AUTHOR=Dijkstra Henk A. , Petersik Paul , Hernández-García Emilio , López Cristóbal TITLE=The Application of Machine Learning Techniques to Improve El Niño Prediction Skill JOURNAL=Frontiers in Physics VOLUME=7 YEAR=2019 URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2019.00153 DOI=10.3389/fphy.2019.00153 ISSN=2296-424X ABSTRACT=

We review prediction efforts of El Niño events in the tropical Pacific with particular focus on using modern machine learning (ML) methods based on artificial neural networks. With current classical prediction methods using both statistical and dynamical models, the skill decreases substantially for lead times larger than about 6 months. Initial ML results have shown enhanced skill for lead times larger than 12 months. The search for optimal attributes in these methods is described, in particular those derived from complex network approaches, and a critical outlook on further developments is given.