| Saharan dust is an important contributor on European air quality levels and consequently has
a relevant impact on human health and ecosystems. Even though most of the transport of dust
particles occurs in altitude, as shown by surface lidars and airborne data, dust events
signi?cantly impact surface PM10 concentrations even in urban traf?c type of air quality
monitoring stations, and background stations are needed to assess the contribution of desert
dust. In this sense, regional air quality models are useful to understand the dynamics and
transport of pollutants.
The present contribution shows a preliminary intercomparison of a set of 7 regional dust
model simulations (NMMB/BSC-Dust, ALADIN, Meso-NH, RegCM, CHIMERE,
COSMO/MUSCAT; MOCAGE and BSC-DREAM8b). The present analysis focuses on the
model capability to properly simulate long-range Saharan dust transport for summer 2012 in
the Western Mediterranean. In this period, Saharan dust events were numerous as shown by
satellite and ground-based observations.
The model evaluation is crucial to determine the individual performance of each model
and it provides a useful tool to identify their strengths and weaknesses. In this study, the
model outputs are compared against a variety of both ground-based and airborne in situ and
remote sensing measurements performed during the pre-ChArMEx/TRAQA ?eld campaign
which included the airborne lidar LNG and the new balloonborne optical particle counter
LOAC. Also, the models are compared with satellite aerosol products (including
MSG/SEVIRI, POLDER and CALIOP) which provide a description of the spatial AOD
distribution over the basin. These observational datasets provide a complete set of unusual
quantitative constraints for model simulations of this period, combining data on aerosol
optical depth, vertical distribution, particle size distribution, and chemical and optical
properties.
Acknowledgements are addressed to OMP/SEDOO for the ChArMEx data portal and to
CNES for balloon operations. The main sponsors of the campaign were ADEME and INSU.
LOAC was developed with funding from ANR. |