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
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
- NSF-PAR ID:
- 10482772
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 960
- Issue:
- 1
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 80
- Size(s):
- Article No. 80
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract 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. -
more » « less
Abstract The optical and near-ultraviolet (NUV) continuum radiation in M-dwarf flares is thought to be the impulsive response of the lower stellar atmosphere to magnetic energy release and electron acceleration at coronal altitudes. This radiation is sometimes interpreted as evidence of a thermal photospheric spectrum with
T ≈ 104K. However, calculations show that standard solar flare coronal electron beams lose their energy in a thick target of gas in the upper and middle chromosphere (log10column mass/[g cm−2] ≲ −3). At larger beam injection fluxes, electric fields and instabilities are expected to further inhibit propagation to low altitudes. We show that recent numerical solutions of the time-dependent equations governing the power-law electrons and background coronal plasma (Langmuir and ion-acoustic) waves from Kontar et al. produce order-of-magnitude larger heating rates than those that occur in the deep chromosphere through standard solar flare electron beam power-law distributions. We demonstrate that the redistribution of beam energy aboveE ≳ 100 keV in this theory results in a local heating maximum that is similar to a radiative-hydrodynamic model with a large, low-energy cutoff and a hard power-law index. We use this semiempirical forward-modeling approach to produce opaque NUV and optical continua at gas temperaturesT ≳ 12,000 K over the deep chromosphere with log10column mass/[g cm−2] of −1.2 to −2.3. These models explain the color temperatures and Balmer jump strengths in high-cadence M-dwarf flare observations, and they clarify the relation among atmospheric, radiation, and optical color temperatures in stellar flares. -
more » « less
Abstract In this paper we present several methods to identify precursors that show great promise for early predictions of solar flare events. A data preprocessing pipeline is built to extract useful data from multiple sources, Geostationary Operational Environmental Satellites and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), to prepare inputs for machine learning algorithms. Two classification models are presented: classification of flares from quiet times for active regions and classification of strong versus weak flare events. We adopt deep learning algorithms to capture both spatial and temporal information from HMI magnetogram data. Effective feature extraction and feature selection with raw magnetogram data using deep learning and statistical algorithms enable us to train classification models to achieve almost as good performance as using active region parameters provided in HMI/Space‐Weather HMI‐Active Region Patch (SHARP) data files. Case studies show a significant increase in the prediction score around 20 hr before strong solar flare events.
-
more » « less
Supervised Machine Learning (ML) models for solar flare prediction rely on accurate labels for a given input data set, commonly obtained from the GOES/XRS X-ray flare catalog. With increasing interest in utilizing ultraviolet (UV) and extreme ultraviolet (EUV) image data as input to these models, we seek to understand if flaring activity can be defined and quantified using EUV data alone. This would allow us to move away from the GOES single pixel measurement definition of flares and use the same data we use for flare prediction for label creation. In this work, we present a Solar Dynamics Observatory (SDO) Atmospheric Imaging Assembly (AIA)-based flare catalog covering flare of GOES X-ray magnitudes C, M and X from 2010 to 2017. We use active region (AR) cutouts of full disk AIA images to match the corresponding SDO/Helioseismic and Magnetic Imager (HMI) SHARPS (Space weather HMI Active Region Patches) that have been extensively used in ML flare prediction studies, thus allowing for labeling of AR number as well as flare magnitude and timing. Flare start, peak, and end times are defined using a peak-finding algorithm on AIA time series data obtained by summing the intensity across the AIA cutouts. An extremely randomized trees (ERT) regression model is used to map SDO/AIA flare magnitudes to GOES X-ray magnitude, achieving a low-variance regression. We find an accurate overlap on 85% of M/X flares between our resulting AIA catalog and the GOES flare catalog. However, we also discover a number of large flares unrecorded or mislabeled in the GOES catalog.
-
Magnetic polarity inversion lines (PILs) in solar active regions are key to triggering flares and eruptions. Recently, engineered PIL features have been used for predicting solar eruptions. Derived from the original PIL dataset, using line-of-sight (LoS) magnetograms provided by the Solar Dynamics Observatory's (SDO) Helioseismic and Magnetic Imager (HMI) Active Region Patches (HARPs), we provide a publicly available comprehensive dataset in a supervised format, where each instance includes a raster of Polarity Inversion Lines (PILs), one of the polarity convex hull, and a multivariate time-series of properties related to PILs. Using SDO-GOES integrated flares historical data covering May 2010 to January 2019, we have assigned each of the instances their corresponding class of flare, FQ, C, M or X. By integrating these diverse data modalities, our approach aims to improve the accuracy of solar flare predictions. Initial findings suggest that the multimodal approach can uncover new patterns and relationships, potentially leading to breakthroughs in predictive accuracy and more effective mitigation strategies against the impacts of solar activities.more » « less
