Physics-Informed Neural Networks as Differentiable Surrogates for 4D-Variational Data Assimilation
Biogeochemical forecasting requires state estimation methods that accommodate sparse observations, nonlinear dynamics, and discontinuous ecological processes. Four-dimensional variational data assimilation (4D-Var) addresses this challenge but depends on tangent-linear and adjoint models that are costly to derive and m...