the Hinode/Solar Optical Telescope-Spectro-Polarimeter (SOT-SP) and Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) instrument metadata, specifically the correspondence of the scaling and pointing information. Accurate calibration of these data sets gives the correspondence needed by interinstrument studies and learning-based magnetogram systems, and is required for physically meaningful photospheric magnetic field vectors. We approach the problem by robustly fitting geometric models on correspondences between images from each instrument’s pipeline. This technique is common in computer vision, but several critical details are required when using scanning-slit spectrograph data like Hinode/SOT-SP. We apply this technique to data spanning a decade of the Hinode mission. Our results suggest corrections to the published Level 2 Hinode/SOT-SP data. First, an analysis on approximately 2700 scans suggests that the reported pixel size in Hinode/SOT-SP Level 2 data is incorrect by around 1%. Second, analysis of over 12,000 scans shows that the pointing information is often incorrect by dozens of arcseconds with a strong bias. Regression of these corrections indicates that thermal effects have caused secular and cyclic drift in Hinode/SOT-SP pointing data over its mission. We offer two solutions. First, direct coalignment with SDO/HMI data via our procedure can improve alignments for many Hinode/SOT-SP scans. Second, since the pointing errors are predictable, simple post-hoc corrections can substantially improve the pointing. We conclude by illustrating the impact of this updated calibration on derived physical data products needed for research and interpretation. Among other things, our results suggest that the pointing errors induce a hemispheric bias in estimates of radial current density.

A Comparative Study of Solar Active Region 12371 with Data-constrained and Data-driven Magnetohydrodynamic Simulations

We performed two data-based magnetohydrodynamic (MHD) simulations for solar active region 12371, which produced an M6.5 flare. The first simulation is a full data-driven simulation where the initial condition is given by a nonlinear force-free field (NLFFF). This NLFFF was extrapolated from photospheric magnetograms approximately 1 hr prior to the flare, and then a time-varying photospheric magnetic field is imposed at the bottom surface. The second simulation is also a data-driven simulation, but it stops driving at the bottom before the time of flare onset and then switches to the data-constrained simulation, where the horizontal component of the magnetic field varies according to an induction equation, while the normal component is fixed with time. Both simulations lead to an eruption, with both simulations producing highly twisted field lines before the eruption, which were not found in the NLFFF alone. After the eruption, the first simulation based on the time-varying photospheric magnetic field continues to produce sheared field lines after the flare without reproducing phenomena such as postflare loops. The second simulation reproduces the phenomena associated with flares well. However, in this case, the evolution of the bottom magnetic field is inconsistent with the evolution of the observed magnetic field. In this Letter, we report potential advantages and disadvantages in data-constrained and data-driven MHD simulations that need to be taken into consideration in future studies.

Evolution of Magnetic Fields and Energy Release Processes during Homologous Eruptive Flares

We explore the processes of the repetitive buildup and the explosive release of magnetic energy, together with the formation of magnetic flux ropes, which eventually resulted in three homologous eruptive flares of successively increasing intensities (i.e., M2.0, M2.6, and X1.0). The flares originated from NOAA active region 12017 between 2014 March 28 and 29. EUV observations and magnetogram measurements, together with coronal magnetic field modeling, suggest that the flares were triggered by the eruption of flux ropes that were embedded in a densely packed system of loops within a small part of the active region. In X-rays, the first and second events show similar evolutions, with single compact sources, while the third event exhibits multiple emission centroids, with a set of strong nonthermal conjugate sources at 50–100 keV during the hard X-ray peak. Over an interval of ≈ 44 hr, the photospheric magnetic field encompassing the three flares undergoes important phases of emergence and cancellation, together with significant changes near the polarity inversion lines within the flaring region. Our observations point toward the tether-cutting mechanism being the plausible triggering process of the eruptions. Between the second and third events, we observe a prominent phase of flux emergence that temporally correlates with the buildup phase of free magnetic energy in the active region corona. In conclusion, our analysis reveals efficient coupling between the rapidly evolving photospheric and coronal magnetic fields in the active region, leading to a continued phase of the buildup of free energy, which results in the homologous flares of successively increasing intensities.

