Sequential Variational Data Assimilation Algorithms at the Splitting Stages of a Numerical Atmospheric Chemistry Model

摘要

A variational data assimilation algorithm is studied numerically. In situ concentration measurement data are assimilated into transport and transformation model of atmospheric chemistry. The algorithm is based on decomposition and splitting methods with solution of variational data assimilation problems for separate splitting stages. A direct algorithm without iterations is used for the linear transport stage. An iterative gradient algorithm is applied for data assimilation at the nonlinear chemical transformation stage. In a realistic numerical experiment, the contributions of data assimilation algorithms for the different splitting stages are compared.