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Titel |
Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants |
VerfasserIn |
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, S. Galmarini |
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 ; 6, no. 3 ; Nr. 6, no. 3 (2013-06-12), S.791-818 |
Datensatznummer |
250017823
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Publikation (Nr.) |
copernicus.org/gmd-6-791-2013.pdf |
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Zusammenfassung |
This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII)
and aims at the operational evaluation
of an ensemble of 12 regional-scale chemical transport models used to
predict air quality over the North American (NA) and European (EU)
continents for 2006. The modelled concentrations of ozone and CO, along with
the meteorological fields of wind speed (WS) and direction (WD), temperature
(T), and relative humidity (RH), are compared against high-quality in-flight
measurements collected by instrumented commercial aircraft as part of the
Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by
Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out
for five model domains positioned around four major airports in NA
(Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt),
from the surface to 8.5 km. We compare mean vertical profiles of modelled
and measured variables for all airports to compute error and variability
statistics, perform analysis of altitudinal error correlation, and examine
the seasonal error distribution for ozone, including an estimation of the
bias introduced by the lateral boundary conditions (BCs). The results
indicate that model performance is highly dependent on the variable,
location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being
analysed. While model performance for T is satisfactory at all sites
(correlation coefficient in excess of 0.90 and fractional bias ≤ 0.01 K),
WS is not replicated as well within the PBL (exhibiting a
positive bias in the first 100 m and also underestimating observed variability),
while above 1000 m, the model performance improves (correlation coefficient
often above 0.9). The WD at NA airports is found to be biased in the PBL,
primarily due to an overestimation of westerly winds. RH is modelled well
within the PBL, but in the free troposphere large discrepancies among models
are observed, especially in EU. CO mixing ratios show the largest range of
modelled-to-observed standard deviations of all the examined species at all
heights and for all airports. Correlation coefficients for CO are typically
below 0.6 for all sites and heights, and large errors are present at all
heights, particularly in the first 250 m. Model performance for ozone in the
PBL is generally good, with both bias and error within 20%. Profiles of
ozone mixing ratios depend strongly on surface processes, revealed by the
sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter
is biased low at all locations in the NA, primarily due to an
underestimation of ozone from the BCs. Most of the model error in the PBL is
due to surface processes (emissions, transport, photochemistry), while
errors originating aloft appear to have relatively limited impact on model
performance at the surface. Suggestions for future work include
interpretation of the model-to-model variability and common sources of model
bias, and linking CO and ozone bias to the bias in the meteorological
fields. Based on the results from this study, we suggest possible in-depth,
process-oriented and diagnostic investigations to be carried out next. |
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