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dc.contributor.authorLeka, K.D.
dc.contributor.authorPark, S-H.
dc.contributor.authorKusano, K.
dc.contributor.authorAndries, J.
dc.contributor.authorBarnes, G.
dc.contributor.authorBingham, S.
dc.contributor.authorBloomfield, D.S.
dc.contributor.authorMcCloskey, A.E.
dc.contributor.authorDelouille, V.
dc.contributor.authorFalcomer, D.
dc.contributor.authorGallagher, P.T.
dc.contributor.authorGeorgoulis, M.K.
dc.contributor.authorKubo, Y.
dc.contributor.authorLee, K.
dc.contributor.authorLee, S.
dc.contributor.authorLobzin, V.
dc.contributor.authorMun, J.
dc.contributor.authorMurray, S.A.
dc.contributor.authorNageem, T.A.M.H.
dc.contributor.authorQahwaji, Rami S.R.
dc.contributor.authorSharpe, M.
dc.contributor.authorSteenburgh, R.
dc.contributor.authorSteward, G.
dc.contributor.authorTerkildsen, M.
dc.date.accessioned2019-07-26T00:07:51Z
dc.date.accessioned2019-08-07T14:34:22Z
dc.date.available2019-07-26T00:07:51Z
dc.date.available2019-08-07T14:34:22Z
dc.date.issued2019-08
dc.identifier.citationLeka KD, Park S-H, Kusano K et al (2019) A comparison of flare forecasting methods. III. Systematic behaviors of operational solar flare forecasting systems. Astrophysical Journal Supplement Series. 881(2): 101.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17194
dc.descriptionYesen_US
dc.description.abstractA 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.en_US
dc.language.isoenen_US
dc.rights© 2019 American Astronomical Association. Reproduced in accordance with the publisher's self-archiving policy.en_US
dc.subjectMethodsen_US
dc.subjectStatistical - sunen_US
dc.subjectFlares - sunen_US
dc.subjectMagnetic fieldsen_US
dc.titleA comparison of flare forecasting methods. III. Systematic behaviors of operational solar flare forecasting systemsen_US
dc.status.refereedYesen_US
dc.date.Accepted2019
dc.date.Accepted2019-05-07
dc.date.application2019-08-16
dc.typeArticleen_US
dc.type.versionAccepted manuscripten_US
dc.identifier.doihttps://doi.org/10.3847/1538-4357/ab2e11
dc.date.updated2019-07-25T23:07:53Z
refterms.dateFOA2019-08-07T14:35:03Z


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