Towards Optimally Weighted Physics-Informed Neural Networks in Ocean Modelling

Understand

The carbon pump of the world's ocean plays a vital role in the biosphere and climate of the earth, urging improved understanding of the functions and influences of the ocean for climate change analyses.

• State-of-the-art techniques are required to develop models that can capture the complexity of ocean currents and temperature flows.
• This work explores the benefits of using physics-informed neural networks (PINNs) for solving partial differential equations related to ocean modeling; such as the Burgers, wave, and advection-diffusion equations.
• We explore the trade-offs of using data vs.