Photospheric Magnetic Free Energy Density of Solar Active Regions

We present the photospheric energy density of magnetic fields in two solar active regions (one of them recurrent) inferred from observational vector magnetograms, and compare it with other available differently defined energy parameters of magnetic fields in the photosphere. We analyze the magnetic fields in Active Regions NOAA 6580-6619-6659 and 11158. The quantity \(\frac{1}{4\pi}{\mathbf{B}}_{n}\cdot{\mathbf{B}}_{p}\) is an important energy parameter that reflects the contribution of magnetic shear to the difference between the potential (\(\mathbf{B}_{p}\)) and the non-potential magnetic field (\(\mathbf{B}_{n}\)), and also the contribution to the free magnetic energy near the magnetic neutral lines in the active regions. It is found that the photospheric mean magnetic energy density shows clear changes before the powerful solar flares in Active Region NOAA 11158, which is consistent with the change in magnetic fields in the flaring lower atmosphere.     

Size-Flux Relation in Solar Active Regions

We present a study of the relationship between integral area and corresponding total magnetic flux for solar active regions. It is shown that some of these relationships are satisfied to simple power laws. Fractal examination showed that some of these power laws can not be justified inside the simple models of stationary magnetic flux tube aggregation. All magnetic fluxes and corresponding areas were calculated using the data measured with the Solar Magnetic Field Telescope of the Huairou Solar Observing Station in Beijing.     

3个太阳活动区中的水平和垂直电流与耀斑的关系

对3个超级活动区（大的δ型黑子群）NOAA 5395、6659、6891中的电流分布作了系统计算；利用已发表的计算方法，首次用于实际活动区的水平电流分布；给出了电流与耀斑核的关系。将这种关系分为两类：密切相关和准相关，并同时给出了统计结果。结果显示：1）对于垂直电流和水平电流来说，密切相关率分别是29％和10％，准相关率分别是50％和30％；2）有些耀斑核与两种电流都相关，而大多数只与其中一种相关；3）与两种电流都不相关的耀斑核只占6％左右；4）两种电流起互补作用，因而对于预报耀斑具有一定的作用。通过分析还发现，磁场剪切强的地方相应于强的垂直电流，而磁中性线附近纵向磁场梯度大的地方相应于强的水平电流。     

Photospheric Plasma Flows Around a Solar Spot

We study photospheric plasma flows in an active region NOAA 8375, by using uninterrupted high-resolution SOHO/MDI observations (137 intensity images, 44 hours of observations). The active region consists of a stable large spot and many small spots and pores. Analyzing horizontal flow maps, obtained with local correlation tracking technique, we found a system of stable persistent plasma flows existing in the active region. The flows start on either side of the sunspot and extend over 100′′ to the east. Our measurements show that the speed of small sunspots and pores, averaged over 44 hours, was about 100 m s⁻¹, which corresponds to root-mean-square longitudinal drifts of sunspots of 0.67°–0.76° day⁻¹. We conclude that these large-scale flows are due to faster proper motion of the large sunspot relative to the ambient photospheric plasma. We suggest that the flows may be a good carrier to transport magnetic flux from eroding sunspots into the outer part of an active region.     

Correlation Between Solar Flare Productivity and Photospheric Magnetic Field Properties

From a large number of SOHO/MDI longitudinal magnetograms, three physical measures including the maximum horizontal gradient, the length of the neutral line, and the number of singular points are computed. These measures are used to describe photospheric magnetic field properties including nonpotentiality and complexity, which is believed to be closely related to solar flares. Our statistical results demonstrate that solar flare productivity increases with nonpotentiality and complexity. Furthermore, the relationship between the flare productivity and these measures can be well fitted with a sigmoid function. These results can be beneficial to future operational flare forecast models.     

