Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model 1LISA, CNRS/INSU UMR7583, Université Paris-Est Créteil et Université Paris Diderot, Institut Pierre Simon Laplace, 94010 Créteil, France
2Institut National de l'Environnement Industriel et des Risques, INERIS, Parc Technologique ALATA-B.P. No. 2, 60550 Verneuil en Halatte, France
3Centre d'Études et de Recherche en Thermique, Environnement et Systèmes EA 3481, Université Paris-Est Créteil, 94010 Créteil, France
Received: 22 Apr 2013 – Published in Geosci. Model Dev. Discuss.: 30 May 2013Abstract. An ensemble Kalman filter (EnKF) has been coupled to the CHIMERE chemical
transport model in order to assimilate ozone ground-based measurements on a
regional scale. The number of ensembles is reduced to 20, which allows for
future operational use of the system for air quality analysis and forecast.
Observation sites of the European ozone monitoring network have been
classified using criteria on ozone temporal variability, based on previous
work by Flemming et al. (2005). This leads to the choice of specific subsets
of suburban, rural and remote sites for data assimilation and for evaluation
of the reference run and the assimilation system. For a 10-day experiment
during an ozone pollution event over Western Europe, data assimilation allows
for a significant improvement in ozone fields: the RMSE is reduced by about a
third with respect to the reference run, and the hourly correlation
coefficient is increased from 0.75 to 0.87. Several sensitivity tests focus
on an a posteriori diagnostic estimation of errors associated with the
background estimate and with the spatial representativeness of observations.
A strong diurnal cycle of both these errors with an amplitude up to a factor
of 2 is made evident. Therefore, the hourly ozone background error and the
observation error variances are corrected online in separate assimilation
experiments. These adjusted background and observational error variances
provide a better uncertainty estimate, as verified by using statistics based
on the reduced centered random variable. Over the studied 10-day period the
overall EnKF performance over evaluation stations is found relatively
unaffected by different formulations of observation and simulation errors,
probably due to the large density of observation sites. From these
sensitivity tests, an optimal configuration was chosen for an assimilation
experiment extended over a three-month summer period. It shows a similarly
good performance as the 10-day experiment.
Revised: 25 Dec 2013 – Accepted: 07 Jan 2014 – Published: 13 Feb 2014
Citation: Gaubert, B., Coman, A., Foret, G., Meleux, F., Ung, A., Rouil, L., Ionescu, A., Candau, Y., and Beekmann, M.: Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model, Geosci. Model Dev., 7, 283-302, doi:10.5194/gmd-7-283-2014, 2014.