Possible enhancement of Earth’s polar motion predictions using a wavelet-based preprocessing procedure

Abstract

Earth’s polar motion predictions are essential in near real-time applications including spacecraft navigation and satellite orbit determinations and are also important for geophysics studies. It has previously been demonstrated that the basic problem in predicting a polar motion time-series is to treat separately its low- and high-frequency components. In this paper, this problem is solved by the combination of wavelet transform with the least-squares (LS) extrapolation and autoregressive (AR) method. Wavelet transform is first employed to separate the deterministic low-frequency components including the Chandler and annual wobbles and irregular short-period high-frequency components of a polar motion time-series. Then the deterministic parts are predicted using LS extrapolation of models for the linear trend, Chandler and annual wobbles, while the remaining irregular parts together with LS residuals are forecasted using the AR stochastic method. The polar motion predictions are computed as a combination of the LS extrapolation and AR prediction. The results show that the polar motion predictions up to 360 days in the future obtained by this approach can be remarkably enhanced due to the use of the wavelet-based preprocessing procedure. We conclude that the separate treatment of low- and high-frequency components is of use to enhance polar motion predictions.