Abstract
This paper presents normal time–frequency transform (NTFT) application in harmonic/quasi-harmonic signal prediction. Particularly, we use the normal wavelet transform (a special NTFT) to make long-term polar motion prediction. Instantaneous frequency, phase and amplitude of Chandler wobble, prograde and retrograde annual wobbles of Earth’s polar motion are analyzed via the NTFT. Results show that the three main wobbles can be treated as quasi-harmonic processes. Current instantaneous harmonic information of the three wobbles can be acquired by the NTFT that has a kernel function constructed with a normal half-window function. Based on this information, we make the polar motion predictions with lead times of 1 year and 5 years. Results show that our prediction skills are very good with long lead time. An abnormality in the predictions occurs during the second half of 2005 and first half of 2006. Finally, we provide the future (starting from 2013) polar motion predictions with 1- and 5-year leads. These predictions will be used to verify the effectiveness of the method proposed in this paper.
Highlights
Polar motion is Earth’s rotation axis movement with respect to its crust
The polar motion (PMx and PMy) time series covering the period from January 1, 1962 to December 31, 2012 is downloaded from the website of International Earth Rotation and Reference Systems Service (IERS) Earth Orientation Center
We explain how the normal time–frequency transform (NTFT) can be used for time–frequency analysis and long-term prediction
Summary
Polar motion is Earth’s rotation axis movement with respect to its crust. It is a significant component of Earth orientation parameters (EOPs). Various techniques have been developed and applied to the polar motion prediction, including those presented by Petrov et al (1995), Kosek et al (1998), Kosek (2002), Schuh et al (2002), Akulenko et al (2002), Akyilmaz and Kutterer (2004), Akyilmaz et al (2011), and Liao et al (2012) These methods either estimate the parameters of harmonic functions and extrapolate them into the future or use stochastic models such as autoregressive integrated moving average processes and Kalman filter with atmospheric angular momentum forecast. This study uses the time– frequency analysis method (i.e., the NTFT) to predict the polar motion. In order to obtain the instantaneous frequency, amplitude and phase at the current time, half-window can be used to construct the kernel function of the NTFT.
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