Articles | Volume 15, issue 23
https://doi.org/10.5194/gmd-15-8869-2022
https://doi.org/10.5194/gmd-15-8869-2022
Model description paper
 | 
12 Dec 2022
Model description paper |  | 12 Dec 2022

A local data assimilation method (Local DA v1.0) and its application in a simulated typhoon case

Shizhang Wang and Xiaoshi Qiao

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Short summary
A local data assimilation scheme (Local DA v1.0) was proposed to leverage the advantage of hybrid covariance, multiscale localization, and parallel computation. The Local DA can perform covariance localization in model space, observation space, or both spaces. The Local DA that used the hybrid covariance and double-space localization produced the lowest analysis and forecast errors among all observing system simulation experiments.