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Modeling and Observation of Loading Contribution to Time-Variable GPS Sites Positions

Conference paper
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 135)

Abstract

We investigate loading consequences on the time-variable GPS station positions of one hundred stations around the world during the 2001–2006 time period. We model the three dimensional site displacements using a Love number formalism to describe the elastic deformation of a spherical Earth model submitted to atmospheric, oceanic and hydrological loadings.

We produce site position time series using the GPS analysis software GAMIT/GLOBK with or without inserting a combination of loading models and study their impact on 3D site positions. First of all, we compare the variability of modeled and observed site positions without integrating loading. We secondly study the variability reduction in the GPS site positions provided by the loading when integrating it in the GAMIT Software as an a priori contribution to the station motion model.

We conclude that the seasonal variability of site vertical displacement is quite well explained by our model at several locations, mainly located at mid-latitudes in the northern hemisphere, while it is much less understood near coastal areas.

Keywords

Earth/Atmosphere/Ocean/Hydrosphere interactions Loading Earth’s deformation GPS Time-variable sites positions Vertical positioning 

Notes

Acknowledgments

The authors thank Matthew Rodell and Florent Lyard for providing their insights and datasets. We thank IGS, ECMWF, NCEP for providing data and products, and GAMITeers, T. Herring, R. King and P. Tregoning, for continuously improving and implementing new methods inside GAMIT/GLOBK.

References

  1. Biancale, R., G. Balmino, J.-M. Lemoine, J.-C. Marty, B. Moynot, F. Barlier., P. Exertier, O. Laurain, P. Gegout, P. Schwintzer, Ch. Reigber, A. Bode, Th. Gruber, R. König, F.-H. Massmann, J.C. Raimondo, R. Schmidt, and S.Y. Zhu. (2000). A new global Earth's gravity field model from satellite orbit perturbations: GRIM5-S1. Geophys. Res. Lett., 27, 3611–3614.CrossRefGoogle Scholar
  2. Biancale R., J.-M. Lemoine, G. Balmino, S. Loyer, S. Bruinsma, F. Perosanz, J.-C. Marty, and P. Gegout (2005). 3 years of decadal geoid variations from GRACE and LAGEOS data, CNES/GRGS product, December.Google Scholar
  3. Boehm J., B. Werl, and H. Schuh (2006). Troposphere mapping func-tions for GPS and very long baseline interferometry from European Centre for Medium-range Weather Forecasts operational analysis data. J. Geophys. Res., 111, B02406, doi:10.1029/2005JB003629.Google Scholar
  4. Boy, J.-P., P. Gegout, and J. Hinderer (2002). Reduction of surface gravity data from global atmospheric pressure loading. Geophys. J. Int., 149, 534–545.CrossRefGoogle Scholar
  5. Boy, J.-P. and J. Hinderer (2006). Study of the seasonal gravity signal in superconducting gravimeter data. J. Geodyn, 41, 227–233.CrossRefGoogle Scholar
  6. Boy, J.-P. and F. Lyard (2008). High-Frequency non-tidal ocean loading effects on surface gravity measurements. Geophys. J. Int., 175, 35–45.CrossRefGoogle Scholar
  7. Carrère, L. and F. Lyard (2003). Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing – comparisons with observations. Geophys. Res. Lett., 30(6), 1275, doi: 10.1029/2002GL016473.Google Scholar
  8. Gegout P. and Cazenave A. (1991). Geodynamics parameters derived from 7 years of laser data on Lageos. Geophys. Res. Lett., 18, 1739–1742.CrossRefGoogle Scholar
  9. Gross, R.S., I. Fukumori, D. Menemenlis, and P. Gegout (2004). Atmospheric and oceanic excitation of length-of-day variations during 1980–2000. J. Geophys. Res., 109, B01406, doi: 10.1029/2003JB002432.Google Scholar
  10. Herring, T.A. (2008). GLOBK: Global Kalman filter VLBI and GPS Analysis Program version 10.33. Massachusetts Institute of Technology (MIT), Cambridge.Google Scholar
  11. King, R. W. and Bock, Y. (2008). Documentation for the GAMIT analysis software, release 10.33. Massachusetts Institute of Technology (MIT), Cambridge.Google Scholar
  12. Petrov, L. and Boy, J.-P. (2004). Study of the atmospheric pressure loading signal in VLBI observations. J. Geophys. Res., 109, B03405, doi: 10.1029/2003JB002500.Google Scholar
  13. Ray J., Z. Altamimi, X. Collilieux, T. van Dam (2008). Anomalous harmonics in the spectra of GPS position estimates. GPS Solut. 12, 55–64, DOI 10.1007/s10291-007-0067-7.Google Scholar
  14. Rodell, M., P.R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J.K. Entin, J.P. Walker, D. Lohmann, and D. Toll (2004). The global land data assimilation system. Bull. Amer. Meteor. Soc., 85(3), 381–394.CrossRefGoogle Scholar
  15. Tregoning, P. and T.M. van Dam (2005). Atmospheric pressure loading corrections applied to GPS data at the observation level. Geophys. Res. Lett., 32, L22310, doi:10.1029/2005GL024104.Google Scholar
  16. van Dam, T., H.-P. Plag, O. Francis, and P. Gegout. (2003). GGFC Special Bureau for Loading: Current status and Plans, in Proceedings of the IERS Workshop on Combination Research and Global Geophysical Fluids, Bavarian Academy of Sciences, Munich, Germany, 18–21 November 2002, IERS Tech. Note 30, edited by B. Richter, W. Schwegmann, and W. R. Dick, pp. 180–198, Int. Earth Rotation Serv., Paris.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • P. Gegout
    • 1
  • J. -P. Boy
    • 1
  • J. Hinderer
    • 2
  • G. Ferhat
    • 1
    • 3
  1. 1.Institut de Physique du Globe de StrasbourgStrasbourgFrance
  2. 2.École et Observatoire des Sciences de la Terre (EOST)StrasbourgFrance
  3. 3.INSA de StrasbourgStrasbourgFrance

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