A new polar motion prediction method combined with the difference between polar motion series

After the first Earth Orientation Parameters Prediction Comparison Campaign (1st EOP PCC), the traditional method using least-squares extrapolation and autoregressive (LS + AR) models was considered as one of the polar motion prediction methods with higher accuracy. The traditional method predicts individual polar motion series separately, which has a single input data and limited improvement in prediction accuracy. To address this problem, this paper proposes a new method for predicting polar motion by combining the difference between polar motion series. The X, Y, and Y-X series were predicted separately using LS + AR models. Then, the new forecast value of X series is obtained by combining the forecast value of Y series with that of Y-X series; the new forecast value of Y series is obtained by combining the forecast value of X series with that of Y-X series. The hindcast experimental comparison results from January 1, 2011 to April 4, 2021 show that the new method achieves a maximum improvement of 12.95% and 14.96% over the traditional method in the X and Y directions, respectively. The new method has obvious advantages compared with the differential method. This study tests the stability and superiority of the new method and provides a new idea for the research of polar motion prediction.