Automatic Computation of Linear Magneto-Hydro-Static Equilibria

Deriving the physical parameters of observed phenomena in the solar atmosphere has fundamental importance, as these parameters are then employed to constrain and validate models. Here we report the development of a new computational algorithm based on a magneto-hydro-static model that computes the magnetic field in the solar atmosphere and automatically matches individual magnetic-field lines with observed structures that appear with enhanced emission in extreme-ultraviolet (EUV) images. Presently, for the quiet-Sun regions, we can only measure the vertical photospheric magnetic field B_{z}, as accurate horizontal magnetic field measurements are not available. Thus, vertical photospheric magnetic-field measurements are extrapolated into the upper atmosphere, from the photosphere to the corona, with a magneto-hydro-static model. Free model parameters are then optimized with a downhill-simplex method by comparing quantitatively magnetic-field lines with the enhanced emission of loop structures composing the so-called coronal bright points recorded in EUV images taken with the Atmospheric Imaging Assembly on-board the Solar Dynamics Observatory. The algorithm will be applicable to any solar image data where individual structures with an enhanced emission can be resolved. Most importantly, the algorithm can be employed to obtain the magnetic properties of these structures above the photosphere.

Incorporating polar field data for improved solar flare prediction

In this paper, we consider incorporating data associated with the sun’s north and south polar field strengths to improve solar flare prediction performance using machine learning models. When used to supplement local data from active regions on the photospheric magnetic field of the sun, the polar field data provides global information to the predictor. While such global features have been previously proposed for predicting the next solar cycle’s intensity, in this paper we propose using them to help classify individual solar flares. We conduct experiments using HMI data employing four different machine learning algorithms that can exploit polar field information. Additionally, we propose a novel probabilistic mixture of experts model that can simply and effectively incorporate polar field data and provide on-par prediction performance with state-of-the-art solar flare prediction algorithms such as the Recurrent Neural Network (RNN). Our experimental results indicate the usefulness of the polar field data for solar flare prediction, which can improve Heidke Skill Score (HSS2) by as much as 10.1%1.

Solar Polar Magnetic Fields: Comparing Full-disk and High-resolution Spectromagnetograph Data

This is the first systematic comparison between photospheric polar magnetic field data from a full-disk synoptic observing program, the National Solar Observatory’s Synoptic Optical Long-term Investigations of the Sun Vector Spectromagnetograph (SOLIS/VSM), and a high-resolution vector spectromagnetograph, the Hinode Solar Optical Telescope Spectropolarimeter (SOT/SP). Polar magnetic fluxes derived from longitudinal magnetic field measurements from both telescopes and from SOT/SP full-Stokes vector data are all compared in the form of polar synoptic maps. Measurements taken over 35 day periods with advantageous rotation axis tilt angle are used; observations extend to the poles, and no synthetic pole-filling is needed. Polar fluxes are derived from longitudinal data assuming an approximately radial field, whereas those derived from vector data are based on measured vector magnitude and direction. However, the full-vector measurements may have a detection problem: polar fields are observed as mostly transverse from (near) Earth, and Zeeman sensitivity to transverse fields is significantly lower than for longitudinal fields. Accordingly, the SOT/SP vector-based polar fluxes are lower than the longitudinal-based fluxes from both telescopes, a result driven by pixels without sufficient Q and U signals for the full-Stokes inversions to detect significant radial field but with good Stokes V signal implying a significant field. Furthermore, the SOT/SP longitudinal-based fluxes are significantly higher than their VSM counterparts because of superior seeing-free spatial resolution and longer observation time. The SOT/SP longitudinal-based polar fluxes appear large enough to account for radial interplanetary field measurements whereas the SOT/SP vector-based and the VSM ones are generally too low.

