Ground-level ozone concentration over Spain: an application of Kalman Filter post-processing to reduce model uncertainties

Abstract

The CALIOPE air quality modelling system, namely WRF-ARW/HERMESEMEP/ CMAQ/BSC-DREAM8b, has been used to perform the simulation of ground level O3 concentration for the year 2004, over the Iberian Peninsula. We use this system to study 5 the daily ground-level O3 maximum. We investigate the use of a post-processing such as the Kalman Filter bias-adjustment technique to improve the simulated O3 maximum. The Kalman Filter bias-adjustment technique is a recursive algorithm to optimally estimate bias-adjustment terms from previous measurements and model results. The bias-adjustment technique is found to improve the simulated O3 maximum for the en10 tire year and the whole domain. The corrected simulation presents improvements in statistical indicators such as correlation, root mean square error, mean bias, standard deviation, and gross error. After the post-processing the exceedances of O3 concentration limits, as established by the European Directive 2008/50/CE, are better reproduced and the uncertainty of the modelling system is reduced from 20% to 7.5%. Such un15 certainty in the model results is under the established EU limit of the 50%. Significant improvements in the O3 average daily cycle and in its amplitude are also observed after the post-processing. The systematic improvements in the O3 maximum simulations suggest that the Kalman Filter post-processing method is a suitable technique to reproduce accurate estimate of ground-level O3 concentration.