J/ApJ/786/19ivo://CDS.VizieR/J/ApJ/786/19doi:10.26093/cds/vizier.17860019CDSBarnes G.Birch A.C.Leka K.D.Braun D.C.2017-09-04T08:19:25Z2017-08-04T11:47:26ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frthe-sunastronomical-modelsThe subsurface properties of active regions (ARs) prior to their appearance at the solar surface may shed light on the process of AR formation. Helioseismic holography has been applied to samples taken from two populations of regions on the Sun (pre-emergence and without emergence), each sample having over 100 members, that were selected to minimize systematic bias, as described in Paper I (Leka et al. 2013ApJ...762..130L). Paper II (Birch et al. 2013ApJ...762..131B) showed that there are statistically significant signatures in the average helioseismic properties that precede the formation of an AR. This paper describes a more detailed analysis of the samples of pre-emergence regions and regions without emergence based on discriminant analysis. The property that is best able to distinguish the populations is found to be the surface magnetic field, even a day before the emergence time. However, after accounting for the correlations between the surface field and the quantities derived from helioseismology, there is still evidence of a helioseismic precursor to AR emergence that is present for at least a day prior to emergence, although the analysis presented cannot definitively determine the subsurface properties prior to emergence due to the small sample sizes.2014ApJ...786...19Bhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/786/19CatalogResearchIsServedByTAP VizieR generic servicerelated-toJ/ApJ/759/141 : Emission measures in solar active regions (Warren+, 2012)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/786/19https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/786/19http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/786/19https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/786/19https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/786/19http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/786/19GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapdefaultJ/ApJ/786/19/table4Best Performing Variables with Skill Score>0.27recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintVariableVariable namemeta.id;meta.maincharWeight[1/3] Weight factor used in spatial average (1)stat.weight;phys.atmol.weight;stat.meanintFilterFilter numbermeta.idcharTI[0/4] Time Intervaltime.intervalintPSSPeirce Skill Score (2)statfloate_PSSUncertainty in PSSstat.errorfloatJ/ApJ/786/19/table5Best Performing Variables with Skill Score>0.24recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintVariableVariable namemeta.id;meta.maincharWeight[1/3] Weight factor used in spatial average (1)stat.weight;phys.atmol.weight;stat.meanintFilterFilter numbermeta.idcharTI[0/4] Time Intervaltime.intervalintPSSPeirce Skill Score (2)statfloate_PSSUncertainty in PSSstat.errorfloat