You can find here tables of mode frequencies, line-widths, asymmetries and amplitudes, resulting from fitting full-disk data, for l=100 to l=1000 (or 900) resulting from ridge fitting, corrected to produce mode estimates.

I have now fitted three instruments (MDI, GONG and HMI) for three Dynamics epochs:

Instrument	Year (length, days)
MDI	2001 (90d)	2002 (98d)	2010 (67d)
GONG		2002 (98d)	2010 (67d)
HMI			2010 (67d)

The exact same epochs were fitted for each instrument for each year, as determined by MDI's full-disk images availability, only the fill factor is different.

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The following files explain the formats, or hold IDL routines:

• multiplets.txt: description of format and content of multiplets.dat
• cg-coefs.txt: description of format and content of cg-coefs.dat
• singlets.txt: description of format and content of singlets.dat

• routines.sav: my IDL routines, as a save set, needed for reproducing the plots, including read_struct(), that can be used to read the .dat files.
• plot-multiplets.pro: IDL routine to plot multiplets.dat
• plot-cg-coefs.pro: IDL routine to plot cg-coefs.dat

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A paper, in preparation, will describe these results. Despite my best efforts, results from co-eval observations using different instruments (and different but appropriate leakage matrices) do not produce the exact same results.

Comparisons of the co-eval results, for frequencies and CG coefs, are in the following PDF files:

• compare-2002-frq.pdf: MDI & GONG 2002 frequencies
• compare-2002-cgs.pdf: MDI & GONG 2002 CG coefs
• compare-2002-cgs-raw.pdf: MDI & GONG 2002 raw (uncorected) CG coefs

• compare-2010-frq.pdf: MDI, GONG & HMI 2010 frequencies
• compare-2010-cgs.pdf: MDI, GONG & HMI 2010 CG coefs
• compare-2010-cgs-raw.pdf: MDI, GONG & HMI 2010 raw (uncorected) CG coefs

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In each subdirectory, the tables are in the following files:

• multiplets.dat: Table of multiplets (l, n), after fitting CG coefs to the singlets.
• multiplets-xx-yyyy.pdf: resulting plot.

• cg-coefs-xx-yyyy.dat: Table of Clebsch-Gordan coefficients
• cg-coefs-xx-yyyy.pdf: resulting plot.

• singlets-xx-yyyy.dat.gz: Table of singlets (l,n,m), some 5.2 million modes, for all azimuthal orders and all degrees from l=100 to l=1000 (gzip compressed file).

where xx-yyyy corresponds to intrument and year (like mdi-2001).

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NOTE that the dots in some of the PDF plots "disappear" at some zoom level(s) when viewing them with acroread - zoom in or out to see them.

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The paper, published in the ApJ and available at astro-ph, that describes the methodology used to produce these tables:

Accurate Characterization of High-Degree Modes Using MDI Observations

S.G. Korzennik(1), M.C. Rabello-Soares(2,3), 
J. Schou(2) and T.P. Larson(2)

(1) Harvard-Smithsonian Center for Astrophysics, Cambridge, MA
(2) W. W. Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA 
(3) now at Universidade Federal de Minas Gerais, Physics Department, Minas Gerais, Brazil

                                    ABSTRACT

      We  present the  first accurate  characterization of  high-degree modes,
 derived using  the best MDI  full-disk full-resolution data set  available. A
 ninety day long time series  of full-disk two arc-second per pixel resolution
 dopplergrams was acquired in 2001, thanks to the high rate telemetry provided
 by the Deep Space Network. These dopplergrams were spatially decomposed using
 our best estimate of the image  scale and the known components of MDI's image
 distortion.   A multi-taper  power spectrum  estimator was  used  to generate
 power spectra for  all degrees and all  azimuthal orders, up to l  = 1000. We
 used a large number of tapers  to reduce the realization noise, since at high
 degrees the individual modes blend into ridges and thus there is no reason to
 preserve a high spectral resolution.  These power spectra were fitted for all
 degrees and all azimuthal  orders, between l = 100 and l  = 1000, and for all
 the orders with  substantial amplitude.  This fitting generated  in excess of
 5.2×10^6 individual  estimates of ridge  frequencies, line-widths, amplitudes
 and  asymmetries (singlets),  corresponding  to some  5,700  multiplets   (l,
 n). Fitting at high  degrees generates ridge characteristics, characteristics
 that  do not correspond  to the  underlying mode  characteristics. We  used a
 sophisticated forward modeling  to recover the best possible  estimate of the
 underlying mode  characteristics (mode  frequencies, as well  as line-widths,
 amplitudes and  asymmetries).  We  describe in detail  this modeling  and its
 validation.   The modeling  has  been extensively  reviewed  and refined,  by
 including  an iterative  process to  improve its  input parameters  to better
 match the observations.  Also, the  contribution of the leakage matrix on the
 accuracy of the procedure has been carefully assessed. We present the derived
 set of  corrected mode characteristics,  that includes not  only frequencies,
 but line  widths, asymmetries and  amplitudes.  We present and  discuss their
 uncertainties  and the  precision of  the ridge  to mode  correction schemes,
 through a  detailed assessment of the  sensitivity of the model  to its input
 set.  The  precision of  the ridge  to mode correction  is indicative  of any
 possible residual systematic biases  in the inferred mode characteristics. In
 our conclusions, we  address how to further improve  these estimates, and the
 implications for other data sets, like GONG+ and HMI. 

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