Impact of assimilated observations on improving tropospheric ozone simulations

The work aims to evaluate the improvement in the capability of regional models to reproduce the distribution of tropospheric pollutants, using the assimilation of surface chemical observations. In particular, the efficacy in correcting the biases of perturbed emission scenarios was analysed. The study was carried out using the Air Quality Model BOLCHEM coupled with a sequential Optimal Interpolation (OI) routine to perform ozone and nitrogen dioxide assimilation. The OI routine was chosen because it is computationally inexpensive. The work was performed using the Observing System Simulation Experiment (OSSE), which allowed the quantification of assimilation impact, through comparison with a reference state. Different sensitivity tests were carried out in order to identify how assimilation can correct perturbations on O(3), induced by NO(x) emissions biased in both flux intensity and time. This simple assimilation approach provided a substantial improvement in surface O(3). It was found to be more effective to assimilate an O(3) precursor, like NO(2), than O(3) itself, and, in order to obtain a discernible impact on 24-h forecasts, it could be sufficient to assimilate observations when NO(x) emissions are higher over a 12-h window. It was also found that temporally biased NO(x) emissions only slightly perturb O(3).