Correlation between Solar Flare Productivity and Photospheric Magnetic Field Properties II. Magnetic Gradient and Magnetic Shear

With 1353 vector magnetograms observed at Huairou Solar Observing Station (HSOS), a statistical analysis is made on the relationship among solar flares, magnetic gradient, and magnetic shear. The results suggest that flare productivity has positive correlations with the gradient and the shear, which can be well fitted by the Boltzmann sigmoidal function. In the vicinity of neutral lines, high gradient and strong shear are roughly coincident in time but barely in position. In addition, flare productivity is more sensitive to the length of neutral lines with strong gradient and shear (L _gs) than independently with strong gradient (L _g) or strong shear (L _s), which means that L _gs can be a better parameter for solar flare forecasting models. Finally, an algorithm to evaluate projection effects on the statistical results is proposed.     

Statistical Models for the Solar Flare Interval Distribution in Individual Active Regions

This article discusses statistical models for the solar flare interval distribution in individual active regions. We analyzed solar flare data in 55 active regions that are listed in the Geosynchronous Operational Environmental Satellite (GOES) soft X-ray flare catalog for the years from 1981 to 2005. We discuss some problems with a conventional procedure to derive probability density functions from any data set and propose a new procedure, which uses the maximum likelihood method and Akaike Information Criterion (AIC) to objectively compare some competing probability density functions. Previous studies of the solar flare interval distribution in individual active regions only dealt with constant or time-dependent Poisson process models, and no other models were discussed. We examine three models – exponential, lognormal, and inverse Gaussian – as competing models for probability density functions in this study. We found that lognormal and inverse Gaussian models are more likely models than the exponential model for the solar flare interval distribution in individual active regions. The possible solar flare mechanisms for the distribution models are briefly mentioned. We also briefly investigated the time dependence of probability density functions of the solar flare interval distribution and found that some active regions show time dependence for lognormal and inverse Gaussian distribution functions. The results suggest that solar flares do not occur randomly in time; rather, solar flare intervals appear to be regulated by solar flare mechanisms. Determining a solar flare interval distribution is an essential step in probabilistic solar flare forecasting methods in space weather research. We briefly mention a probabilistic solar flare forecasting method as an application of a solar flare interval distribution analysis. The application of our distribution analysis to a probabilistic solar flare forecasting method is one of the main objectives of this study.     

Statistical Assessment of Photospheric Magnetic Features in Imminent Solar Flare Predictions

In this study we use the ordinal logistic regression method to establish a prediction model, which estimates the probability for each solar active region to produce X-, M-, or C-class flares during the next 1-day time period. The three predictive parameters are (1) the total unsigned magnetic flux T _flux, which is a measure of an active region’s size, (2) the length of the strong-gradient neutral line L _gnl, which describes the global nonpotentiality of an active region, and (3) the total magnetic dissipation E _diss, which is another proxy of an active region’s nonpotentiality. These parameters are all derived from SOHO MDI magnetograms. The ordinal response variable is the different level of solar flare magnitude. By analyzing 174 active regions, L _gnl is proven to be the most powerful predictor, if only one predictor is chosen. Compared with the current prediction methods used by the Solar Monitor at the Solar Data Analysis Center (SDAC) and NOAA’s Space Weather Prediction Center (SWPC), the ordinal logistic model using L _gnl, T _flux, and E _diss as predictors demonstrated its automatic functionality, simplicity, and fairly high prediction accuracy. To our knowledge, this is the first time the ordinal logistic regression model has been used in solar physics to predict solar flares.     

Photospheric Magnetic Evolution in the WHI Active Regions

Sequences of line-of-sight (LOS) magnetograms recorded by the Michelson Doppler Imager are used to quantitatively characterize photospheric magnetic structure and evolution in three active regions that rotated across the Sun??s disk during the Whole Heliosphere Interval (WHI), in an attempt to relate the photospheric magnetic properties of these active regions to flares and coronal mass ejections (CMEs). Several approaches are used in our analysis, on scales ranging from whole active regions, to magnetic features, to supergranular scales, and, finally, to individual pixels. We calculated several parameterizations of magnetic structure and evolution that have previously been associated with flare and CME activity, including total unsigned magnetic flux, magnetic flux near polarity-inversion lines, amount of canceled flux, the ??proxy Poynting flux,?? and helicity flux. To catalog flare events, we used flare lists derived from both GOES and RHESSI observations. By most such measures, AR 10988 should have been the most flare- and CME-productive active region, and AR 10989 the least. Observations, however, were not consistent with this expectation: ARs 10988 and 10989 produced similar numbers of flares, and AR 10989 also produced a few CMEs. These results highlight present limitations of statistics-based flare and CME forecasting tools that rely upon line-of-sight photospheric magnetic data alone.     

