Abstract
<abstract> Based on the review of nonlinear forcing singular vector (NFSV) for dealing with the most disturbing model error and the optimal forcing vector (OFV) for neutralizing model error effect, the NFSV-data assimilation (NFSV-DA) approach was reinterpreted as neutralizing combined effect of model errors and initial errors in predictions. Then the calculation of adjoint-related gradient was derived for solving the NFSV-DA. With the applications to El Ni?o and tropical cyclone predictabilities, the usefulness of the NFSV-DA was emphasized for improving prediction skill of weather and climate. Furthermore, how to further consummate the NFSV-DA was discussed and future works were prospected. It is finally expected that the NFSV-DA becomes operational and greatly increases the prediction level of weather and climate. </abstract>
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