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Register a new userMeasuring the magnetic origins of solar flares, CMEs and Space Weather
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We take a broad look at the problem of identifying the magnetic solar causes of space weather. With the lackluster performance of extrapolations based upon magnetic field measurements in the photosphere, we identify a region in the near UV part of the spectrum as optimal for studying the development of magnetic free energy over active regions. Using data from SORCE, Hubble Space Telescope, and SKYLAB, along with 1D computations of the near-UV (NUV) spectrum and numerical experiments based on the MURaM radiation-MHD and HanleRT radiative transfer codes, we address multiple challenges. These challenges are best met through a combination of near UV lines of bright ion{Mg}{2}, and lines of ion{Fe}{2} and ion{Fe}{1} (mostly within the $4s-4p$ transition array) which form in the chromosphere up to $2times10^4$ K. Both Hanle and Zeeman effects can in principle be used to derive vector magnetic fields. However, for any given spectral line the $tau=1$ surfaces are generally geometrically corrugated owing to fine structure such as fibrils and spicules. By using multiple spectral lines spanning different optical depths, magnetic fields across nearly-horizontal surfaces can be inferred in regions of low plasma $beta$, from which free energies, magnetic topology and other quantities can be derived. Based upon the recently-reported successful suborbital space measurements of magnetic fields with the CLASP2 instrument, we argue that a modest space-borne telescope will be able to make significant advances in the attempts to predict solar eruptions. Difficulties associated with blended lines are shown to be minor in an Appendix.
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The Suns outer atmosphere is heated to temperatures of millions of degrees, and solar plasma flows out into interplanetary space at supersonic speeds. This paper reviews our current understanding of these interrelated problems: coronal heating and the acceleration of the ambient solar wind. We also discuss where the community stands in its ability to forecast how variations in the solar wind (i.e., fast and slow wind streams) impact the Earth. Although the last few decades have seen significant progress in observations and modeling, we still do not have a complete understanding of the relevant physical processes, nor do we have a quantitatively precise census of which coronal structures contribute to specific types of solar wind. Fast streams are known to be connected to the central regions of large coronal holes. Slow streams, however, appear to come from a wide range of sources, including streamers, pseudostreamers, coronal loops, active regions, and coronal hole boundaries. Complicating our understanding even more is the fact that processes such as turbulence, stream-stream interactions, and Coulomb collisions can make it difficult to unambiguously map a parcel measured at 1 AU back down to its coronal source. We also review recent progress -- in theoretical modeling, observational data analysis, and forecasting techniques that sit at the interface between data and theory -- that gives us hope that the above problems are indeed solvable.
We study the influence of the large-scale interplanetary magnetic field configuration on the solar energetic particles (SEPs) as detected at different satellites near Earth and on the correlation of their peak intensities with the parent solar activity. We selected SEP events associated with X and M-class flares at western longitudes, in order to ensure good magnetic connection to Earth. These events were classified into two categories according to the global interplanetary magnetic field (IMF) configuration present during the SEP propagation to 1AU: standard solar wind or interplanetary coronal mass ejections (ICMEs). Our analysis shows that around 20% of all particle events are detected when the spacecraft is immersed in an ICME. The correlation of the peak particle intensity with the projected speed of the SEP-associated coronal mass ejection is similar in the two IMF categories of proton and electron events, $approx 0.6$. The SEP events within ICMEs show stronger correlation between the peak proton intensity and the soft X-ray flux of the associated solar flare, with correlation coefficient $r=,$0.67$pm$0.13, compared to the SEP events propagating in the standard solar wind, $r=,$0.36$pm$0.13. The difference is more pronounced for near-relativistic electrons. The main reason for the different correlation behavior seems to be the larger spread of the flare longitude in the SEP sample detected in the solar wind as compared to SEP events within ICMEs. We discuss to which extent observational bias, different physical processes (particle injection, transport, etc.), and the IMF configuration can influence the relationship between SEPs and coronal activity.
