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Prediction Analysis of UT1-UTC Time Series by Combination of the Least-Squares and Multivariate Autoregressive Method

  • Tomasz Niedzielski
  • Wiesław Kosek
Conference paper
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 137)

Abstract

The objective of this paper is to extensively discuss the theory behind the multivariate autoregressive prediction technique used elsewhere for forecasting Universal Time (UT1-UTC) and to characterise its performance depending on input geodetic and geophysical data. This method uses the bivariate time series comprising length-of-day and the axial component of atmospheric angular momentum data and needs to be combined with a least-squares extrapolation of a polynomial-harmonic model. Two daily length-of-day time series, i.e. EOPC04 and EOPC04_05 spanning the time interval from 04.01.1962 to 02.05.2007, are utilised. These time series are corrected for tidal effects following the IERS Conventions model. The data on the axial component of atmospheric angular momentum are processed to gain the 1-day sampling interval and cover the time span listed above. The superior performance of the multivariate autoregressive prediction in comparison to autoregressive forecasting is noticed, in particular during El Niño and La Niña events. However, the accuracy of the multivariate predictions depends on a particular solution of input length-of-day time series. Indeed, for EOPC04-based analysis the multivariate autoregressive predictions are more accurate than for EOPC04_05-based one. This finding can be interpreted as the meaningful influence of smoothing on forecasting performance.

Keywords

Atmospheric angular momentum El Niño/Southern Ociallation Length of day Multivariate autoregressive model Prediction 

Notes

Acknowledgements

The research was financed from the Polish science funds for the period of 2009-2011 provided by Polish Ministry of Science and Higher Education through the grant no. N N526 160136 under leadership of Dr Tomasz Niedzielski at the Space Research Centre of Polish Academy of Sciences. The first author was also supported by EU EuroSITES project. The authors of R 2.9.0 – A Language and Environment and additional packages are acknowledged.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Space Research CentrePolish Academy of SciencesWarsawPoland
  2. 2.Institute of Geography and Regional DevelopmentUniversity of WrocławWrocławPoland
  3. 3.OceanlabUniversity of AberdeenNewburghUK
  4. 4.Department of Land SurveyingUniversity of Agriculture in KrakówKrakówPoland

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