Physics
Scientific paper
Jan 2000
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000pepi..117...21f&link_type=abstract
Physics of the Earth and Planetary Interiors, Volume 117, Issue 1-4, p. 21-35.
Physics
12
Scientific paper
This paper is devoted to a new approach to the problem of estimating the free core nutation (FCN) parameters from tidal gravity data. We first review different models of the FCN resonance parameters (period, damping, strength), as well as different inversion techniques used in gravimetry (analytical, linearised least squares, non-linear generalised inverse, stochastic). We propose then a new Bayesian inversion method since such a probabilistic view allows the most complete and reliable information on the FCN resonance to be obtained. We show the consequences of introducing the positivity of the quality factor Q and, even more important, we show that the null information criterion on this factor allows us to better understand why Q is often underestimated in gravity studies (or even found to be negative) with standard least squares techniques. We apply the Bayesian estimation method to a set of gravity data originating from a 3000-day record (1988-1996) of the superconducting gravimeter (SG T005) near Strasbourg (France), after correction for pressure effects and ocean loading with the help of a recent model derived from satellite altimetry. The marginal distribution found for the eigenperiod is nearly Gaussian and leads to a most probable value of 428 days, in agreement with previous gravity studies. The Q distribution is found to be highly asymmetrical with a flat maximum probability that Q exceeds 105, in agreement with the high values derived from very large baseline interferometry (VLBI) studies. The joint probability laws of the parameters show that strong correlations exist between some couples of parameters. Finally, the important impact of inaccurate ocean loading corrections on the determination of the damping of the eigenmode is pointed out; it appears that wrong ocean corrections may lead to underestimation of Q or, even worse, to generation of negative Q when using standard least squares retrieval techniques applied to gravity data.
Florsch Nicolas
Hinderer Jacques
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