The solar group at the National Astronomical Observatory of Japan is conducting synoptic solar observations with the Solar Flare Telescope. While it is a part of a long-term solar monitoring, contributing to the study of solar dynamo governing solar activity cycles, it is also an attempt at contributing to space weather research. The observations include imaging with filters for H$alpha$, Ca K, G-band, and continuum, and spectropolarimetry at the wavelength bands including the He I 1083.0 nm / Si I 1082.7 nm and the Fe I 1564.8 nm lines. Data for the brightness, Doppler signal, and magnetic field information of the photosphere and the chromosphere are obtained. In addition to monitoring dynamic phenomena like flares and filament eruptions, we can track the evolution of the magnetic fields that drive them on the basis of these data. Furthermore, the magnetic field in solar filaments, which develops into a part of the interplanetary magnetic cloud after their eruption and occasionally hits the Earth, can be inferred in its pre-eruption configuration. Such observations beyond mere classical monitoring of the Sun will hereafter become crucially important from the viewpoint of the prediction of space weather phenomena. The current synoptic observations with the Solar Flare Telescope is considered to be a pioneering one for future synoptic observations of the Sun with advanced instruments.
Monitoring of the Sun and its activity is a task of growing importance in the frame of space weather research and awareness. Major space weather disturbances at Earth have their origin in energetic outbursts from the Sun: solar flares, coronal mass ejections and associated solar energetic particles. In this review we discuss the importance and complementarity of ground-based and space-based observations for space weather studies. The main focus is drawn on ground-based observations in the visible range of the spectrum, in particular in the diagnostically manifold H$alpha$ spectral line, which enables us to detect and study solar flares, filaments, filament eruptions, and Moreton waves. Existing H$alpha$ networks such as the GONG and the Global High-Resolution H$alpha$ Network are discussed. As an example of solar observations from space weather research to operations, we present the system of real-time detection of H$alpha$ flares and filaments established at Kanzelhohe Observatory (KSO; Austria) in the frame of the ESA Space Situational Awareness programme. During the evaluation period 7/2013 - 11/2015, KSO provided 3020 hours of real-time H$alpha$ observations at the SWE portal. In total, 824 H$alpha$ flares were detected and classified by the real-time detection system, including 174 events of H$alpha$ importance class 1 and larger. For the total sample of events, 95% of the automatically determined flare peak times lie within $pm$5 min of the values given in the official optical flares reports (by NOAA and KSO), and 76% of the start times. The heliographic positions determined are better than $pm$5$^circ$. The probability of detection of flares of importance 1 or larger is 95%, with a false alarm rate of 16%. These numbers confirm the high potential of automatic flare detection and alerting from ground-based observatories.
Among the eruptive activity phenomena observed on the Sun, the most technology threatening ones are flares with associated coronal mass ejections (CMEs) and solar energetic particles (SEPs). Flares with associated CMEs and SEPs are produced by magnetohydrodynamical processes in magnetically active regions (ARs) on the Sun. However, these ARs do not only produce flares with associated CMEs and SEPs, they also lead to flares and CMEs, which are not associated with any other event. In an attempt to distinguish flares with associated CMEs and SEPs from flares and CMEs, which are unassociated with any other event, we investigate the performances of two machine learning algorithms. To achieve this objective, we employ support vector machines (SVMs) and multilayer perceptrons (MLPs) using data from the Space Weather Database of Notification, Knowledge, Information (DONKI) of NASA Space Weather Center, {it the Geostationary Operational Environmental Satellite} ({it GOES}), and the Space-Weather Heliospheric and Magnetic Imager Active Region Patches (SHARPs). We show that True Skill Statistics (TSS) and Heidke Skill Scores (HSS) calculated for SVMs are slightly better than those from the MLPs. We also show that the forecasting time frame of 96 hours provides the best results in predicting if a flare will be associated with CMEs and SEPs (TSS=0.92$pm$0.09 and HSS=0.92$pm$0.08). Additionally, we obtain the maximum TSS and HSS values of 0.91$pm$0.06 for predicting that a flare will not be associated with CMEs and SEPs for the 36 hour forecast window, while the 108 hour forecast window give the maximum TSS and HSS values for predicting CMEs will not be accompanying any events (TSS=HSS=0.98$pm$0.02).
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