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Titel |
How realistic are air quality hindcasts driven by forcings from climate model simulations? |
VerfasserIn |
G. Lacressonnière, V.-H. Peuch, J. Arteta, B. Josse, M. Joly, V. Marecal, D. Saint Martin, M. Déqué, L. Watson |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1991-959X
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Digitales Dokument |
URL |
Erschienen |
In: Geoscientific Model Development ; 5, no. 6 ; Nr. 5, no. 6 (2012-12-12), S.1565-1587 |
Datensatznummer |
250002958
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Publikation (Nr.) |
copernicus.org/gmd-5-1565-2012.pdf |
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Zusammenfassung |
Predicting how European air quality could evolve over the next decades in the
context of changing climate requires the use of climate models to produce
results that can be averaged in a climatologically and statistically sound
manner. This is a very different approach from the one that is generally used
for air quality hindcasts for the present period; analysed meteorological
fields are used to represent specifically each date and hour. Differences
arise both from the fact that a climate model run results in a pure model output, with
no influence from observations (which are useful to correct for a range of
errors), and that in a "climate" set-up, simulations on a given day, month
or even season cannot be related to any specific period of time (but can just
be interpreted in a climatological sense). Hence, although an air quality
model can be thoroughly validated in a "realistic" set-up using analysed
meteorological fields, the question remains of how far its outputs can be
interpreted in a "climate" set-up. For this purpose, we focus on Europe and
on the current decade using three 5-yr simulations performed with the
multiscale chemistry-transport model MOCAGE and use meteorological forcings
either from operational meteorological analyses or from climate
simulations. We investigate how statistical skill indicators compare in the
different simulations, discriminating also the effects of meteorology on
atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the
dependent emissions and deposition processes (volatile organic compound
emissions, deposition velocities, etc.). Our results show in particular how
differing boundary layer heights and deposition velocities affect horizontal
and vertical distributions of species. When the model is driven by
operational analyses, the simulation accurately reproduces the observed values
of O3, NOx, SO2 and, with some bias that can be
explained by the set-up, PM10. We study how the simulations driven
by climate forcings differ, both due to the realism of the forcings (lack of
data assimilated and lower resolution) and due to the lack of representation
of the actual chronology of events. We conclude that the indicators such as
mean bias, mean normalized bias, RMSE and deviation standards can be used to
interpret the results with some confidence as well as the health-related
indicators such as the number of days of exceedance of regulatory
thresholds. These metrics are thus considered to be suitable for the
interpretation of simulations of the future evolution of European air quality. |
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