Abstract
This paper describes the pre-operational analysis and forecasting system
developed during MACC (Monitoring Atmospheric Composition and Climate)
and continued in the MACC-II (Monitoring Atmospheric Composition and
Climate: Interim Implementation) European projects to provide air
quality services for the European continent. 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 paper gives an
overall picture of its status at the end of MACCII (summer 2014) and
analyses the performance of the multi-model ensemble. The MACC-II system
provides daily 96 h forecasts with hourly outputs of 10 chemical
species/aerosols (O-3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs
(non-methane volatile organic compounds) and PAN + 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 a
selection of representative air quality data from European monitoring
stations.
The performance of the system is assessed daily, weekly and every 3
months (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 ensemble
median to forecast regional ozone pollution events. The seasonal
performances of the individual models and of the multi-model ensemble
have been monitored since September 2009 for ozone, NO2 and PM10. The
statistical indicators for ozone in summer 2014 show that the ensemble
median gives on average the best performances compared to the seven
models. There is very little degradation of the scores with the forecast
day but there is a marked diurnal cycle, similarly to the individual
models, that can be related partly to the prescribed diurnal variations
of anthropogenic emissions in the models. During summer 2014, the
diurnal ozone maximum is underestimated by the ensemble median by about
4 mu g m(-3) on average. Locally, during the studied ozone episodes, the
maxima from the ensemble median are often lower than observations by
30-50 mu g m(-3). Overall, ozone scores are generally good with average
values for the normalised indicators of 0.14 for the modified normalised
mean bias and of 0.30 for the fractional gross error. Tests have also
shown that the ensemble median is robust to reduction of ensemble size
by one, that is, if predictions are unavailable from one model. Scores
are also discussed for PM10 for winter 2013-1014. There is an
underestimation of most models leading the ensemble median to a mean
bias of 4.5 mu g m(-3). The ensemble median fractional gross error is
larger for PM10 (similar to 0.52) than for ozone and the correlation is
lower (similar to 0.35 for PM10 and similar to 0.54 for ozone). This is
related to a larger spread of the seven model scores for PM10 than for
ozone linked to different levels of complexity of aerosol representation
in the individual models. 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.
