Search Results

1 - 10 of 123 items :

  • Earth orientation x
Clear All
Future of Earth Orientation Predictions

Future of Earth Orientation Predictions

Earth orientation prediction has undergone a number of changes over the last few decades in response to changing conditions in the Earth orientation parameter user community. However, considering the recent pace of change, it is likely that the rate at which innovations are introduced into the prediction process will increase. Potential drivers for change are discussed and possible directions for change are outlined.

Open access
Employing Combination Procedures to Short-Time Eop Prediction

References Kalarus M., Schuh H., Kosek W., Akyilmaz O., Bizouard Ch., Gambis D., Gross R., Kumakshev S., Kutterer H., Mendes Cerveira P. J., Pasynok S., Zotov L., Achievements of the Earth orientation parameters prediction comparison campaign. J. Geodesy , Vol. 84, 587-596. Luzum B., Wooden W., McCarthy D., Schuh H., Kosek W., Kalarus M., (2007). Ensemble Prediction for Earth Orientation Parameters, Geophysical Research Abstracts , Vol. 9, EGU2007-A-04315. Malkin Z. (2009

Open access
On the Probability Distribution of Earth Orientation Parameters Data

) Transformation to Normality of the Null Distribution of G1, Biometrika , 57, 679-681. Eubanks T.M. (1993) Variations in the Orientation of the Earth, Contributions of Space Geodesy to Geodynamics: Earth Dynamics , Smith D.E., Turcotte D.L. (eds), AGU Geodynamics Series, 1-54. Freedman A.P., Steppe J.A., Dickey J.O., Eubanks T.M., Sung L.Y. (1994) The shortterm prediction of universal time and length of day using atmospheric angular momentum, Journal of Geophysical Research , 99 (B4), 6981

Open access
Analysis of Pole Coordinate Data Predictions in the Earth Orientation Parameters Combination of Prediction Pilot Project

References Bizouard C and D. Gambis, 2009, The combined solution C04 for Earth Orientation Parameters, recent improvements, Springer Verlag series, Series International Association of Geodesy Symposia, Vol. 134 Drewes, Hermann (Ed.), 265-270. Freedman, A. P., J. A. Steppe, J. O. Dickey, T. M. Eubanks, and L.-Y. Sung, 1994, The short-term prediction of universal time and length of day using atmospheric angular momentum, J. Geophys. Res., 99, 6981-6996. Gambis D., 2004, Monitoring

Open access
Scheduling And Simulation Of VLBI Measurements For The Determination Of Earth Orientation Parameters

Geodetic VLBI System . Nilsson, Tobias, Robert Heinkelmann, Maria Karbon, Virginia Raposo-Pulido, Benedikt Soja, and Harald Schuh. 2014. “Earth Orientation Parameters Estimated from VLBI during the CONT11 Campaign.” Journal of Geodesy 88 (5): 491–502. doi:10.1007/s00190-014-0700-5. Petrachenko, W. T., H. Schuh, A. E. Niell, D. Behrend, and B. E. Corey. 2010. “VLBI2010: Next Generation VLBI System for Geodesy and Astrometry.” American Geophysical Union . http://adsabs.harvard.edu/abs/2010AGUFM.G14B..06P . Petrachenko, B., A. Niell, D. Behrend, B

Open access
Testing impact of the strategy of VLBI data analysis on the estimation of Earth Orientation Parameters and station coordinates

., Heinkelmann, R., Karbon, M., Raposo-Pulido, V., Soja, B., & Schuh, H. (2014). Earth orientation parameters estimated from VLBI during the CONT11 campaign. Journal of Geodesy, 88(5), 491-502. doi: 10.1007/s00190-014-0700-5 Petit, G., & Luzum, B. (Eds.). (2010). IERS Conventions (2010). IERS Technical Note 36, Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main, Germany. Petrachenko, W., Behrend, D., Hase, H., Ma, C., Niell, A., Schuh, H., & Whitney, A. (2013). The VLBI2010 Global Observing System (VGOS). In EGU General

Open access
Extreme Learning Machine for the Predictions of Length of Day

., Eubanks TM., Steppe JA., Freedman AP., Dickey JO. and Runge TF. (1998) A Kalman-filter-based approach to combining independent Earth-orientation series. Journal of Geodesy, Vol. 72, No. 4, 1998, pp. 215-235. Huang GB., Zhu QY. and Siew CK. (2004) Extreme learning machine: a new learning scheme of feedforward neural networks. Proceedings of 2004 IEEE International Joint Conference on Neural Networks, Budapest, Hungary, pp. 985-990. Huang GB., Zhu QY. and Siew CK. (2006) Extreme learning machine: theory and applications, Neurocomputing, Vol. 70, No. 1-3, 2006, pp. 489

Open access
UT1 Prediction Based on Long-Time Series Analysis

References Akulenko L. D., Kumakshev S. A., Markov Yu.G., and Rykhlova L. V. (2002). Forecasting the Polar Motions of the Deformable Earth. Astronomy Reports , Vol. 46, 858-865. IERS (2001-2009). IERS Annual Reports 2000-2007 , Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main. Lambeck K. (1980). The Earth's Variable Rotation: Geophysical causes and consequences. Cambridge Univ. Press. Luzum B, Nothnagel A. (2010). Improved UT1

Open access
Complex Demodulation in Monitoring Earth Rotation by VLBI: Testing the Algorithm by Analysis of Long Periodic EOP Components

REFERENCES Artz, T., Tesmer née Böckmann, S., Nothnagel, A. (2011) Assessment of periodic subdiurnal Earth rotation variations at tidal frequencies through transformation of VLBI normal equation systems, Journal of Geodesy , Vol. 86(9), 565-584. Böhm J., Böhm S., Nilsson T., Pany A., Plank L., Spicakova H., Teke, K., Schuh, H. (2012a) The new Vienna VLBI Software VieVS, Proc. of IAG Scientific Assembly 2009, International Association of Geodesy Symposia Series , Vol. 136, 1007-1011. Böhm S., Brzeziński A., Schuh H. (2012b) Complex demodulation

Open access
Ultra-Rapid DUT1-Observations with E-VLBI

and future prospects, Journal of Geodesy , Vol. 81(68):479, doi:10.1007/s00190-006-0131-z. Sekido M., Takiguchi H., Koyama Y., Kondo T., Haas R., Wagner J., Ritakari J., Kurihara S., Kokado K. (2008) Ultra-rapid UT1 measurements by e-VLBI, Earth Planets and Space , Vol. 60, 865-870.

Open access