Interpretable Structural Model Error Discovery From Sparse Assimilation Increments Using Spectral Bias‐Reduced Neural Networks: A Quasi‐Geostrophic Turbulence Test Case
Rambod Mojgani,
Ashesh Chattopadhyay,
Pedram Hassanzadeh
Abstract:Earth system models suffer from various structural and parametric errors in their representation of nonlinear, multi‐scale processes, leading to uncertainties in their long‐term projections. The effects of many of these errors (particularly those due to fast physics) can be quantified in short‐term simulations, for example, as differences between the predicted and observed states (analysis increments). With the increase in the availability of high‐quality observations and simulations, learning nudging from the… Show more
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