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

Tomasz Niedzielski , Wiesław Kosek


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.
Author Tomasz Niedzielski
Tomasz Niedzielski,,
, Wiesław Kosek (FoEEaLS / DoG)
Wiesław Kosek,,
- Department of Geodesy
Publication size in sheets0.5
Book Sneeuw Nico, Novák Pavel, Crespi Mattia, Sansò Fernando (eds.): VII Hotine-Marussi Symposium on mathematical geodesy : proceedings of the Symposium in Rome, 6-10 June, 2009, International Association of Geodesy Symposia, vol. 137, 2012, Springer, ISBN 978-3-642-22077-7, [978-3-642-22078-4], 407 p., DOI:10.1007/978-3-642-22078-4
Keywords in EnglishAtmospheric angular momentum, El Niño/Southern Ociallation, Length of day, Multivariate autoregressive model, Prediction
Languageen angielski
Score (nominal)10
Citation count*3 (2016-03-16)
Additional fields
FinansowanieThe 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.
Share Share

Get link to the record

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Are you sure?