Articles | Volume 24, issue 3
https://doi.org/10.5194/npg-24-329-2017
https://doi.org/10.5194/npg-24-329-2017
Research article
 | 
03 Jul 2017
Research article |  | 03 Jul 2017

An estimate of the inflation factor and analysis sensitivity in the ensemble Kalman filter

Guocan Wu and Xiaogu Zheng

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Short summary
The accuracy of the assimilation results crucially relies on the estimate accuracy of forecast error covariance matrix in data assimilation. Ensemble Kalman filter estimates the forecast error covariance matrix as the sampling covariance matrix of the ensemble forecast states, which need to be further inflated. The experiment results on the Lorenz-96 model show that the analysis error is reduced and the analysis sensitivity to observations is improved using the proposed inflation technique.