Title: Classification of ENSO phases using topological data analysis
Authors: Adam Jaeger - Wichita State University (United States) [presenting]
Abstract: The El Nino Southern Oscillation (ENSO) is one of the most powerful climate phenomena that can change global air circulation, affecting temperature and rainfall around the planet. Classification of these phases has traditionally relied on average sea surface temperatures in the equatorial Pacific without consideration of any structural information. Topological data analysis(TDA) is an innovative approach which focuses on a data set's ``shape'' or topological structures such as loops, holes, and voids. We used TDA to describe the homology groups of the two-dimensional function determined by sea surface temperatures of the tropical Pacific Ocean and utilize these summaries as a potential alternative to the prediction of ENSO phase.