El Ni\~No Southern Oscillation

The El Niño-Southern Oscillation (ENSO) is a climate pattern characterized by fluctuating sea surface temperatures in the tropical Pacific Ocean, impacting global weather patterns. Current research focuses on improving ENSO prediction accuracy and understanding its complex dynamics using advanced machine learning models, such as convolutional neural networks, transformers, and recurrent neural networks, which are showing improved skill in forecasting beyond existing methods. These advancements are leading to better predictions of ENSO events, including the ability to distinguish between different types of El Niño and La Niña events and their varying impacts, thereby enhancing our capacity for climate forecasting and disaster preparedness. Furthermore, explainable AI techniques are providing insights into the physical mechanisms driving ENSO and its teleconnections, improving our understanding of its global influence.