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dc.contributor.authorPark, S.H.
dc.contributor.authorLeka, K.D.
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.authorFalconer, 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.authorHamad Nageem, Tarek A.M.
dc.contributor.authorQahwaji, Rami S.R.
dc.contributor.authorSharpe, M.
dc.contributor.authorSteenburgh, R.A.
dc.contributor.authorSteward, G.
dc.contributor.authorTerkildsen, M.
dc.date.accessioned2021-03-21T00:41:24Z
dc.date.accessioned2021-03-26T13:19:51Z
dc.date.available2021-03-21T00:41:24Z
dc.date.available2021-03-26T13:19:51Z
dc.date.issued2020-02-19
dc.identifier.citationPark SH, Leka KD, Kusano K et al (2020) A Comparison of Flare Forecasting Methods. IV. Evaluating Consecutive-day Forecasting Patterns. Astrophysical Journal. 890(2): 124.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18411
dc.descriptionNoen_US
dc.description.abstractA crucial challenge to successful flare prediction is forecasting periods that transition between "flare-quiet" and "flare-active." Building on earlier studies in this series in which we describe the methodology, details, and results of flare forecasting comparison efforts, we focus here on patterns of forecast outcomes (success and failure) over multiday periods. A novel analysis is developed to evaluate forecasting success in the context of catching the first event of flare-active periods and, conversely, correctly predicting declining flare activity. We demonstrate these evaluation methods graphically and quantitatively as they provide both quick comparative evaluations and options for detailed analysis. For the testing interval 2016-2017, we determine the relative frequency distribution of two-day dichotomous forecast outcomes for three different event histories (i.e., event/event, no-event/event, and event/no-event) and use it to highlight performance differences between forecasting methods. A trend is identified across all forecasting methods that a high/low forecast probability on day 1 remains high/low on day 2, even though flaring activity is transitioning. For M-class and larger flares, we find that explicitly including persistence or prior flare history in computing forecasts helps to improve overall forecast performance. It is also found that using magnetic/modern data leads to improvement in catching the first-event/first-no-event transitions. Finally, 15% of major (i.e., M-class or above) flare days over the testing interval were effectively missed due to a lack of observations from instruments away from the Earth-Sun line.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.3847/1538-4357/ab65f0en_US
dc.subjectSunen_US
dc.subjectSolar magnetic fieldsen_US
dc.subjectSolar flaresen_US
dc.subjectSolar activityen_US
dc.subjectSolar active region magnetic fieldsen_US
dc.subjectSunspotsen_US
dc.subjectSolar x-ray flaresen_US
dc.subjectAstronomy data analysisen_US
dc.subjectAstronomy data visualisationen_US
dc.subjectAstrostatistics toolsen_US
dc.titleA Comparison of Flare Forecasting Methods. IV. Evaluating Consecutive-day Forecasting Patternsen_US
dc.status.refereedYesen_US
dc.date.Accepted2019-12-26
dc.typeArticleen_US
dc.type.versionNo full-text in the repositoryen_US
dc.date.updated2021-03-21T00:41:29Z
refterms.dateFOA2021-03-26T13:25:04Z
dc.openaccess.statusNot Open Accessen_US


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