On the Limits of Univariate Deep Learning for Significant Wave Height Forecasting

The study targets significant wave height forecasting in the ocean and geophysics domain. It performs a systematic hyperparameter search over five deep learning architectures and nine context lengths for a single NDBC buoy station. The best-performing configurations are then re-evaluated on a 47-buoy corpus covering 37 years of observations.