Interpretable Structural Model Error Discovery From Sparse Assimilation Increments Using Spectral Bias‐Reduced Neural Networks: A Quasi‐Geostrophic Turbulence Test Case

Interpretable Structural Model Error Discovery From Sparse Assimilation Increments Using Spectral Bias‐Reduced Neural Networks: A Quasi‐Geostrophic Turbulence Test Case

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 sh...

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Bibliographic Details
Main Authors: Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2024-03-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
model error
spectral bias
data assimilation
interpolation
neural network
bias
Online Access:https://doi.org/10.1029/2023MS004033

Internet

https://doi.org/10.1029/2023MS004033

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