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

Abstract

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.

Keywords

• Earth rotation parameters
• Polar motion prediction
• LS+AR
• Differences between series
• Mean absolute error