A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

Abstract

Abstract. This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. The paper gives an overall picture of its status at the end of MACC-II (summer 2014). This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs and PAN + PAN precursors) over 8 vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performances of the system are assessed daily, weekly and 3 monthly (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the median ensemble to forecast regional ozone pollution events. The time period of this case study is also used to illustrate that the median ensemble generally outperforms each of the individual models and that it is still robust even if two of the seven models are missing. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10 and show an overall improvement over time. The change of the skills of the ensemble over the past two summers for ozone and the past two winters for PM10 are discussed in the paper. While the evolution of the ozone scores is not significant, there are improvements of PM10 over the past two winters that can be at least partly attributed to new developments on aerosols in the seven individual models. Nevertheless, the year to year changes in the models and ensemble skills are also linked to the variability of the meteorological conditions and of the set of observations used to calculate the statistical indicators. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

Ozone attributed to Madrid and Barcelona on-road transport emissions: Characterization of plume dynamics over the Iberian Peninsula

“…Moreover, the overall O 3 overestimation can be related to the underestimation of NO 2 (MB = − 5.6 μgNO 2 m −3 on average for the six CTs) that limits the O 3 titration by NO 2 . The RMSE (23.8-29.5 μg m − 3 ) is slightly higher than the annual error of the CALIOPE operational forecast for 2013 (21.1 μg m −3 ; Arévalo et al, 2014) but it is in the range of RMSE of the median MACC-II ensemble daily forecast (20-26 μg m −3 ) in the Mediterranean area (Marécal et al, 2015). Finally, another factor that can explain the general overestimation of O 3 is related to the contribution of the boundary conditions in the western IP domain (O 3 and precursors coming from North America and the Atlantic) which is of special relevance in the IP due to its location in Western Europe as suggested in the area apportionment study by Pay et al (2014b).…”

Meteorological Conditions During an Ozone Episode in Dallas‐Fort Worth, Texas, and Impact of Their Modeling Uncertainties on Air Quality Prediction

“…Such uncertainties need to be carefully considered in air quality evaluations and policy decision‐making (Bei et al, ; Gilliam et al, ; Ludwig & Shelar, ; Pielke, ). While meteorological ensemble modeling has received much attention in both research and operational forecasting during the past three decades (e.g., Palmer et al, ; Stensrud et al, ; Toth & Kalnay, ), the use of ensembles of Eulerian dynamically generated meteorology‐air quality models to characterize uncertainties of air quality forecast has been lagging behind (e.g., Bei et al, ; Delle Monache et al, ; Delle Monache & Stull, ; Djalalova et al, ; Galmarini et al, ; Marecal et al, ; McKeen et al, ; Monteiro et al, ; Vautard et al, ; Zhang et al, ). To achieve skillful probabilistic air quality forecasts, different approaches were used to construct the ensemble, including using multiple air quality models (Delle Monache & Stull, ; Djalalova et al, ; Galmarini et al, ; Marecal et al, ; McKeen et al, ; Monteiro et al, ; Vautard et al, ), perturbing emissions (Delle Monache et al, ), and perturbing meteorological conditions (Bei et al, ; Zhang et al, ).…”

Ozone and aerosol tropospheric concentrations variability analyzed using the ADRIMED measurements and the WRF and CHIMERE models

“…The first step is to evaluate if the ADRIMED period was highly polluted or not, compared to previous summers in this Marécal et al (2015). This production has been established by the GEMS FP6 project and its follow-up FP7 projects (MACC, MACC-II and MACC-III).…”