Lagrangian four-dimensional variational data assimilation of chemical species

Abstract

For the first time, the method of four-dimensional variational data assimilation is applied to the analysis of chemically active trace species. By combining observations with a numerical model to analyse simultaneously several species over a period of a few days, the analysis method is able to exploit information which is not available to conventional analysis techniques. Moreover, effective use can be made of asynoptic observations even for species which have strong diurnal cycles. Synoptic analyses are produced. A Lagrangian approach is adopted, allowing a separation of dynamics and chemistry which considerably reduces the computational expense of the method.