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| Titel |
A new chemistry option in WRF-Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data |
| VerfasserIn |
P. Tuccella, G. Curci, G. A. Grell, G. Visconti, S. Crumeyrolle, A. Schwarzenboeck, A. A. Mensah |
| 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 ; 8, no. 9 ; Nr. 8, no. 9 (2015-09-04), S.2749-2776 |
| Datensatznummer |
250116552
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| Publikation (Nr.) |
 copernicus.org/gmd-8-2749-2015.pdf |
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| Zusammenfassung |
| A parameterization for secondary organic aerosol (SOA) production based on
the volatility basis set (VBS) approach has been coupled with microphysics
and radiative schemes in the Weather Research and Forecasting model with
Chemistry (WRF-Chem) model. The new chemistry option called
"RACM-MADE-VBS-AQCHEM" was evaluated on a cloud
resolving scale against ground-based and aircraft measurements collected
during the IMPACT-EUCAARI (Intensive Cloud Aerosol Measurement Campaign –
European Integrated project on Aerosol Cloud Climate and Air quality
interaction) campaign, and complemented with satellite data from MODIS. The
day-to-day variability and the diurnal cycle of ozone (O3) and nitrogen
oxides (NOx) at the surface are captured by the model. Surface aerosol
mass concentrations of sulfate (SO4), nitrate (NO3), ammonium
(NH4), and organic matter (OM) are simulated with correlations larger
than 0.55. WRF-Chem captures the vertical profile of the aerosol mass
concentration in both the planetary boundary layer (PBL) and free troposphere
(FT) as a function of the synoptic condition, but the model does not capture
the full range of the measured concentrations. Predicted OM concentration is
at the lower end of the observed mass concentrations. The bias may be
attributable to the missing aqueous chemistry processes of organic compounds
and to uncertainties in meteorological fields. A key role could be played by
assumptions on the VBS approach such as the SOA formation pathways, oxidation
rate, and dry deposition velocity of organic condensable vapours. Another
source of error in simulating SOA is the uncertainties in the anthropogenic
emissions of primary organic carbon. Aerosol particle number concentration
(condensation nuclei, CN) is overestimated by a factor of 1.4 and 1.7 within
the PBL and FT, respectively. Model bias is most likely attributable to the
uncertainties of primary particle emissions (mostly in the PBL) and to the
nucleation rate. Simulated cloud condensation nuclei (CCN) are also
overestimated, but the bias is more contained with respect to that of CN. The
CCN efficiency, which is a characterization of the ability of aerosol
particles to nucleate cloud droplets, is underestimated by a factor of 1.5
and 3.8 in the PBL and FT, respectively. The comparison with MODIS data shows
that the model overestimates the aerosol optical thickness (AOT). The domain
averages (for 1 day) are 0.38 ± 0.12 and 0.42 ± 0.10 for MODIS
and WRF-Chem data, respectively. The droplet effective radius (Re)
in liquid-phase clouds is underestimated by a factor of 1.5; the cloud liquid
water path (LWP) is overestimated by a factor of 1.1–1.6. The consequence is
the overestimation of average liquid cloud optical thickness (COT) from a few
percent up to 42 %. The predicted cloud water path (CWP) in all phases
displays a bias in the range +41–80 %, whereas the bias of COT is
about 15 %. In sensitivity tests where we excluded SOA, the skills of the
model in reproducing the observed patterns and average values of the
microphysical and optical properties of liquid and all phase clouds
decreases. Moreover, the run without SOA (NOSOA) shows convective clouds
with an enhanced content of liquid and frozen hydrometers, and stronger
updrafts and downdrafts. Considering that the previous version of WRF-Chem
coupled with a modal aerosol module predicted very low SOA content (secondary
organic aerosol model (SORGAM) mechanism) the new proposed option may lead to
a better characterization of aerosol–cloud feedbacks. |
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