Dynamic Wave Trains: A Procedural Approach to Spatially Varying Ocean Synthesis

Abstract Vast oceans are a critical component of many virtual environments. While procedural methods efficiently generate non‐repetitive, large‐scale content with low memory footprints, they usually lack the ability to model in real‐time local interactions with obstacles such as diffraction, reflection and refraction, or spatial variations such as localized wind ripples. We present a procedural ocean synthesis method that addresses this by enabling local control over wave properties including frequency, orientation, velocity and amplitude. By controlling a sum of independent wave trains, our approach seamlessly integrates spatial variations and wavelength‐dependent interactions with the environment. The model allows for high performance parallel evaluation at any scale, enabling the real‐time rendering and filtering of height fields, normal maps and rough BRDF, depending on rendering requirements. Additionally, we leverage the phase information encoded in the model to simulate secondary effects such as foam at a low computational cost.