3D‐Var data assimilation using a variational autoencoder

Data assimilation of atmospheric observations traditionally relies on variational and Kalman filter methods. Here, an alternative neural network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three‐dimensional variational (3D‐Var) data assimilation cost function is util...

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Bibliographic Details

Published in:	Quarterly journal of the Royal Meteorological Society Vol. 150; no. 761; pp. 2273 - 2295
Main Authors:	Melinc, Boštjan, Zaplotnik, Žiga
Format:	Journal Article
Language:	English
Published:	Chichester, UK John Wiley & Sons, Ltd 01.04.2024 Wiley Subscription Services, Inc
Subjects:	3D‐Var analysis increments background errors Computation Data assimilation Data collection Kalman filters Lower troposphere machine learning neural network Neural networks Troposphere variational autoencoder
ISSN:	0035-9009, 1477-870X
Online Access:	Get full text
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