Seasonal forecasting

Seasonal forecasting has traditionally been modeled using complex dynamical models, rather than statistical methods, often called general circulation models (GCMs). However, seasonal variations, such as those due to El Niño/Southern Oscillation (ENSO) and polar vortices, are difficult to predict using traditional methods. ML and deep learning can improve our forecasting of multi-year ENSO events    and polar vortices.