Autocovariance prediction of complex-valued polar motion time series Original Research Article

Autocovariance prediction formulae of complex-valued time series are derived and applied to predict pole coordinate data. The pole coordinate data are transformed into the polar motion radius and angular distance and afterwards their predictions are computed. The predictions of the radius and angular distance are transformed into the pole coordinate predictions. The radius and its prediction refer to the 6-year running mean of polar motion data and its autocovariance predictions. The prediction errors depend mostly on the starting epochs of prediction due to irregular variations of polar motion. The mean prediction errors of x and y pole coordinate data are slightly greater than those computed by the current method of polar motion prediction carried out in the IERS Sub-Bureau for Rapid Service and Prediction.