Ensemble variational data assimilation method based on regional successive analysis scheme

Abstract

The ensemble variational data assimilation method may be subject to significant uncertainties due to the size of forecast ensemble. We found that this problem occurs because the analysis increment of this method is expressed as a linear combination of ensemble perturbation vectors or expansion of the orthogonal basis vectors. Though this method avoids introducing adjoint model while calculating the gradient of object function, the number of physical control variables is much larger than the sample size of forecast ensemble, which causes the assimilation results to be sensitive to the number of ensemble members. For this reason, the regional successive analysis scheme of ensemble variational method is proposed. By this scheme, the ratio between the number of physical control variables in analysis region and the sample size is decreased, so that it is expected that the problem can be solved. The results of numerical experiments using shallow water model show that the regional successive analysis scheme can give better assimilation results than traditional method, and the analysis precision is improved appreciably.