Hostname: page-component-7479d7b7d-qlrfm Total loading time: 0 Render date: 2024-07-13T01:14:36.428Z Has data issue: false hasContentIssue false
  • English
  • Français

Long-term Earth Orientation Monitoring Using Various Techniques

Published online by Cambridge University Press:  12 April 2016

D. Gambis
D. Gambis*
Affiliation:
IERS/CB and UMR8630, Paris Observatory, Paris, France

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A continuous composite series of polar motion components extending from 1846 until now called EOP (IERS) C01 is available at the Earth Orientation Section of the Central Bureau of the IERS. This series is the basis of the IERS system. It relies on different series derived from optical astrometry until 1972 and geodetic techniques since. It is given at 0.1 year intervals (1846–1889) and 0.05 year intervals (1890-now). Its accuracy has dramatically improved from 100 mas in 1846 to about 0.2 mas at present.

Now the IERS combined solutions involve mainly the contributions of VLBI, GPS and SLR techniques. It is regularly recomputed to take advantage of the improvement of the various recent individual contributions and of the refinement of the analyses procedures.

The objective of this paper is to describe this long-term polar motion series and to present the evolution and the state of the art of the multi-technique EOP combined solutions and the predictions regularly computed at the IERS/CB.

Type
Part 4. Long-term Polar Motion
Information
International Astronomical Union Colloquium , Volume 178: Polar Motion: Historical and Scientific Problems , 2000 , pp. 337 - 344
Copyright
Copyright © Astronomical Society of the Pacific 2000

References

Bevington, P.R., 1969, Data reduction and error analysis for the physical sciences, McGraw-Hill Book Company, New York, USA.Google Scholar
Bougeard, M.L., Gambis, D. and Ray, R., 1999, Algorithms for box constrained M-estimation: fitting large data sets with applications to Earth Orientation Parameters series, subm. to Physics and Chemistry of the Earth.Google Scholar
Eisop, E. And Gambis, D., 1997: The combined solutions of the IERS Central Bureau, Proc. Journées Systèmes de Référence, Praha, p. 104.Google Scholar
Fedorov, E.P., Korsun, A.A., Mayor, S.P., Pantschenko, N.I., Tarady, V.K., and Yatskiv, Y.S., 1972: Dvizhenie polyusa Zemli s 1890.0 po 1969.0.NaukovaGoogle Scholar
Frede, V., 1999, PhD thesis, Paris Observatory.Google Scholar
Gambis, D., 1992, Wavelet transform analysis of the length of the day and the El Niño/Southern oscillation variations at intraseasonal and interannual time scales, Ann. geophys., 10, 429–437.Google Scholar
Gambis, D., 1996: Multi-technique EOP combinations, Proceedings of the 1996 IGS Analysis Center Workshop, Silver Spring. MD, edited by Van Scoy, P. and Neilan, R.E., Pasadena, CA, JPL, JPL Publication 96–23.Google Scholar
Gambis, D., 1996, Monitoring Earth Rotation using various techniques, current results and future prospects, Proc. Coll. IAU 165, Dynamics and as-trometry of natural and artificial celestial bodies.CrossRefGoogle Scholar
Gray, J.E. and Allan, D.W. 1974: A method for estimating the frequency stability of an individual oscillator. Proc 8th Ann. Symp. on Frequency Control, 2439, 277–287.Dumka, Kiev. [English translation of the text available].Google Scholar
IERS Conventions, 1996, McCarthy (ed.).Google Scholar
Torrence, C. and Compo, G.P., 1998: A Practical Guide to Wavelet Analysis. Bull. Amer. Meteor. Soc., 79, 61–78.Google Scholar
Vondrák, J., Ron, C., Pesek, I., Cepek, A., 1995, Astron. and Astrophys., 297, 899–906.Google Scholar