Interpretable structural model error discovery from sparse assimilation increments using spectral bias‐reduced neural networks: A quasi‐geostrophic turbulence test …
R Mojgani, A Chattopadhyay… - Journal of Advances in …, 2024 - Wiley Online Library
Earth system models suffer from various structural and parametric errors in their
representation of nonlinear, multi‐scale processes, leading to uncertainties in their long …
representation of nonlinear, multi‐scale processes, leading to uncertainties in their long …
[PDF][PDF] xesn: Echo state networks powered by Xarray and Dask
Xesn is a Python package that allows scientists to easily design Echo State Networks
(ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture …
(ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture …
Dynamic-Mode Decomposition of Geostrophically Balanced Motions from SWOT Altimetry
The decomposition of oceanic flow into its balanced and unbalanced motions carries
theoretical and practical significance for the oceanographic community. These two motions …
theoretical and practical significance for the oceanographic community. These two motions …
Nonlinear ensemble filtering with diffusion models: Application to the surface quasi-geostrophic dynamics
The intersection between classical data assimilation methods and novel machine learning
techniques has attracted significant interest in recent years. Here we explore another …
techniques has attracted significant interest in recent years. Here we explore another …