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

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Part of the book series: International Association of Geodesy Symposia ((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.

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References

  • Abarca del Rio A, Gambis D, Salstein DA (2000) Interannual signals in length of day and atmospheric angular momentum. Annales Geophysicae 18:347–364

    Article  Google Scholar 

  • Akyilmaz O, Kutt erer H (2004) Prediction of Earth rotation parameters by fuzzy inference systems. J Geodes 78:82–93

    Google Scholar 

  • Freedman AP, Steppe JA, Dickey JO, Eubanks TM, Sung LY (1994) The short-term prediction of universal time and length of day using atmospheric angular momentum. J Geophys Res 99(B4):6981–6996

    Google Scholar 

  • Gross RS, Eubanks TM, Steppe JA, Freedman AP, Dickey JO, Runge TF (1998) A Kalman filter-based approach to combining independent Earth-orientation series. J Geodes 72:215–235

    Article  Google Scholar 

  • Gross RS, Marcus SL, Eubanks TM, Dickey JO, Keppenne CL (1996) Detection of an ENSO signal in seasonal length-of-day variations. Geophys Res Lett 23:3373–3376

    Article  Google Scholar 

  • Johnson T, Luzum BJ, Ray JR (2005) Improved near-term Earth rotation predictions using atmospheric angular momentum analysis and forecasts. J Geodyn 39:209–221

    Article  Google Scholar 

  • Kalarus M, Kosek W (2004) Prediction of Earth orientation parameters by artificial neural networks. Artificial Satellites 39:175–184

    Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds B, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471

    Article  Google Scholar 

  • Kosek W (1992) Short periodic autoregressive prediction of the Earth rotation parameters. Artificial Satellites 27:9–17

    Google Scholar 

  • Kosek W, Kalarus M, Johnson TJ, Wooden WH, McCarthy DD, Popiński W(2005) A comparison of LOD and UT1-UTC forecasts by different combination prediction techniques. Artificial Satellites 40:119–125

    Google Scholar 

  • Kosek W, McCarthy DD, Luzum BJ (1998) Possible improvement of Earth orientation forecast using autocovariance prediction procedures. J Geodes 72:189–199

    Article  Google Scholar 

  • McCarthy DD, Petit G (eds) (2004) IERS Conventions 2003 IERS Technical Note No. 32, Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main

    Google Scholar 

  • Neumaier A, Schneider T (2001) Estimation of parameters and eigenmodes of multivariate autoregressive models. ACM Trans Math Software 27:27–57

    Article  Google Scholar 

  • Niedzielski T, Kosek W (2008) Prediction of UT1-UTC, LOD and AAM χ3 by combination of least-squares and multivariate stochastic methods. J Geodes 82:83–92

    Article  Google Scholar 

  • Niedzielski T, Sen AK, Kosek W (2009) On the probability distribution of Earth orientation parameters data. Artficial Satellites 44:33–41

    Article  Google Scholar 

  • Rosen RD, Salstein DA, Eubanks TM, Dickey JO, Steppe JA (1984) An El Niño signal in atmoshperic angular momentum and Earth rotation. Science 27:411–414

    Article  Google Scholar 

  • Schuh H, Ulrich M, Egger D, Müller J, Schwegmann W (2002) Prediction of Earth orientation parameters by artificial neural networks. J Geodes 76:247–258

    Article  Google Scholar 

  • Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464

    Article  Google Scholar 

  • Zhao J, Han Y (2008) The relationship between the interannual variation of Earth’s rotation and El Niño events. Pure Appl Geophys 165:1435–1443

    Article  Google Scholar 

Download references

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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Correspondence to Tomasz Niedzielski .

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Niedzielski, T., Kosek, W. (2012). Prediction Analysis of UT1-UTC Time Series by Combination of the Least-Squares and Multivariate Autoregressive Method. In: Sneeuw, N., Novák, P., Crespi, M., Sansò, F. (eds) VII Hotine-Marussi Symposium on Mathematical Geodesy. International Association of Geodesy Symposia, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22078-4_23

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