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An ensemble Kalman filter (EnKF) has been coupled to the CHIMERE chemicaltransport model in order to assimilate ozone ground-based measurements on aregional scale. The number of ensembles is reduced to 20, which allows forfuture operational use of the system for air quality analysis and forecast.Observation sites of the European ozone monitoring network have beenclassified using criteria on ozone temporal variability, based on previouswork by Flemming et al. (2005). This leads to the choice of specific subsetsof suburban, rural and remote sites for data assimilation and for evaluationof the reference run and the assimilation system. For a 10-day experimentduring an ozone pollution event over Western Europe, data assimilation allowsfor a significant improvement in ozone fields: the RMSE is reduced by about athird with respect to the reference run, and the hourly correlationcoefficient is increased from 0.75 to 0.87. Several sensitivity tests focuson an a posteriori diagnostic estimation of errors associated with thebackground estimate and with the spatial representativeness of observations.A strong diurnal cycle of both these errors with an amplitude up to a factorof 2 is made evident. Therefore, the hourly ozone background error and theobservation error variances are corrected online in separate assimilationexperiments. These adjusted background and observational error variancesprovide a better uncertainty estimate, as verified by using statistics basedon the reduced centered random variable. Over the studied 10-day period theoverall EnKF performance over evaluation stations is found relativelyunaffected by different formulations of observation and  simulation errors,probably due to the large density of observation sites. From thesesensitivity tests, an optimal configuration was chosen for an assimilationexperiment extended over a three-month summer period. It shows a similarlygood performance as the 10-day experiment

Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model