Building Tangent‐Linear and Adjoint Models for Data Assimilation With Neural Networks

Building Tangent‐Linear and Adjoint Models for Data Assimilation With Neural Networks

Abstract We assess the ability of neural network emulators of physical parametrization schemes in numerical weather prediction models to aid in the construction of linearized models required by four‐dimensional variational (4D‐Var) data assimilation. Neural networks can be differentiated trivially,...

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Bibliographic Details
Main Authors: Sam Hatfield, Matthew Chantry, Peter Dueben, Philippe Lopez, Alan Geer, Tim Palmer
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2021-09-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
neural network
data assimilation
tangent‐linear
adjoint
Online Access:https://doi.org/10.1029/2021MS002521

Internet

https://doi.org/10.1029/2021MS002521

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