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

A Comparison of Flare Forecasting Methods. II. Benchmarks, Metrics and Performance Results for Operational Solar Flare Forecasting Systems