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Acoustic Holographic Studies of Solar Active Region Structure A. Malanushenko 1,2, D. Braun 3, S. Kholikov 2, J. Leibacher 2, C. Lindsey 3 (1) Saint Petersburg.

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Presentation on theme: "Acoustic Holographic Studies of Solar Active Region Structure A. Malanushenko 1,2, D. Braun 3, S. Kholikov 2, J. Leibacher 2, C. Lindsey 3 (1) Saint Petersburg."— Presentation transcript:

1 Acoustic Holographic Studies of Solar Active Region Structure A. Malanushenko 1,2, D. Braun 3, S. Kholikov 2, J. Leibacher 2, C. Lindsey 3 (1) Saint Petersburg State University (2) National Solar Observatory, Tucson, AZ (3) Colorado Research Corp., Boulder, CO

2 Abstract We present results of a study of the morphology and evolution of active regions using solar acoustic holography. These include acoustic signatures of large far-side active regions and their relationship to near-side activity indicators (e.g. Ca II K-line images and magnetograms) a half rotation before and after the farside image, and the direct comparison of near-side acoustic signatures with the standard activity indicators, not only in their own right but also to calibrate the farside acoustic signature.

3 About GONG Far side map with GONG data 2002.04.01 12.00

4 The Global Oscillation Network Group (GONG) is a program for detailed study of solar internal structure and dynamics using helioseismology. GONG is a six-station network of extremely sensitive velocity imagers, located around the Earth, to obtain nearly continuous observations of the Sun's "five-minute" oscillations. The sites that comprise the GONG network are: Big Bear Solar Observatory Learmonth Solar Observatory Udaipur Solar Observatory Observatorio del Teide Cerro Tololo Interamerican Observatory Mauna Loa Observatory Current, real data, coverage is around 87%. About GONG

5 Basic concepts Propagation of a disturbance on the farside to the nearside is called the “egression” [H+], and the converse is the “ingression” [H-] egression& ingression schemes chromosphere photosphere plage sunspot Acoustic waves propagating Regions of depressed photosphere, mainly plages and sunspots, reduce wave travel time by a few seconds and thus can be detected by examining acoustic waves. The computations apply to waves that reflect once from the solar surface between the active region and the near side.

6 To study phase shifts between complex functions H + and H -, we build correlation maps, H + *H -. Where the Sun is quiet and H + =H -, we get a real value. Where there is a phase shift, the imaginary part of the correlation becomes significant. The imaginary part of the correlation map, normalized to amplitude, gives a pattern of regions, in terms of phase shifts, mainly due to plages but also to sunspots. In the case of quiet Sun, H + = H -. But if a wave coming to some point A was reflected from sunspot, its travel time was reduced, that is why its phase was shifted and H +  H - in A. It means that by studying phase shifts between H + and H - sunspot and plages can be seen. Because of wave diffraction, spatial resolution is limited to about 10° of arc on the Sun’s surface. Basic concepts active region signature far side image: Im(H + *H - )

7 Magnetogram for [2002.03.10..2002.03.26] Far Side map for [2002.03.27..2002.04.05] Magnetogram for [2002.04.01..2002.04.21] Far Side map for [2002.03.27..2002.04.05] Correlation of far side with near side: predictive capabilities For a comparison, magnetogram data taken at the NASA/NSO/Kitt Peak Vacuum Telescope were used

8 Correlation of far side with near side: predictive capabilities There are practical ways to improve the quality of GONG farside images. One of them is building a cumulative map from consecutive images, which shows good visual correlation with the nearside one half-rotation before and after it was taken, as shown on the picture. A principal difficulty in calibrating farside technique is the lifetime of active regions. Large active regions, for which the predictive task is applied, may live for more than half a rotation. So complete study of far- side signatures should include an accurate study of active region lifetime function.

9 The correlation between GONG and MDI farside image is pretty much linear. The width of the correlation can be caused by slight differences in the preparation of the final images, such as smearing the very output with a slightly different value. Calibration between GONG and MDI The more important thing is a constant phase shift between GONG and MDI results. The lines are parallels to y = x.

10 Correlation of far side with near side: predictive capabilities 1.Frequent site changes 2.Frequent data gaps, even if they are small 3.Large data gaps, even if they are infrequent 4.Errors caused by clouds About 60% of the far-side images computed from GONG images are similar to MDI images computed at the same time and clearly show large active regions on the Sun’s far side. The reasons for the noise coming from a numerical simulation of an inverse problem could arise from the following:

11 Comparison of nearside acoustic data with observations For a comparison, magnetograms data taken in NASA/NSO/Kitt Peak Vacuum Telescope and CaIIK data taken in Big Bear Solar Observatory was used Nearside acoustic map Magnetogram with nearside contours

12 Comparison of nearside acoustic data with observations Acoustic holography principles, applied to a shorter wavelengths and thus showing the nearside interior “from above”, were considered to be used for a comparison with farside data. For a comparison, magnetogram data taken in NASA/NSO/Kitt Peak Vacuum Telescope was used Till nearside images are showing active regions in a very fine details, they can be used to calibrate phase shifts with a magnetic field strength. It clearly shows that the technique is correct at shorter wavelengths and also shows that farside could very well be calibrated with nearside observations by themselves.

13 Days since 2002.02.23 GONG MDI Solar Activity Index

14 Testing correlation with index of solar activity. Data used: Farside images from GONG and MDI and “nearside” solar activity index from Beljium Solar Data Senter. The following reduction has been done: 1. Mean values calculated for each Farside image 2. Each sets of data was normalized by subtracting of correspondent average value and dividing by standard deviation. These plots show normalized mean for GONG, MDI and nearside activity indices as a function of time. The correlation between solar activity index and farside images for both GONG and MDI is not possible to see with this simple model. It is necessary to setup additional calibration procedure for farside images to make them compatible with index of solar activity.


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