Investigating datasets with high IRIS burst prevalence

Context. Approximately 0.01% of all Si IV 1394 Å spectra sampled in 2013 and 2014 by the Interface Region Imaging Spectrograph (IRIS) have IRIS burst profiles. However, these events are not evenly distributed across datasets with 19.31% of these spectra being identified in only six (of more than 3500) rasters. Aims. Here, we investigate five of these six datasets, with the aim of understanding why they contain so many IRIS burst profiles. This research will help guide future targeted analyses of IRIS bursts. Methods. We analyse five datasets sampled by the IRIS satellite, studying both Si IV 1394 Å spectra and 1400 Å filter slit-jaw imager (SJI) data. IRIS burst profiles are identified through the use of an automated algorithm. Additionally, we study co-spatial line-of-sight photospheric magnetic field maps sampled by the Solar Dynamics Observatory’s Helioseismic and Magnetic Imager (SDO/HMI) instrument. Results. The majority of identified IRIS burst profiles (12 401 out of 13 904) found in the five datasets analysed here were localised to seven small regions in the time-distance domain (temporal durations of < 4 h and spatial lengths of < 12″ along the slit). The SJI data co-spatial to these regions contained long-lived or repetitive compact brightenings, matching the defined properties of UV bursts, which remained close to the IRIS slit throughout their evolutions. The IRIS burst profiles were not limited to the brightest pixels in the fields of view (FOVs) nor did they comprise the majority of bright (> 500 DN/s) pixels. These IRIS burst profiles occurred co-spatial to evolving (e.g., cancelling) opposite polarity magnetic fields where magnetic reconnection is thought to be possible. Conclusions. More than 10% of the IRIS burst profiles identified during the entirety of 2013 and 2014 are contained in just seven small regions in the time-distance domain where long-lived (lifetimes > 10 min) or repetitive UV bursts occurred along the axis of the IRIS slit.

Ultraviolet spectropolarimetry: investigating stellar magnetic field diagnostics

Magnetic fields are important for stellar photospheres and magnetospheres, influencing photospheric physics and sculpting stellar winds. Observations of stellar magnetic fields are typically made in the visible, although infrared observations are becoming common. Here we consider the possibility of directly detecting magnetic fields at ultraviolet (UV) wavelengths using high resolution spectropolarimetry, specifically considering the capabilities of the proposed Polstar mission. UV observations are particularly advantageous for studying wind resonance lines not available in the visible, but they can also provide many photospheric lines in hot stars. Detecting photospheric magnetic fields using the Zeeman effect and Least Squares Deconvolution is potentially more effective in the UV due to the much higher density of strong lines. We investigate detecting magnetic fields in the magnetosphere of a star using the Zeeman effect in wind lines, and find that this could be detectable at high S/N in an O or B star with a strong magnetic field. We consider detecting magnetic fields using the Hanle effect in linear polarization, which is complementary to the Zeeman effect, and could be more sensitive in photospheric lines of rapid rotators. The Hanle effect can also be used to infer circumstellar magnetism in winds. Detecting the Hanle effect requires UV observations, and a multi-line approach is key for inferring magnetic field properties. This demonstrates that high resolution spectropolarimetry in the UV, and the proposed Polstar mission, has the potential to greatly expand our ability to detect and characterize magnetic fields in and around hot stars.

Cyclic Variations of the Polarity of the Photospheric Magnetic Field

Cyclic Variations of the Polarity of the Photospheric Magnetic Field

Reconstructing solar magnetic fields from historical observations

Context. We apply our recently developed method to reconstruct synoptic maps of the photospheric magnetic field from observations of chromospheric plages and the magnetic polarity of sunspots. Here, we apply the method to an extended time interval from 1915 to 1985. Aims. Systematic magnetographic observations of the solar photospheric magnetic field were initiated as recently as the 1970s and the lack of earlier observations limits our ability to study and understand the long-term evolution of the Solar global field. This study is aimed at creating synoptic maps of magnetic fields for the pre-magnetograph era and using these maps as input for modern simulation models to investigate the long-term (centennial) evolution of the Sun’s global magnetic fields. Methods. We reconstructed active Solar regions by identifying chromospheric plages from Ca II K line synoptic maps and assigning magnetic polarities based on the observed polarity of sunspots. We used a surface flux transport (SFT) model to simulate the evolution of the photospheric magnetic field from the reconstructed active regions. We used the potential field source surface (PFSS) model to determine the amount of open magnetic flux from the reconstruction and from magnetographic observations. We also reconstructed the coronal field during two eclipses and compared the result with eclipse drawings. Results. We successfully reconstructed the photospheric magnetic field from 1915 to 1985. The number and total magnetic flux of the reconstructed active regions shows a realistic cyclic behavior that mostly follows the evolution of the sunspot number, even on relatively short timescales. The polar field strengths of cycles 19 and 20 do not reflect the evolution of the sunspot number very accurately, which may be related to problems related to the calcium data during cycle 19 and the long data gap during cycle 20. The polarity of polar fields and the amount of open field both at high and low latitudes all demonstrate the expected cyclic behavior. The agreement of the modeled coronal structure with eclipse drawings in 1922 and 1923 is fair.

