Optimal Inversion of Open Boundary Conditions Using BPNN Data-Driven Model

One of major difficulties with numerical tidal models is accurate inversion of open boundary conditions. A data-driven model based on artificial neural network is developed to retrieve open boundary values. All training data are calculated by numerical tidal model, so the tidal physics are not disturbed. The basic idea is to find out the relationship between open boundary values and the values of interior tidal stations. Case testes are carried out with a real ocean bay named Liaodong bay, part of the Bohai Sea, China. One of major tidal constituents, M2 is considered. Case studies show that the inversion method for open boundary conditions can make a more satisfactory inversion for a practical problem.