Articles | Volume 13, issue 8
https://doi.org/10.5194/gmd-13-3607-2020
https://doi.org/10.5194/gmd-13-3607-2020
Development and technical paper
 | 
19 Aug 2020
Development and technical paper |  | 19 Aug 2020

An offline framework for high-dimensional ensemble Kalman filters to reduce the time to solution

Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet

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Latest update: 21 Jul 2024
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Short summary
This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.