Investigations and Experiments of Variances Filtering Technology in the Ensemble Data Assimilation

Abstract

AbstractAn experimental Ensemble Data Assimilation (YH‐EDA) system has been built with 10 ensemble members based on the operational YH4DVAR system. The system can provide flow‐dependent background‐error variances, which are superior to the operational ones both in structure and magnitude. However, the finite ensemble size implies a detrimental sampling noise for the variances estimation. To solve this problem, a spectral filtering technique is implemented to formulate a low‐passing filter. Taking into account the typical horizontal length scales of noise and signal, the filter can eliminate the sampling noise while extracting the signal of interest. In the ensemble variance filtering experimentations of the 9th typhoon “Jebi” in 2013, our results show that the 10‐members' filtered variances exhibit better performance than 30‐members's estimation. The successful implementation of the spectral filtering reduces the requirement of large ensemble size of Ensemble Data Assimilation system, which indicates that spectral filtering has become an important and necessary technology in EDA operational implementation.