Deep-learning Reconstruction of Sunspot Vector Magnetic Fields for Forecasting Solar Storms

Solar magnetic activity produces extreme solar flares and coronal mass ejections, which pose grave threats to electronic infrastructure and can significantly disrupt economic activity. It is therefore important to appreciate the triggers of explosive solar activity and develop reliable space weather forecasting. Photospheric vector magnetic field data capture sunspot magnetic field complexity and can therefore improve the quality of space weather prediction. However, state-of-the-art vector field observations are consistently only available from Solar Dynamics Observatory/Helioseismic and Magnetic Imager (HMI) since 2010, with most other current and past missions and observational facilities, such as Global Oscillations Network Group (GONG), only recording line-of-sight (LOS) fields. Here, using an inception-based convolutional neural network (CNN), we reconstruct HMI sunspot vector field features from LOS magnetograms of HMI and GONG with high fidelity (∼90% correlation) and sustained flare forecasting accuracy. We rebuild vector field features during the 2003 Halloween storms, for which only LOS field observations are available, and the CNN-estimated electric current helicity accurately captures the observed rotation of the associated sunspot prior to the extreme flares, showing a striking increase. Our study thus paves the way for reconstructing three solar cycles worth of vector field data from past LOS measurements, which are of great utility in improving space weather forecasting models and gaining new insights about solar activity.

The characteristics of flare- and CME-productive solar active regions

Solar flares and coronal mass ejections (CMEs) cause immediate and adverse effects on the interplanetary space and geospace. In an era of space-based technical civilization, the deeper understanding of the mechanisms that produce them and the construction of efficient prediction schemes are of paramount importance. The source regions of flares and CMEs exhibit some common morphological characteristics, such as δ-spots, filaments and sigmoids, which are associated with strongly sheared magnetic polarity inversion lines, indicative of the complex magnetic configurations that store huge amounts of free magnetic energy and helicity. The challenge is to transform this empirical knowledge into parameters/predictors that can help us distinguish efficiently between quiet, flare-, and CME-productive (eruptive) active regions. This paper reviews these efforts to parameterize the characteristics of eruptive active regions as well as the importance of transforming new knowledge into more efficient predictors and including new types of data. Magnetic properties of active regions were first introduced when systematic ground-based observations of the photospheric magnetic field became possible and the relevant research was boosted by the provision of near real time, uninterrupted, high-quality observations from space, which allowed the study of large, statistically significant samples. Nonetheless, flare and CME prediction still faces a number of challenges. The magnetic field information is still constrained at the photospheric level and accessed only from one vantage point of observation, thus there is always need for better predictors; the dynamic behavior of active regions is still not fully incorporated into predictions; the inherent stochasticity of flares and CMEs renders their prediction probabilistic, thus benchmark sets are necessary to optimize and validate predictions. To meet these challenges, researchers have put forward new magnetic properties, which describe different aspects of magnetic energy storage mechanisms in active regions and offer the opportunity of parametric studies for over an entire solar cycle. This inventory of features/predictors is now expanded to include information from flow fields, transition region and coronal spectroscopy, data-driven modeling of the coronal magnetic field, as well as parameterizations of dynamic effects from time series. Further work towards these directions may help alleviate the current limitations in observing the magnetic field of higher atmospheric layers. In this task, fundamental and operational research converge, with promising results which could stimulate the development of new missions and lay the ground for future exploratory studies, also profiting from and utilizing the long anticipated observations of the new generation of instruments.

