A chemical four-dimensional variational data assimilation system has been developed and applied for the study of an episode with enhanced summerly ozone levels. In this study the optimization parameters are the initial values bf the chemical constituents. The case study focuses on an ozone episode over central Europe during August 1997. The associated observational database consists mainly of surface observations of ozone; and nitrogen oxides, but also a limited number of ozone radiosonde records. The four-dimensional data assimilation algorithm is composed of the chemistry transport model, its adjoint model with the adjoint versions of the Regional Acid Deposition Model (RADM2) chemical mechanism, horizontal and Vertical advection schemes, implicit vertical diffusion, and a limited memory quasi-newton minimization routine. The underlying model of the spatiotemporal data assimilation scheme is the comprehensive mesoscale-alpha EUropean Air pollution Dispersion model (EURAD), which is based on the RADM2 gas phase mechanism. On the basis of a 6 hours data assimilation interval, analyses of the chemical state of the atmosphere were obtained, where the skin is verified in two different ways: (1) improvements of forecasts subsequent to the assimilation procedure, and (2) validation of the analyses with observational data which is withheld from the variational data assimilation algorithm. It is demonstrated that significant improvements are achieved for short-term forecasts including the afternoon ozone peak abundances. The analysis skill is further corroborated by examinations with retained measurement data.
