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J/ApJ/786/19     Statistical analysis of solar active regions    (Barnes+, 2014)

Helioseismology of pre-emerging active regions. III. Statistical analysis. Barnes G., Birch A.C., Leka K.D., Braun D.C. <Astrophys. J., 786, 19 (2014)> =2014ApJ...786...19B (SIMBAD/NED BibCode)
ADC_Keywords: Sun ; Models Keywords: methods: statistical - Sun: helioseismology - Sun: interior - Sun: magnetic fields - Sun: oscillations - sunspots Abstract: The 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. Description: In brief, samples from two populations are considered: "pre-emergence" targets (PE) that track a 32°x32° patch of the Sun prior to the emergence of a NOAA-numbered AR and "non-emergence" targets (NE) selected for lack of emergence and lack of strong fields in the central portions of the tracked patch. The PE sample size comprises 107 targets obtained between 2001 and 2007, matched to 107 NE targets drawn from an initially larger sample and selected further to match the PE distributions in time and observing location on the disk. File Summary:
FileName Lrecl Records Explanations
ReadMe 80 . This file table4.dat 29 1325 Best Performing Variables with Skill Score>0.27 table5.dat 29 1335 Best Performing Variables with Skill Score>0.24
See also: J/ApJ/759/141 : Emission measures in solar active regions (Warren+, 2012) Byte-by-byte Description of file: table4.dat table5.dat
Bytes Format Units Label Explanations
1- 7 A7 --- Variable Variable name 9 I1 --- Weight [1/3] Weight factor used in spatial average (1) 11- 14 A4 --- Filter Filter number 16 I1 --- TI [0/4] Time Interval 18- 23 F6.3 --- PSS Peirce Skill Score (2) 25- 29 F5.3 --- e_PSS Uncertainty in PSS
Note (1): Weight factor as follows: 1 = uniform; 2 = cos θ; 3 = sin θ. Note (2): We used the Peirce skill score (Peirce, 1884Sci.....4..453P). It is given by PSS=npp/np-nnp/nn, where where npp is the number of regions that were classified by the discriminant analysis to be emergences and did emerge, np is the number of PE regions, nnp is the number of regions that were classified by the discriminant analysis to be non-emergences but did emerge, and nn is the number of NE regions.
History: From electronic version of the journal References: Leka et al. Paper I 2013ApJ...762..130L Birch et al. Paper II 2013ApJ...762..131B
(End) Prepared by [AAS], Tiphaine Pouvreau [CDS] 20-Jul-2017
The document above follows the rules of the Standard Description for Astronomical Catalogues.From this documentation it is possible to generate f77 program to load files into arrays or line by line

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