Sea surface height forecasts are influenced by many uncertainties. Traditional statistical methods help make predictions but often rely on assumptions that don’t fully capture the climate system’s complexity. In this paper , Andrew Brettin and co-authors develop a machine learning model that learns a simplified representation of the climate system, improving sea surface height predictions. Their approach outperforms methods that separate data compression and prediction. Additionally, the model highlights key regions where better sea level representation can enhance regional forecasts.