Accurate Characterization of High-Degree Modes Using MDI Observations

TL;DR

This paper presents a detailed method for accurately characterizing high-degree solar oscillation modes using MDI data, involving advanced spectral analysis and modeling to recover true mode properties from ridge measurements.

Contribution

The study introduces a novel, comprehensive approach combining multi-taper spectral estimation and forward modeling to precisely determine high-degree mode characteristics from MDI observations.

Findings

Successfully characterized modes up to l=1000

Developed a validated forward modeling technique

Provided corrected mode parameters with uncertainty estimates

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. 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 up to l = 1000, with a large number of tapers to reduce the realization noise, while the blending at high degrees negates the need for high spectral resolution. These power spectra were fitted for all degrees and all azimuthal orders, between l = 100 and l = 1000. This fitting generated in excess of 6x10^6 individual estimates of ridge frequencies, line-widths, amplitudes and asymmetries (singlets: l,n,m), corresponding to some 6,000 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, discuss their uncertainties and the precision of the ridge to mode correction schemes. In our conclusions, we address how to further improve these estimates, and the implications for other data sets, like GONG+ and HMI.