Large-Scale Electric Fields in Solar Flare Regions

A method of separating electric field in the flare region in the potential and vortex (induced) parts is discussed. According to the proposed model, the motion of flare ribbons from the central line of the flare region is caused by the vortex component of the coronal electric field, while the motion of bright spots within the flare region towards the central line is driven by the potential component of that field. The intensity of both the components of the flare region electric field is estimated to equal approximately 1–3 V cm^–1, which provides the input of the electromagnetic energy into the active region at a rate of about 10¹⁰ erg cm^–2 s^–1.     

The Horizontal Component of Photospheric Plasma Flows During the Emergence of Active Regions on the Sun

The dynamics of horizontal plasma flows during the first hours of the emergence of active region magnetic flux in the solar photosphere have been analyzed using SOHO/MDI data. Four active regions emerging near the solar limb have been considered. It has been found that extended regions of Doppler velocities with different signs are formed in the first hours of the magnetic flux emergence in the horizontal velocity field. The flows observed are directly connected with the emerging magnetic flux; they form at the beginning of the emergence of active regions and are present for a few hours. The Doppler velocities of flows observed increase gradually and reach their peak values 4?–?12 hours after the start of the magnetic flux emergence. The peak values of the mean (inside the ±?500 m?s^?1 isolines) and maximum Doppler velocities are 800?–?970 m?s^?1 and 1410?–?1700 m?s^?1, respectively. The Doppler velocities observed substantially exceed the separation velocities of the photospheric magnetic flux outer boundaries. The asymmetry was detected between velocity structures of leading and following polarities. Doppler velocity structures located in a region of leading magnetic polarity are more powerful and exist longer than those in regions of following polarity. The Doppler velocity asymmetry between the velocity structures of opposite sign reaches its peak values soon after the emergence begins and then gradually drops within 7?–?12 hours. The peak values of asymmetry for the mean and maximal Doppler velocities reach 240?–?460 m?s^?1 and 710?–?940 m?s^?1, respectively. An interpretation of the observable flow of photospheric plasma is given.     

Solar Flare Occurrence Rate and Waiting Time Statistics

We use Renewal Theory for the estimation and interpretation of the flare rate from the Geostationary Operational Environmental Satellite (GOES) soft X-ray?flare catalogue. It is found that, in addition to the flare rate variability with the solar cycles, a much faster variation occurs. The fast variation on time scales of days and hours down to minute scale appears to be comparable with time intervals between two successive flares (waiting times). The detected fast non-stationarity of the flaring rate is discussed in the framework of the previously published stochastic models of the waiting time dynamics.     

On the Possible Connection between Photospheric 5-Min Oscillation and Solar Flare Microwave Emission

Dynamic spectra of low-frequency modulation of microwave emission from solar flares are obtained. Data of 15 bursts observed in 1989–2000 with Metsähovi radio telescope at 37 GHz have been used. During 13 bursts a 5-min modulation of the microwave emission intensity was detected with the frequency of ν _I = 3.2± 0.24 (1σ) mHz. Five bursts revealed a 5-min wave superimposed on a ～1 Hz, linear frequency modulated signal generated, presumably, by coronal magnetic loop, this wave frequency is ν_fm = 3.38± 0.37 (1σ) mHz. Both intensity and frequency modulations detected are in good agreement with the data on 5-min global oscillations of photosphere and with the data on the umbral velocity oscillations observed in the vicinity of sunspots. Possible role of p-mode photospheric oscillations in modulation of microwave burst emission is discussed.     

