Parallel variational assimilation in aeronomy

Aeronomy studies the chemical composition of upper atmosphere. An important goal in aeronomic research is to collect a data set of satellite observations that provides comprehensive global coverage. Such a data set takes many months of surveying, because appropriate satellites have a very narrow footprint. In the course of the collection, stratospheric winds redistribute the air. It is therefore necessary to complement a purely vertical aeronomic assimilation process with a stratospheric advection model, and also with a chemical kinetic model. Chemical kinetics need to be calibrated from the advected assimilation data set but the time scales involved in the advection are much longer than those of chemical kinetics. Parallel computing can speed up this calibration process significantly. This is currently not possible, because practically all the assimilation methods are inherently sequential. In this article, we study the separability of chemical and dynamic assimilation on parallel computers with a theoretical analysis and simple one dimensional models.