Comparison between probability density functions of vertical electric current in solar active regions based on HMI/SDO and SOT/Hinode data

Studying electric currents in solar active regions (AR) is an essential step in understanding solar activity in general and solar flares in particular. In this paper, we compare probability density functions of vertical electric current PDF(|jz|) in several active regions, using HMI/SDO and SOT/Hinode photospheric magnetic field data. We have established that at a high value (above the noise level of |jz| >9•10³ statampere/cm²) of current structures of ARs these functions are nearly identical. The main difference in PDFs for low (noise) jz≤9•10³ statampere/cm² is due to differences in sensitivity of these two instruments. We have also found that the criterion of pixel selection from magnetic field strength is inapplicable, and the similarity between PDFs is determined by high jz. For all PDF(|jz|) under study we have calculated the power law exponent of the PDF tail for the two instruments, which coincide within their errors for the current structures with current values above noise level. Thus there is no significant difference as to which instrument is used for analyzing probability density functions in high current parts of ARs where flares are localized.

Сравнение функций плотности вероятности вертикального электрического тока в активных областях Солнца по данным инструментов HMI/SDO и SOT/Hinode

Studying electric currents in solar active regions (AR) is an essential step in understanding solar activity in general and solar flares in particular. In this paper, we compare probability density functions of vertical electric current PDF(|jz|) in several active regions, using HMI/SDO and SOT/Hinode photospheric magnetic field data. We have established that at a high value (above the noise level of |jz| >9•10³ statampere/cm²) of current structures of ARs these functions are nearly identical. The main difference in PDFs for low (noise) jz≤9•10³ statampere/cm² is due to differences in sensitivity of these two instruments. We have also found that the criterion of pixel selection from magnetic field strength is inapplicable, and the similarity between PDFs is determined by high jz. For all PDF(|jz|) under study we have calculated the power law exponent of the PDF tail for the two instruments, which coincide within their errors for the current structures with current values above noise level. Thus there is no significant difference as to which instrument is used for analyzing probability density functions in high current parts of ARs where flares are localized.

What drives decayless kink oscillations in active-region coronal loops on the Sun?

Here, we present a study of the phenomena of decayless kink oscillations in a system of active-region (AR) coronal loops. Using high-resolution observations from two different instruments, namely the Extreme Ultraviolet Imager (EUI) on board Solar Orbiter and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory, we follow these AR loops for an hour each on three consecutive days. Our results show significantly more resolved decayless waves in the higher resolution EUI data compared with the AIA data. Furthermore, the same system of loops exhibits many of these decayless oscillations on Day 2, while we detect very few oscillations on Day 3 , and find none at all on Day 1. Analysis of photospheric magnetic field data reveals that, most of the time, these loops were rooted in sunspots, where supergranular flows are generally absent. This suggests that supergranular flows, which are often invoked as drivers of decayless waves, are not necessarily driving such oscillations in our observations. Similarly, our findings also cast doubt on other possible drivers of these waves, such as a transient driver or mode conversion of longitudinal waves near the loop footpoints. In conclusion, our analysis suggests that none of the commonly suspected sources proposed to drive decayless oscillations in active-region loops seem to be operating in this event, and therefore the search for that elusive wave driver needs to continue.

On the Origin of the Photospheric Magnetic Field

This article presents results that challenge the paradigms that (1) the convection zone is the source of the radial magnetic field in the photosphere and (2) that coronal currents are neutralized from the perspective of the photosphere. We demonstrate, using a new analysis tool applied to simulations and observations, that bare or partially dressed current channels are supported by the solar corona and that fingerprints of these coronal current systems can be detected in the photosphere. These coronal current channels can be a significant source of the radial component of the magnetic field in the photosphere. The roots of these coronal current channels in the photosphere are the source of the magnetic field component parallel to the polarity inversion line in active region NOAA 12673. These analyses and observations transform our theoretical understanding of coronal evolution and argue for a reexamination of the present paradigm in which the convection zone is the sole source of the photospheric magnetic field.

