Ensemble Transform Kalman Incremental Smoother and Its Application to Data Assimilation and Prediction

Ensemble Transform Kalman Incremental Smoother and Its Application to Data Assimilation and Prediction

The analysis correction made by data assimilation (DA) can introduce model shock or artificial signal, leading to degradation in forecast. In this study, we propose an Ensemble Transform Kalman Incremental Smoother (ETKIS) as an incremental update solution for ETKF-based algorithms. ETKIS not only h...

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Bibliographic Details
Main Authors: Zhe-Hui Lin, Shu-Chih Yang, Eugenia Kalnay
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Applied Mathematics and Statistics
Subjects:
data assimilation
numerical weather prediction
ensemble Kalman filter
incremental update method
nonlinear dynamics
Online Access:https://www.frontiersin.org/articles/10.3389/fams.2021.687743/full

Internet

https://www.frontiersin.org/articles/10.3389/fams.2021.687743/full

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