TY - JOUR
T1 - A Comparison of Flare Forecasting Methods. III. Systematic Behaviors of 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
AU - Steenburgh, Rob
AU - Steward, Graham
AU - Terkildsen, Michael
PY - 2019/8/20
Y1 - 2019/8/20
N2 - A workshop was recently held at Nagoya University (31 October – 02 November 2017), sponsored by the Center for International Collaborative Research, at the Institute for Space-Earth Environmental Research, Nagoya University, Japan, 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.
AB - A workshop was recently held at Nagoya University (31 October – 02 November 2017), sponsored by the Center for International Collaborative Research, at the Institute for Space-Earth Environmental Research, Nagoya University, Japan, 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.
KW - methods: statistical
KW - Sun: flares
KW - Sun: magnetic fields
U2 - 10.3847/1538-4357/ab2e11
DO - 10.3847/1538-4357/ab2e11
M3 - Article
VL - 881
JO - Astrophysical Journal
JF - Astrophysical Journal
SN - 0004-637X
IS - 2
M1 - 101
ER -