Application of Singular Spectrum Analysis in Deep-Ocean Tide Reconstruction and Prediction

Abstract

This study utilized the Singular Spectrum Analysis (SSA) approach to perform time series orthogonalization and demonstrated its use by analyzing vertical tidal acceleration and sea level time series from different deep-ocean locations. This method quantifies astronomical variations by using decomposed vertical tidal acceleration to reconstruct and predict deep-ocean tide. The results show that each decomposed vertical tidal acceleration can be associated with the decomposed sea level having at least 5 astronomical variations. Their associated energies can also be used to diagnose the change of the oceanic tide response to tidal acceleration. Performance evaluation also shows that this method can give comparable reconstruction accuracy and slightly better prediction accuracy compared to the harmonic analysis-based method. It is indicated that the proposed method is accurate enough to be applied in a tsunami detection algorithm. The results also indicate that the proposed method is stable enough to provide unpropagated prediction residuals.