Before revision:  Specifically, the proposed method is formulated as to construct a linear mapping from the prior ensemble to the posterior one, and the linear mapping is computed  by minimizing the Kullback-Leibler divergence between the transformed distribution by the linear mapping and the actual posterior  .
After revision:  Specifically, the proposed method is formulated as to construct a linear mapping from the prior ensemble to the posterior one, and the linear mapping is computed by minimizing the Kullback-Leibler divergence between the transformed distribution by the linear mapping and the actual posterior . A gradient descent scheme is proposed to solve the resulting optimization problem. With numerical examples we demonstrate that the method has competitive performance against existing methods .