New Tools for Decomposition of Sea Floor Pressure Data - A Practical Comparison of Modern and Classical Approaches

TL;DR

This paper compares modern and classical methods for decomposing long-term sea floor pressure data, highlighting that Sparse Decomposition generally outperforms others despite efficiency trade-offs.

Contribution

It introduces and evaluates Empirical Mode Decomposition and Sparse Decomposition methods for geoscience data analysis, providing a practical comparison with traditional techniques.

Findings

Sparse Decomposition performed best overall

Classical Fourier and Wavelet methods often fail with complex data

No single method fulfills all analysis requirements

Abstract

In recent years more and more long-term broadband data sets are collected in geosciences. Therefore there is an urgent need of algorithms which semi-automatically analyse and decompose these data into separate periods which are associated with different processes. Often Fourier and Wavelet Transform is used to decompose the data into short and long period effects but these fail often because of their simplicity. In this paper we investigate the novel approaches Empircial Mode Decomposition and Sparse Decomposition for long-term sea floor pressure data analysis and compare them with the classical ones. Our results indicate that none of the methods fulfils all the requirements but Sparse Decomposition performed best except for computing efficiency.