Improving Multiday Solar Wind Speed Forecasts

AbstractWe analyze the residual errors for the Wang‐Sheeley‐Arge (WSA) solar wind speed forecasts as a function of the photospheric magnetic field expansion factor (fp) and the minimum separation angle (d) in the photosphere between the footpoints of open field lines and the nearest coronal hole boundary. We find the map of residual speed errors are systematic when examined as a function of fp and d. We use these residual error maps to apply corrections to the model speeds. We test this correction approach using 3‐day lead time speed forecasts for an entire year of observations and model results. Our methods can readily be applied to develop corrections for the remaining WSA forecast lead times which range from 1 to 7 days in 1‐day increments. Since the solar wind density, temperature, and the interplanetary magnetic field strength all correlate well with the solar wind speed, the improved accuracy of solar wind speed forecasts enables the production of multiday forecasts of the solar wind density, temperature, pressure, and interplanetary field strength, and geophysical indices. These additional parameters would expand the usefulness of Air Force Data Assimilative Photospheric Flux Transport‐WSA forecasts for space weather clients.

Chinese Sunspot Drawings and Their Digitization—(VII) Sunspot Penumbra to Umbra Area Ratio Using the Hand-Drawing Records from Yunnan Observatories

The ratio of penumbral to umbra area of sunspots plays a crucial role in the solar physics fields, especially for understanding the origin and evolution of the solar activity cycle. By analyzing the recently digitized sunspot drawings observed from Yunnan Observatories (1957–2021), we investigate the long-term variation of the penumbral to umbra area ratio of sunspots. An automatic extraction method, based on the maximum between-class variance and the morphological discrimination, is used to accurately extract penumbra and umbra and to calculate the ratio over six solar cycles (cycle 19–24). The expected value of the ratio of penumbra to umbra area is found to be 6.63 ± 0.98, and it does not exhibit any systematic variation with sunspot latitudes and phases. The average ratio fluctuates from 5 to 7.5 per year and the overall trend has decreased after 1999 compared to the previous one. The ratio of sunspot penumbra to umbra area satisfies the log-normal distribution, implying that its variation is related to the evolution of the photospheric magnetic field. Our results are consistent with previous works.

Reconstructing solar magnetic fields from historical observations

Context. The bright regions in the solar chromosphere and temperature minimum have a good spatial correspondence with regions of intense photospheric magnetic field. Bright regions are visible in different emission lines and parts of the continuum. Their observation started more than a hundred years ago with the invention of the spectroheliograph. While the historical spectroheliograms are essential for studying the long-term variability of the Sun, the modern satellite-borne observations can help us reveal the nature of chromospheric brightenings in previously unattainable detail. Aims. Our aim is to improve the understanding of the relation between magnetic fields and radiative structures byf studying modern seeing-free observations of far-ultraviolet (FUV) radiation around 1600 Å and photospheric magnetic fields. Methods. We used Helioseismic and Magnetic Imager (HMI) observations of photospheric magnetic fields and Atmospheric Imaging Assembly (AIA) observations of FUV contrast around 1600 Å. We developed a robust method to find contrast thresholds defining bright and dark AIA 1600 Å pixels, and we combine them to bright and dark clusters. We investigate the relation of magnetic fields and AIA 1600 Å radiation in bright and dark clusters. Results. We find that the percentage of bright pixels (ranging from 2% to 10%) almost entirely explains the observed variability of 1600 Å emission. We developed a multilinear regression model based on the percentages of bright and dark pixels, which can reliably predict the magnitude of the disk-averaged unsigned magnetic field. We find that bright and dark clusters closely correspond respectively to the populations of moderate (B > 55 G) and strong (B > 1365 G) magnetic field HMI clusters. The largest bright clusters have a constant mean unsigned magnetic field, as found previously for Ca II K plages. However, the magnetic field strength of bright clusters is 254.7 ± 0.1 G, which is roughly 100 G larger than found earlier for Ca II K plages.

Photospheric magnetic field variation during solar flares and their implication for the generation of sunquakes

AbstractSolar flares are an explosive manifestation of the complex magnetic structuring of active regions in the solar atmosphere. The photospheric magnetic field is found to change rapidly, abruptly, and significantly during flaring events. Previous studies are mainly based on line-of-sight or low-cadence data. In this work, we focus on the temporal and spatial evolution of the permanent changes in the magnetic field of solar flares from high-cadence vector data (135 seconds) of the imaging system (dopplergrams and magnetograms) of the SDO/HMI instrument. The highly energetic events under analysis occurred during the solar cycle 24, covering low and high energy ranges, according to GOES classification. This investigation also stands as a crucial input for the characterization and understanding of sunquakes.