Weighting algorithms to stack superconducting gravimeter data for the potential detection of the Slichter modes

Details Weighting algorithms to stack superconducting gravimeter data for the potential detection of the Slichter modes Weighting algorithms to stack superconducting gravimeter data for the potential detection of the Slichter modes

Jan 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006jgeo...41..326g&link_type=abstract

Journal of Geodynamics, Volume 41, Issue 1-3, p. 326-333.

Physics

2

Scientific paper

We propose a weighting scheme in stacking superconducting gravimeter (SG) records, i.e. stacking different records with appropriate distinct weights, for potential detection of weak signals such as the Slichter modes. The stacking methods considered include the geometric averages of the spectral amplitudes, which is in principle equivalent to the product spectrum of Smylie et al. [Smylie, D.E., Hinderer, J., Richter, B., Ducarme, B., 1993. The product spectra of gravity and barometric pressure in Europe. Phys. Earth Planet. Int. 80, 135 157], and the multi-station method of Courtier et al. [Courtier, N., Ducarme, B., Goodkind, J., Hinderer, J., Imanishi, Y., Seama, N., Sun, H., Merriam, J., Bengert, B., Smylie, D.E., 2000. Global superconducting gravimeter observations and the search for the translational modes of the inner core. Phys. Earth Planet. Int. 117, 3 20]. Numerical tests are made using real SG data. The results show that the weighting brings apparent improvement when data with distinctly different noise levels are stacked together. However, for evident reason, the improvement is not as prominent if the data stacked are of similar noise level. Although there has been no apparent triplet associated with the Slichter modes identified, the developed technique is envisioned to improve potentially such detection.

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