This paper describes the pre-operational analysis and forecasting systemdeveloped during MACC (Monitoring Atmospheric Composition and Climate) andcontinued in the MACC-II (Monitoring Atmospheric Composition and Climate:Interim Implementation) European projects to provide air quality servicesfor the European continent. This system is based on seven state-of-the artmodels developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS,MATCH, MOCAGE and SILAM). These models are used to calculate multi-modelensemble products. The paper gives an overall picture of its status at theend of MACC-II (summer 2014) and analyses the performance of the multi-modelensemble. The MACC-II system provides daily 96 h forecasts with hourlyoutputs of 10 chemical species/aerosols (O3, NO2, SO2, CO,PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) andPAN+PAN precursors) over eight vertical levels from the surface to 5 km height.The hourly analysis at the surface is done a posteriori for the past day using aselection of representative air quality data from European monitoringstations.The performance of the system is assessed daily, weekly and every 3 months(seasonally) through statistical indicators calculated using the availablerepresentative air quality data from European monitoring stations. Resultsfor a case study show the ability of the ensemble median to forecastregional ozone pollution events. The seasonal performances of the individualmodels and of the multi-model ensemble have been monitored since September2009 for ozone, NO2 and PM10. The statistical indicators for ozonein summer 2014 show that the ensemble median gives onaverage the best performances compared to the seven models. There is very little degradation ofthe scores with the forecast day but there is a marked diurnal cycle,similarly to the individual models, that can be related partly to theprescribed diurnal variations of anthropogenic emissions in the models.During summer 2014, the diurnal ozone maximum is underestimated by theensemble median by about 4 μg m?3 on average. Locally, during thestudied ozone episodes, the maxima from the ensemble median are often lowerthan observations by 30–50 μg m?3. Overall, ozone scores aregenerally good with average values for the normalised indicators of 0.14 forthe modified normalised mean bias and of 0.30 for the fractional grosserror. Tests have also shown that the ensemble median is robust to reductionof ensemble size by one, that is, if predictions are unavailable from onemodel. Scores are also discussed for PM10 for winter 2013–1014. Thereis an underestimation of most models leading the ensemble median to amean bias of ?4.5 μg m?3. The ensemble median fractional grosserror is larger for PM10 (~ 0.52) than for ozone andthe correlation is lower (~ 0.35 for PM10 and~ 0.54 for ozone). This is related to a larger spread of the sevenmodel scores for PM10 than for ozone linked to different levels ofcomplexity of aerosol representation in the individual models. In parallel,a scientific analysis of the results of the seven models and of the ensembleis also done over the Mediterranean area because of the specificity of itsmeteorology and emissions.The system is robust in terms of the production availability. Major effortshave been done in MACC-II towards the operationalisation of all itscomponents. Foreseen developments and research for improving itsperformances are discussed in the conclusion.
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