Parallel Implementation of the Ensemble Empirical Mode Decomposition and Its Application for Earth Science Data Analysis

To efficiently perform multiscale analysis of high-resolution, global, multiple-dimensional datasets, the authors have deployed the parallel ensemble empirical mode decomposition (PEEMD) package by implementing three-level parallelism into the ensemble empirical mode decomposition (EMD), achieving a scaled performance of 5,000 cores. In this study, they discuss the implementation of the PEEMD and its application for the analysis of Earth science data, including the solution of the Lorenz model, an idealized terrain-induced flow, and Hurricane Sandy.