An automated survey of three and five minute oscillations in active regions

Details An automated survey of three and five minute oscillations in active regions An automated survey of three and five minute oscillations in active regions

Dec 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufmsh13b1952i&link_type=abstract

American Geophysical Union, Fall Meeting 2011, abstract #SH13B-1952

Astronomy and Astrophysics

Astrophysics

[7500] Solar Physics, Astrophysics, And Astronomy, [7509] Solar Physics, Astrophysics, And Astronomy / Corona, [7546] Solar Physics, Astrophysics, And Astronomy / Transition Region

Scientific paper

We present the results of an survey of the automatically detected three and five minute oscillation content of 44 active regions automatically detected by the SDO Feature Finding Team SPoCA (Spatial Possibilistic Clustering Algorithm; Barra et al., A&A, 2009, 505, 361). Analysis is restricted to one hour, full cadence, cut-outs of automatically detected active regions found in 171Å and 193Å from Atmospheric Imaging Assembly (AIA) data on board the Solar Dynamics Observatory (SDO). The oscillations were found using an improved version of the automated oscillation detection algorithm of Ireland et al. 2010, Sol. Phys. 264, 403, that also estimates the coherence and the local phase speed of any detected oscillating region. It is shown that most active regions only support very few oscillating regions of either three or five minute periods. Further, very few of these oscillating regions have a substantial coherence (greater than 0.6) and a relative phase speed error of less than 50%, our criteria for the detection of an identifiable and coherent wave. These results suggest that oscillating regions in active regions are rare. Finally, a large proportion of the regions that do oscillate with 5 minute periods do not do so coherently and with a well-defined phase speed. These results are discussed in the context of the recent suggestion that most five-minute oscillations are not due to slow-mode magnetohydrodynamic waves (De Moortel et al. 2000, A&A 355, L23) but are due to quasi-periodic flows (De Pontieu and McIntosh, 2010, Ap. J. 722, 1013). The advantages of using automated detection and classification methods are also briefly discussed.

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