Solar p-mode frequencies at : What do analyses of unresolved observations actually measure?

¹ School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
² ESA Research and Science Support Department, ESTEC, 2200 AG Noordwijk, The Netherlands
³ School of Science & Mathematics, Sheffield Hallam University, Sheffield S1 1WB
⁴ Département Cassini, URA CNRS 1362, Observatoire de la Côte d'Azur, 06304 Nice, France
⁵ Institute of Theoretical Astrophysics, University of Oslo, PO Box 1029, 0315 Oslo, Norway

Corresponding author: W. J. Chaplin, wjc@bison.ph.bham.ac.uk

Received: 7 October 2003
Accepted: 3 December 2003

Abstract

We have studied in detail the extraction of estimates of p-mode frequencies from unresolved observations of the visible disc of the Sun. Examples of data of this type include ground-based observations made by the Birmingham Solar-Oscillations Network (BiSON), and space-borne observations made by the GOLF and VIRGO/SPM instruments on board the ESA/NASA SOHO satellite. The fitting of the modes is complicated in practice by the asymmetric arrangement in frequency of the three components (, 0 and 2) that are prominent in such data. In order to investigate the effect of this we used a series of 10-yr artificial datasets into which varying degrees of asymmetry were introduced. The sets were designed to mimic the characteristics of the BiSON and GOLF data, and were analyzed both with and without the BiSON window function from the period 1992 through 2001. Since reliable estimates of the asymmetry have only recently been extracted from unresolved observations (Chaplin et al. [CITE]a) it has for a long time been standard practice to fit the modes to a model that assumes a symmetrically arranged multiplet. We have tested the impact of this on the accuracy of the extracted frequencies. Furthermore, we demonstrate that asymmetric models can be successfully applied, provided the data are of sufficient length and quality. We also discuss the implications of our simulations for analyses of real solar data.