A CNN subgrid model trained on one quasi-geostrophic regime underestimates out-of-distribution activation and output spectra, and retraining only the first hidden layer with target data corrects the spectral bias.
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Fourier analysis of the physics of transfer learning for data-driven subgrid-scale models of ocean turbulence
A CNN subgrid model trained on one quasi-geostrophic regime underestimates out-of-distribution activation and output spectra, and retraining only the first hidden layer with target data corrects the spectral bias.