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@ARTICLE{Marcal:276360,
author = {Marécal, V. and Peuch, V.-H. and Andersson, C. and
Andersson, S. and Arteta, J. and Beekmann, M. and
Benedictow, A. and Bergström, R. and Bessagnet, B. and
Cansado, A. and Chéroux, F. and Colette, A. and Coman, A.
and Curier, R. L. and Denier van der Gon, H. A. C. and
Drouin, A. and Elbern, H. and Emili, E. and Engelen, R. J.
and Eskes, H. J. and Foret, G. and Friese, E. and Gauss, M.
and Giannaros, C. and Guth, J. and Joly, M. and Jaumouillé,
E. and Josse, B. and Kadygrov, N. and Kaiser, J. W. and
Krajsek, K. and Kuenen, J. and Kumar, U. and Liora, N. and
Lopez, E. and Malherbe, L. and Martinez, I. and Melas, D.
and Meleux, F. and Menut, L. and Moinat, P. and Morales, T.
and Parmentier, J. and Piacentini, A. and Plu, M. and
Poupkou, A. and Queguiner, S. and Robertson, L. and Rouïl,
L. and Schaap, M. and Segers, A. and Sofiev, M. and
Tarasson, L. and Thomas, M. and Timmermans, R. and
Valdebenito, Á. and van Velthoven, P. and van Versendaal,
R. and Vira, J. and Ung, A.},
title = {{A} regional air quality forecasting system over {E}urope:
the {MACC}-{II} daily ensemble production},
journal = {Geoscientific model development},
volume = {8},
number = {9},
issn = {1991-9603},
address = {Katlenburg-Lindau},
publisher = {Copernicus},
reportid = {FZJ-2015-06818},
pages = {2777 - 2813},
year = {2015},
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 MACC-II (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 (O3, 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 μg m−3 on average.
Locally, during the studied ozone episodes, the maxima from
the ensemble median are often lower than observations by
30–50 μg 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 μg m−3. The
ensemble median fractional gross error is larger for PM10 (~
0.52) than for ozone and the correlation is lower (~ 0.35
for PM10 and ~ 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.},
cin = {IEK-8},
ddc = {910},
cid = {I:(DE-Juel1)IEK-8-20101013},
pnm = {243 - Tropospheric trace substances and their
transformation processes (POF3-243)},
pid = {G:(DE-HGF)POF3-243},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000364325700005},
doi = {10.5194/gmd-8-2777-2015},
url = {https://juser.fz-juelich.de/record/276360},
}