Achievements of the Earth orientation parameters prediction comparison campaign
Precise transformations between the international celestial and terrestrial reference frames are needed for many advanced geodetic and astronomical tasks including positioning and navigation on Earth and in space. To perform this transformation at the time of observation, that is for real-time appli...
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Published in: | Journal of geodesy Vol. 84; no. 10; pp. 587 - 596 |
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Main Authors: | , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Berlin/Heidelberg
Springer-Verlag
01-10-2010
Springer Nature B.V Springer Verlag |
Subjects: | |
Online Access: | Get full text |
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Summary: | Precise transformations between the international celestial and terrestrial reference frames are needed for many advanced geodetic and astronomical tasks including positioning and navigation on Earth and in space. To perform this transformation at the time of observation, that is for real-time applications, accurate predictions of the Earth orientation parameters (EOP) are needed. The Earth orientation parameters prediction comparison campaign (EOP PCC) that started in October 2005 was organized for the purpose of assessing the accuracy of EOP predictions. This paper summarizes the results of the EOP PCC after nearly two and a half years of operational activity. The ultra short-term (predictions to 10 days into the future), short-term (30 days), and medium-term (500 days) EOP predictions submitted by the participants were evaluated by the same statistical technique based on the mean absolute prediction error using the IERS EOP 05 C04 series as a reference. A combined series of EOP predictions computed as a weighted mean of all submissions available at a given prediction epoch was also evaluated. The combined series is shown to perform very well, as do some of the individual series, especially those using atmospheric angular momentum forecasts. A main conclusion of the EOP PCC is that no single prediction technique performs the best for all EOP components and all prediction intervals. |
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ISSN: | 0949-7714 1432-1394 |
DOI: | 10.1007/s00190-010-0387-1 |