On the Limits of Univariate Deep Learning for Significant Wave Height Forecasting
Fluid Mechanics
This study evaluates five deep learning architectures for univariate significant wave height forecasting using buoy observations. Across a 47-buoy, 37-year evaluation corpus, the model families converge to nearly identical performance, with an between-family standard deviation of 0.0014 square meters.
New See LICENSE file significant wave height forecastingocean buoysdeep learning comparison