Quantitative estimation of surface ozone observation and forecast errors

Abstract

Five-month time series of hourly ground level ozone data of more than 360 German monitoring sites are investigated to estimate errors in observations and forecasts by a comprehensive three-dimensional regional chemistry transport model. On the assumption of uniform measurement techniques, error variances and spatial error correlations in the gridded background field are derived from the analysis of observation increments which are the differences between observations and modeled data. A thorough estimation of those error characteristics is the basic requirement for all data assimilation techniques. The results indicate how the representativeness of the observation sites is limited by differences in local emission characteristics. Additionally, there is a strong dependency on the time of day. The conclusion is that the description of observation and background error covariances for the analysis of ground level ozone has to be time-dependent and spatially inhomogeneous.