TY - JOUR
T1 - A Comparison of Flare Forecasting Methods. II. Benchmarks, Metrics and Performance Results for Operational Solar Flare Forecasting Systems
AU - Leka, K. D.
AU - Park, Sung-Hong
AU - Kusano, Kanya
AU - Andries, Jessie
AU - Barnes, Graham
AU - Bingham, Suzy
AU - Bloomfield, D. Shaun
AU - McCloskey, Aoife E.
AU - Delouille, Veronique
AU - Falconer, David
AU - Gallagher, Peter T.
AU - Georgoulis, Manolis K.
AU - Kubo, Yuki
AU - Lee, Kangjin
AU - Lee, Sangwoo
AU - Lobzin, Vasily
AU - Mun, JunChul
AU - Murray, Sophie A.
AU - Nageem, Tareek A. M. Hamad
AU - Qahwaji, Rami
AU - Sharpe, Michael A.
AU - Steenburgh, Rob
AU - Steward, Graham
AU - Terkildsen, Michael
PY - 2019/8/16
Y1 - 2019/8/16
N2 - 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.
AB - 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.
KW - methods: statistical
KW - Sun: flares
KW - Sun: magnetic fields
U2 - 10.3847/1538-4365/ab2e12
DO - 10.3847/1538-4365/ab2e12
M3 - Article
SN - 0067-0049
VL - 243
JO - Astrophysical Journal, Supplement Series
JF - Astrophysical Journal, Supplement Series
IS - 2
M1 - 36
ER -