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LEI Yu, ZHAO Danning. Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20200007
Citation: LEI Yu, ZHAO Danning. Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20200007

Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction

doi: 10.13203/j.whugis20200007
Funds:

the Scientific Research Program of Shaanxi Natural Science Foundation, No. 2020JQ893

  • Received Date: 2020-10-09
    Available Online: 2021-05-07
  • The priori studies have revealed that the Chandler and annual wobbles (CW and AW) in polar motion (PM) are unstable over time. In order to further enhance the prediction accuracy of polar motion (PM), a harmonic model for the linear trend, CW and AW with time-varying coefficients is developed in this paper. The developed model takes into account the variations in both amplitudes and phases of the CW and AW. The PM predictions are calculated by means of two schemes to valid the effectives of the developed model:the least-squares extrapolation of the variable harmonic model for the linear trend, time-varying CW and AW in combination with the autoregressive technique, denoted as VLS+AR, and the combination of the least-squares extrapolation of the invariable harmonic model and AR filtering, referred to LS+AR. The results show that the accuracies of the PM predictions obtained by the VLS+AR are better than those generated by the LS+AR, especially for medium- and long-term predictions.
  • [1] Gambis D, Luzum B. Earth Rotation Monitoring, UT1 Determination and Prediction[J]. Metrologia, 2011, 48(4):165-170.
    [2] Bizouard C, Seoane L. Atmospheric and Oceanic Forcing of Rapid Polar Motion[J]. Journal of Geodesy, 2010, 84(1):19-30.
    [3] Dill R, Dobslwa H, Thomas M. Improved 90-day Earth Orientation Predictions from Angular Momentum Forecasts of Atmosphere, Ocean, and Terrestrial Hydrosphere[J]. Journal of Geodesy, 2019, 93(3):287-295.
    [4] Xu X Q, Zhou Y H. EOP Prediction Using Least Square Fitting and Autoregressive Filter over Optimized Data Intervals[J]. Advances in Space Research, 2015, 56(10):2248-2253.
    [5] Schuh H, Ulrich M, Egger D, et al. Prediction of Earth Orientation Parameters by Artificial Neural Networks[J]. Journal of Geodesy, 2002, 76(5):247-258.
    [6] Liao D C, Wang Q J, Zhou Y H, et al. Long-term Prediction of the Earth Orientation Parameters by the Artificial Neural Network Technique[J]. Journal of Geodynamics, 2012, 62:87-92.
    [7] Akyilmaz O, Kutterer H, Shum C K, et al. Fuzzy-wavelet Based Prediction of Earth Rotation Parameters[J]. Applied Soft Computing, 2011, 11(1):837-841.
    [8] Kalarus M, Schuh H, Kosek W, et al. Achievements of the Earth Orientation Parameters Prediction Comparison Campaign[J]. Journal of Geodesy, 2010, 84(10):587-596.
    [9] Schuh H, Nagel S, Seitz T. Linear Drift and Periodic Variations Observed in Long Time Series of Polar Motion[J]. Journal of Geodesy, 2001, 74(10):701-710.
    [10] Guo J Y, Han Y B. Seasonal and Inter-annual Variations of Length of Day and Polar Motion Observed by SLR in 1993-2006[J]. Chinese Science Bulletin, 2009, 54(1):46-52.
    [11] Guo J Y, Li Y B, Dai C L, Shum C K. A Technique to Improve the Accuracy of Earth Orientation Prediction Algorithms Based on Least Squares Extrapolation[J]. Journal of Geodynamics, 2013(70):36-48.
    [12] Brockwell P J, Davis R A. Introduction to Time Series and Forecasting[M]. New York:Springer, 1996.
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Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction

doi: 10.13203/j.whugis20200007
Funds:

the Scientific Research Program of Shaanxi Natural Science Foundation, No. 2020JQ893

Abstract: The priori studies have revealed that the Chandler and annual wobbles (CW and AW) in polar motion (PM) are unstable over time. In order to further enhance the prediction accuracy of polar motion (PM), a harmonic model for the linear trend, CW and AW with time-varying coefficients is developed in this paper. The developed model takes into account the variations in both amplitudes and phases of the CW and AW. The PM predictions are calculated by means of two schemes to valid the effectives of the developed model:the least-squares extrapolation of the variable harmonic model for the linear trend, time-varying CW and AW in combination with the autoregressive technique, denoted as VLS+AR, and the combination of the least-squares extrapolation of the invariable harmonic model and AR filtering, referred to LS+AR. The results show that the accuracies of the PM predictions obtained by the VLS+AR are better than those generated by the LS+AR, especially for medium- and long-term predictions.

LEI Yu, ZHAO Danning. Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20200007
Citation: LEI Yu, ZHAO Danning. Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20200007
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