Solar flares are extremely energetic phenomena in our Solar System. Their impulsive, often drastic radiative increases, in particular at short wavelengths, bring immediate impacts that motivate solar physics and space weather research to understand solar flares to the point of being able to forecast them. As data and algorithms improve dramatically, questions must be asked concerning how well the forecasting performs; crucially, we must ask how to rigorously measure performance in order to critically gauge any improvements. Building upon earlier-developed methodology (Barnes et al. 2016, Paper I), international representatives of regional warning centers and research facilities assembled in 2017 at the Institute for Space-Earth Environmental Research, Nagoya University, Japan to -for the first time -directly compare the performance of operational solar flare forecasting methods. Multiple quantitative evaluation metrics are employed, with focus and discussion on evaluation methodologies given the restrictions of operational forecasting. Numerous methods performed consistently above the "no skill" level, although which method scored top marks is decisively a function of flare event definition and the metric used; there was no single winner. Following in this paper series we ask why the performances differ by examining implementation details (Leka et al. 2019, Paper III), and then we present a novel analysis method to evaluate temporal patterns of forecasting errors in (Park et al. 2019, Paper IV). With these works, this team presents a well-defined and robust methodology for evaluating solar flare forecasting methods in both research and operational frameworks, and today's performance benchmarks against which improvements and new methods may be compared.

Magnetic field topologies between the Sun and Earth are important for the connectivity to Earth of solar suprathermal particles, e.g., solar energetic particles and beam electrons in type III solar radio bursts. An approach is developed for mapping large‐scale magnetic field lines near the solar equatorial plane, using near‐Earth observations and a solar wind model with nonzero azimuthal magnetic field at the source surface. Unlike Parker's spiral model, which restricts the in‐ecliptic angle ΦB in the Geocentric Solar Ecliptic coordinates to (90°–180°, 270°–360°) and so is unable to predict field configurations for the other ΦB values frequently observed in the solar wind, our approach can account for all the observed ΦB values. A set of predicted maps shows that near both minimal and maximal solar activity the field lines are typically open and that loops with both ends either connected to or disconnected from the Sun are relatively rare. The open field lines, nonetheless, often do not closely follow the Parker spiral, being less or more tightly wound, or strongly azimuthally or radially oriented, or inverted. The time‐varying classes, e.g., bidirectional electrons, of suprathermal electron pitch angle distributions (PADs) at 1 AU are predicted from the mapped field line configurations and compared with Wind observations for two solar rotations, one each near solar minimum and solar maximum. PAD predictions by our approach agree quantitatively (≈90%) with the PAD observations and outperform (by ≈20%) PAD predictions using Parker's model.

[1] Because of the rapidly increasing role of technology, including complicated electronic systems, spacecraft, etc., modern society has become more vulnerable to a set of extraterrestrial influences (space weather) and requires continuous observation and forecasts of space weather. The major space weather events like solar flares and coronal mass ejections are usually accompanied by solar radio bursts, which can be used for a real-time space weather forecast. Coronal type III radio bursts are produced near the local electron plasma frequency and near its harmonic by fast electrons ejected from the solar active regions and moving through the corona and solar wind. These bursts have dynamic spectra with frequency rapidly falling with time, the typical duration of the coronal burst being about 1 --3 s. This paper presents a new method developed to detect coronal type III bursts automatically and its implementation in a new Automated Radio Burst Identification System. The central idea of the implementation is to use the Radon transform for more objective detection of the bursts as approximately straight lines in dynamic spectra. Preliminary tests of the method with the use of the spectra obtained during 13 days show that the performance of the current implementation is quite high, $84%, while no false positives are observed and 23 events not listed previously are found. Prospects for improvements are discussed. The first automatically detected coronal type III radio bursts are presented.

to quantitatively compare the performance of today's operational solar flare forecasting facilities. Building upon Paper I of this series (Barnes et al. 2016), in Paper II (Leka et al. 2019 we described the participating methods for this latest comparison effort, the evaluation methodology, and presented quantitative comparisons. In this paper we focus on the behavior and performance of the methods when evaluated in the context of broad implementation differences. Acknowledging the short testing interval available and the small number of methods available, we do find that forecast performance: 1) appears to improve by including persistence or prior flare activity, region evolution, and a human "forecaster in the loop"; 2) is hurt by restricting data to disk-center observations; 3) may benefit from long-term statistics, but mostly when then combined with modern data sources and statistical approaches. These trends are arguably weak and must be viewed with numerous caveats, as discussed both here and in Paper II. Following this present work, we present in Paper IV a novel analysis method to evaluate temporal patterns of forecasting errors of both types (i.e., misses and false alarms; Park et al. 2019). Hence, most importantly, with this series of papers we demonstrate the techniques for facilitating comparisons in the interest of establishing performance-positive methodologies.