Mesogranulation and Turbulence in Photospheric Flows

Below the scale of supergranules we find that cellular flows are present in the solar photosphere at two distinct size scales, approximately 2 Mm and 4 Mm, with distinct characteristic times. Simultaneously present in the flow is a non-cellular component, with turbulent scaling properties and containing 30% of the flow energy. These results are obtained by means of wavelet spectral analysis and modeling of vertical photospheric motions in a 2-hour sequence of 120 SOHO/MDI, high-resolution, Doppler images near disk center. The wavelets permit detection of specific local flow patterns corresponding to convection cells.     

Estimating Flare-Related Photospheric Lorentz Force Vector Changes Within Active Regions

It is shown that expressions for the global Lorentz force associated with a flaring active region derived by Fisher et al. (Solar Phys. 277, 59, 2012) can be used to estimate the Lorentz-force changes for strong fields in large structures over photospheric subdomains within active regions. Gary’s (Solar Phys. 203, 71, 2001) model for the stratified solar atmosphere is used to demonstrate that in large-scale structures with typical horizontal magnetic length scale ??300 km and with strong magnetic fields (≥?1 kG at the τ=1 opacity layer at 5000 Å), the Lorentz force acting on the photosphere may be approximated by a surface integral based on photospheric boundary data alone. These conditions cover many of the sunspot fields and major neutral lines that have been studied using Fisher et al.’s (2012) expressions over the past few years. The method gives a reasonable estimate of flare-related Lorentz-force changes based on photospheric magnetogram observations provided that the Lorentz-force changes associated with the flare have a lasting effect on the observed fields, and they are not immediately erased by post-flare equilibration processes.     

Organized Subsurface Flows near Active Regions

Local helioseismic techniques, such as ring analysis and time-distance helioseismology, have already shown that large-scale flows near the surface converge towards major active regions. Ring analysis has further demonstrated that at greater depths some active regions exhibit strong outflows. A critique leveled at the ring-analysis results is that the Regularized Least Squares (RLS) inversion kernels on which they are based have negative sidelobes near the surface. Such sidelobes could result in a surface inflow being misidentified as a diverging outflow at depth. In this paper we show that the Optimally Located Averages (OLA) inversion technique, which produces kernels without significant sidelobes, generates flows markedly similar to the RLS results. Active regions are universally zones of convergence near the surface, while large complexes evince strong outflows deeper down.     

Flare Prediction Using Photospheric and Coronal Image Data

The precise physical process that triggers solar flares is not currently understood. Here we attempt to capture the signature of this mechanism in solar-image data of various wavelengths and use these signatures to predict flaring activity. We do this by developing an algorithm that i) automatically generates features in 5.5 TB of image data taken by the Solar Dynamics Observatory of the solar photosphere, chromosphere, transition region, and corona during the time period between May 2010 and May 2014, ii) combines these features with other features based on flaring history and a physical understanding of putative flaring processes, and iii) classifies these features to predict whether a solar active region will flare within a time period of \(T\) hours, where \(T = 2 \mbox{ and }24\). Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We find that when optimizing for the True Skill Score (TSS), photospheric vector-magnetic-field data combined with flaring history yields the best performance, and when optimizing for the area under the precision–recall curve, all of the data are helpful. Our model performance yields a TSS of \(0.84 \pm0.03\) and \(0.81 \pm0.03\) in the \(T = 2\)- and 24-hour cases, respectively, and a value of \(0.13 \pm0.07\) and \(0.43 \pm0.08\) for the area under the precision–recall curve in the \(T=2\)- and 24-hour cases, respectively. These relatively high scores are competitive with previous attempts at solar prediction, but our different methodology and extreme care in task design and experimental setup provide an independent confirmation of these results. Given the similar values of algorithm performance across various types of models reported in the literature, we conclude that we can expect a certain baseline predictive capacity using these data. We believe that this is the first attempt to predict solar flares using photospheric vector-magnetic field data as well as multiple wavelengths of image data from the chromosphere, transition region, and corona, and it points the way towards greater data integration across diverse sources in future work.