Variational Implicit Normal-Mode Initialization for a Multilevel Model

Abstract

Recent studies have demonstrated that variational nonlinear normal-mode initialization can be efficiently implemented in the context of shallow-water models, provided one uses a physical space formulation. The implicit nonlinear normal-mode initialization (INMI) technique provides essentially the same balancing benefit as standard ?explicit? nonlinear NMI but does not require the explicit computation of the linear free modes of the model. This allows variational initialization with arbitrary horizontal variation of the weights that specify the changes to the analyzed fields during initialization. As a consequence, the variational extension of INMI allows more flexibility to control the relative adjustment of mass and wind fields over data-rich and data-poor regions. The purpose of this paper is to demonstrate the feasibility of variational implicit normal-mode initialization (VINMI) for multilevel models. This new scheme is illustrated on the presently operational Canadian baroclinic regional finite-element (RFE) model. It is shown that the VINMI scheme efficiently controls the relative magnitude of the changes to the analyzed mass and wind fields during the balancing (initialization) processes. A comparison is also made of the impact of the VINMI scheme versus that of the presently operational unconstrained version of the initialization scheme (INMI). Future development and applications of the method are discussed at the end of the paper.