Space-weather HMI Active Region Patches Research Articles

Non-neutralized Electric Currents in Solar Active Regions and Flare Productivity

We explore the association of non-neutralized currents with solar flare occurrence in a sizable sample of observations, aiming to show the potential of such currents in solar flare prediction. We use the regularly produced high quality vector magnetograms by the Helioseismic Magnetic Imager and more specifically the Space weather HMI Active Region Patches (SHARP). Through a newly established method, that incorporates detailed error analysis, we calculate the non-neutralized currents contained in active regions (AR). Two predictors are produced, namely the total and the maximum unsigned non-neutralized current. Both are tested in AR time-series and a representative sample of point-in-time observations during the interval 2012-2016. The average values of non-neutralized currents in flaring active regions are by more than an order of magnitude higher than in non-flaring regions and correlate very well with the corresponding flare index. The temporal evolution of these parameters appears to be connected to physical processes, such as flux emergence and/or magnetic polarity inversion line formation that are associated with increased solar flare activity. Using Bayesian inference of flaring probabilities, it is shown that the total unsigned non-neutralized current outperforms significantly the total unsigned magnetic flux and other well established current-related predictors. Thus, it shows good prospects for inclusion in an operational flare forecasting service. We plan to use the new predictor in the framework of the FLARECAST project along with other highly performing predictors.

Detailed analysis of dynamic evolution of three Active Regions at the photospheric level before flare and CME occurrence

We present a combined analysis of the applications of the weighted horizontal magnetic gradient (denoted as WGM in Korsós et al. (2015)) method and the magnetic helicity tool (Berger and Field, 1984) employed for three active regions (ARs), namely NOAA AR 11261, AR 11283 and AR 11429. We analysed the time series of photospheric data from the Solar Dynamics Observatory taken between August 2011 and March 2012. During this period the three ARs produced a series of flares (eight M- and six X-class) and coronal mass ejections (CMEs). AR 11261 had four M-class flares and one of them was accompanied by a fast CME. AR 11283 had similar activities with two M- and two X-class flares, but only with a slow CME. Finally, AR 11429 was the most powerful of the three ARs as it hosted five compact and large solar flare and CME eruptions. For applying the WGM method we employed the Debrecen sunspot data catalogue, and, for estimating the magnetic helicity at photospheric level we used the Space-weather HMI Active Region Patches (SHARP’s) vector magnetograms from SDO/HMI (Solar Dynamics Observatory/Helioseismic and Magnetic Imager). We followed the evolution of the components of the WGM and the magnetic helicity before the flare and CME occurrences. We found a unique and mutually shared behaviour, called the U-shaped pattern, of the weighted distance component of WGM and of the shearing component of the helicity flux before the flare and CME eruptions. This common pattern is associated with the decreasing-receding phases yet reported only known to be a necessary feature prior to solar flare eruption(s) but found now at the same time in the evolution of the shearing helicity flux. This result leads to the conclusions that (i) the shearing motion of photospheric magnetic field may be a key driver for solar eruption in addition to the flux emerging process, and that (ii) the found decreasing-approaching pattern in the evolution of shearing helicity flux may be another precursor indicator for improving the forecasting of solar eruptions.

Predicting Solar Flares Using SDO/HMI Vector Magnetic Data Products and the Random Forest Algorithm

Abstract Adverse space-weather effects can often be traced to solar flares, the prediction of which has drawn significant research interests. The Helioseismic and Magnetic Imager (HMI) produces full-disk vector magnetograms with continuous high cadence, while flare prediction efforts utilizing this unprecedented data source are still limited. Here we report results of flare prediction using physical parameters provided by the Space-weather HMI Active Region Patches (SHARP) and related data products. We survey X-ray flares that occurred from 2010 May to 2016 December and categorize their source regions into four classes (B, C, M, and X) according to the maximum GOES magnitude of flares they generated. We then retrieve SHARP-related parameters for each selected region at the beginning of its flare date to build a database. Finally, we train a machine-learning algorithm, called random forest (RF), to predict the occurrence of a certain class of flares in a given active region within 24 hr, evaluate the classifier performance using the 10-fold cross-validation scheme, and characterize the results using standard performance metrics. Compared to previous works, our experiments indicate that using the HMI parameters and RF is a valid method for flare forecasting with fairly reasonable prediction performance. To our knowledge, this is the first time that RF has been used to make multiclass predictions of solar flares. We also find that the total unsigned quantities of vertical current, current helicity, and flux near the polarity inversion line are among the most important parameters for classifying flaring regions into different classes.

Comparison of Predictive Efficiency of Topological Descriptors and SHARP in Solar Flares Forecasting

AbstractIn the current paper, we investigate topological invariants, calculated by HMI LOS magnetograms as complexity descriptors of solar magnetic fields. We compared them with the physical parameters provided by the Space-weather HMI Active Region Patches (SHARP). We have repeated forecasting experiment of Stanford Solar Observatories Group with the same positive and negative active region patches database, but replace SHARP parameters with topological invariants of corresponding LOS magnetograms. The classification results turned out practically identical to those obtained by the Stanford Solar Observatory group. This means that using LOS magnetograms retains enough complexity for magnetic field description.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: SHARPs – Space-Weather HMI Active Region Patches

A new data product from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) called Space-weather HMI Active Region Patches (SHARPs) is now available. SDO/HMI is the first space-based instrument to map the full-disk photospheric vector magnetic field with high cadence and continuity. The SHARP data series provide maps in patches that encompass automatically tracked magnetic concentrations for their entire lifetime; map quantities include the photospheric vector magnetic field and its uncertainty, along with Doppler velocity, continuum intensity, and line-of-sight magnetic field. Furthermore, keywords in the SHARP data series provide several parameters that concisely characterize the magnetic-field distribution and its deviation from a potential-field configuration. These indices may be useful for active-region event forecasting and for identifying regions of interest. The indices are calculated per patch and are available on a twelve-minute cadence. Quick-look data are available within approximately three hours of observation; definitive science products are produced approximately five weeks later. SHARP data are available at http://jsoc.stanford.edu and maps are available in either of two different coordinate systems. This article describes the SHARP data products and presents examples of SHARP data and parameters.