Improvement of dual-resolution approach for ensemble data assimilation and tests with simulated data. Part II: Assimilation experiments

In this two-part paper, an improved dual-resolution (DR) strategy for ensemble square root filter (EnSRF) algorithm is developed and tested with simulated data. In Part I, the new method is described and examinations are discussed. In this part, the analysis quality of such approach is studied through a set of experiments with assimilation cycles. Firstly, sensitivity experiments are performed to examine aspects related to observation variables and data density. It appears that improved DR method is more perfect than the DR algorithm proposed by Gao et al., especially when more observation variables are involved and observations are more dense. Moreover, such predominance is also significant in consecutive assimilation cycles. In addition, it is feasible that the adjusted relation in the first forecast and assimilation cycle is of applicability in later analysis.