On the Inference of the Solar Internal Rotation Profile from Frequency-splitting Data

Details On the Inference of the Solar Internal Rotation Profile from Frequency-splitting Data On the Inference of the Solar Internal Rotation Profile from Frequency-splitting Data

Oct 1996

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996apj...470..621w&link_type=abstract

Astrophysical Journal v.470, p.621

Astronomy and Astrophysics

Astronomy

14

Convection, Magnetohydrodynamics: Mhd, Sun: Interior, Sun: Oscillations

Scientific paper

From the earliest helioseismology data it was inferred that the internal angular velocity of the Sun is invariant across the convection zone (i.e., it mimics the surface differential rotation). This result caused some concern to theoreticians since many dynamo and dynamical models of the convection zone require that the angular velocity be approximately constant on cylinders concentric about the rotation axis.
Stark and others have argued that in order to test models of the angular velocity against frequency- splitting data the uncertainties in these data must be magnified, and it is shown here that within these uncertainties it is indeed difficult to exclude some models in which the angular velocity is independent of radius across a region including the convection zone and some depths below it. Further, Gough and his colleagues have recently claimed that the currently available data are not inconsistent with some models for which the angular velocity is constant on cylinders within the Sun's convection zone. Thus, inferences from frequency-splitting data regarding the internal angular velocity of the Sun would seem to be somewhat uncertain.
In this paper, these uncertainties are discussed and an alternative approach is proposed in which a forward method is used to find the simplest model for the angular velocity (i.e., with the least positional variations) consistent with the data, including the quoted uncertainties. While it is not claimed that such a model represents the true angular velocity, its features may be said to "characterize" the essential properties of a particular data set.

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