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dc.contributor.authorPagano, Paolo
dc.contributor.authorMackay, Duncan H.
dc.contributor.authorYardley, Stephanie L.
dc.date.accessioned2019-09-03T11:30:04Z
dc.date.available2019-09-03T11:30:04Z
dc.date.issued2019-09-26
dc.identifier260661622
dc.identifier4e1bf568-d2d7-4e5c-9a75-c8a85dda2347
dc.identifier85074129600
dc.identifier85074129600
dc.identifier000488058300002
dc.identifier.citationPagano , P , Mackay , D H & Yardley , S L 2019 , ' A prospective new diagnostic technique for distinguishing eruptive and noneruptive active regions ' , Astrophysical Journal , vol. 883 , no. 2 , 112 . https://doi.org/10.3847/1538-4357/ab3e42en
dc.identifier.issn0004-637X
dc.identifier.otherORCID: /0000-0001-6065-8531/work/66591821
dc.identifier.urihttps://hdl.handle.net/10023/18411
dc.descriptionThis research has received funding from the Science and Technology Facilities Council (UK) through the consolidated grant ST/N000609/1 and the European Research Council (ERC) under the European Union Horizon 2020 research and innovation program (grant agreement No. 647214). This work used the DiRAC@Durham facility managed by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The equipment was funded by BEIS capital funding via STFC capital grants ST/P002293/1, ST/R002371/1, and ST/S002502/1, Durham University and STFC operations grant ST/R000832/1. DiRAC is part of the National e-Infrastructure. S.L.Y. would like to acknowledge STFC for support via the Consolidated Grants SMC1/YST025 and SMC1/YST037. D.H.M. would like to thank both the UK STFC and the ERC (Synergy Grant: WHOLE SUN, Grant Agreement No. 810218) for financial support.en
dc.description.abstractActive regions are the source of the majority of magnetic flux rope ejections that become coronal mass ejections (CMEs). To identify in advance which active regions will produce an ejection is key for both space weather prediction tools and future science missions such as Solar Orbiter. The aim of this study is to develop a new technique to identify which active regions are more likely to generate magnetic flux rope ejections. The new technique will aim to (i) produce timely space weather warnings and (ii) open the way to a qualified selection of observational targets for space-borne instruments. We use a data-driven nonlinear force-free field (NLFFF) model to describe the 3D evolution of the magnetic field of a set of active regions. We determine a metric to distinguish eruptive from noneruptive active regions based on the Lorentz force. Furthermore, using a subset of the observed magnetograms, we run a series of simulations to test whether the time evolution of the metric can be predicted. The identified metric successfully differentiates active regions observed to produce eruptions from the noneruptive ones in our data sample. A meaningful prediction of the metric can be made between 6 and 16 hr in advance. This initial study presents an interesting first step in the prediction of CME onset using only line-of-sight magnetogram observations combined with NLFFF modeling. Future studies will address how to generalize the model such that it can be used in a more operational sense and for a variety of simulation approaches.
dc.format.extent15
dc.format.extent3348154
dc.language.isoeng
dc.relation.ispartofAstrophysical Journalen
dc.subjectSolar activityen
dc.subjectSolar magnetic fieldsen
dc.subjectSpace weatheren
dc.subjectSolar active regionsen
dc.subjectSolar active region magnetic fieldsen
dc.subjectSolar coronal mass ejectionsen
dc.subjectSolar coronaen
dc.subjectSolar flaresen
dc.subjectQB Astronomyen
dc.subjectQC Physicsen
dc.subjectSpace and Planetary Scienceen
dc.subjectAstronomy and Astrophysicsen
dc.subjectT-NDASen
dc.subject.lccQBen
dc.subject.lccQCen
dc.titleA prospective new diagnostic technique for distinguishing eruptive and noneruptive active regionsen
dc.typeJournal articleen
dc.contributor.sponsorEuropean Research Councilen
dc.contributor.sponsorScience & Technology Facilities Councilen
dc.contributor.sponsorScience & Technology Facilities Councilen
dc.contributor.sponsorScience & Technology Facilities Councilen
dc.contributor.sponsorScience & Technology Facilities Councilen
dc.contributor.sponsorEuropean Research Councilen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Applied Mathematicsen
dc.identifier.doi10.3847/1538-4357/ab3e42
dc.description.statusPeer revieweden
dc.identifier.grantnumber647214en
dc.identifier.grantnumberST/S000402/1en
dc.identifier.grantnumberST/N000609/1en
dc.identifier.grantnumberPO: 4070103637en
dc.identifier.grantnumberN/Aen
dc.identifier.grantnumber810218en


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