Enhancing Air Quality Forecasts over Catalonia (Spain) Using Model Output Statistics

摘要

ModelOutput Statistics (MOS) is a well-known technique that allows improving outputsfrom numerical atmospheric models. In this contribution, we present the developmentof a MOS algorithm to improve air quality forecasts in Catalonia, a region inthe northeast of Spain. These forecasts are obtained from an Eulerian coupledair quality modelling system developed by Meteosim. Nitrogen Dioxide (NO2),Particulate Matter (PM10) and Ozone (03) have been thepollutants considered and the methodology has been applied on statisticalvalues of these pollutants according to regulatory levels. Four MOS algorithmshave been developed, characterized by different approaches in relation withseasonal stratification and stratification according to the measurementstations considered. Algorithms have been compared among them in order toobtain a MOS that reduces the forecast uncertainties. Results obtained showthat the best MOS designed increases the accuracy of NO2 maximum 1-hdaily value forecast from 71% to 75%, from 68% to 81% in the case of dailyvalues of PM10, and finally, the accuracy of O3 maximum1-h daily value from 79% to 87%.