Reanalysis

see also Model Intercomparison

Several regional models are in use to predict Saharan dust events and dust transport towards Europe. It is proposed to test the performance of the different models by means of an intercomparison study based on reanalysis of selected years. The model evaluation will make use of a wide range of available datasets describing different aspects of the atmospheric dust. The results of this study are expected to improve the dust parameterization in the individual models and ultimately improve dust forecasts.

In regions downwind of major dust sources, where frequent occurrences of elevated dust concentration significantly affects air quality and traffic, precise dust forecasts are useful for decision makers and the general public. The usefulness of dust forecast models not only depends on the quality of the underlying meteorological model, but also on their skill to correctly predict dust emission and deposition. In particular, the ability of the models to simulate the precise location and intensity of dust emission events are suspected to be of major importance for the dust forecasting skill. Earlier model studies already pointed out the importance of prescribing surface properties like the surface roughness lengths and the surface wind fields realistically to correctly compute dust emissions. However, the performance of the different dust transport models have not yet been systematically compared, and the main reasons for model discrepancies have not yet been determined.

Several models (mostly operating at regional-scale, including DREAM [Perez et al., 2006], SKIRON [Kallos et al., 1997, Rodriguez et al., 2001], TAU [Kishcha et al., 2005]  and CHIMERE-DUST  [Menut et al., 2005] are used for forecasting advancing Saharan dust transport towards southern Europe. A dust forecast model intercomparison study following the approach that was successfully  applied in the AEROCOM  project ([Textor et al., 2006]; http://nansen.ipsl.jussieu.fr/AEROCOM/aerocomhome.html)  (a multi-model intercomparison and evaluation project for global aerosol models  with observations that aimed at reducing uncertainty in simulated radiative forcing) will help to reveal the major strengths and weaknesses of the individual regional Saharan dust models, ultimately leading to improved dust forecasts. Different models are used for different regions of interest.

At least one full year (2006) will be analyzed to capture both absence and presence of dust in different regions in particular source areas in the Sahara. The test year is selected such that as much as possible observation data are available for model evaluation, including remote sensing information (e.g. from the CALIPSO and Meteosat satellites), as well as data from field studies AMMA (2006) and SAMUM1 (2006). Long term data (most of these are already available on the AEROCOM data server) to support such an analysis include:

• Aerosol optical thickness measurements from the AERONET sunphotometer network
• Satellite retrievals: optical thickness over dark surfaces (e.g. from instruments onboard NASA Terra and Aqua satellites), ‘Deep Blue’ aerosol retrievals, OMI absorbing aerosol index. Geostationary satellite information, e.g. Meteosat Second Generation SEVIRI infrared dust index (including derived dust source activation frequencies)
• Vertical backscatter profiles (CALIPSO satellite retrievals, ground lidar data (EARLINET network)
• PM10 concentration measurements e.g. in Southern Europe
• Standard meteorological observations (10-m surface wind speed, precipitation) for evaluation of the model meteorology

The model domains must include North Africa and Southern Europe to be large enough to include the relevant source regions and downwind transport. A set of model diagnostics for the intercomparison study will be determined in cooperation with the participating model groups. The expected model output fields (NetCDF format) include dust optical thickness, surface concentrations, and selected extinction profiles. Models should also provide forecasted fields at +2 days to investigate forecast skills. The model intercomparison study should preferably be based at the Regional Center.

Performing a series of model experiments will help to identify the major sources for discrepancies between the different models. If possible, each model should perform three different model experiments for each dust case:

1. Standard model setup
2. Dust emissions in the model computed with prescribed surface wind fields for assessment of the different emission schemes
3. Prescribed dust emissions (including fixed size distribution) for each model

The timeframe of such project would be approximately two years, if the existing AEROCOM infrastructure would be reused and adapted. The support of a programmer based at the Regional Center would be required because of the needs to re-grid and homogenize the model output fields that will in general be provided in different formats and grid arrangements (1 week per model => 10 weeks for ten models). Furthermore it would be necessary to compile and integrate the observational data sets, which come with the case study chosen, into the AEROCOM model-data comparison software tools (ca. 10 weeks depending on complexity of final choices). It will also be necessary to prepare appropriate graphical tools, carry out statistical analyses and compute scores and make the results available via a web interface.

References

Kishcha, P., F. Barnaba, G. P. Gobbi, P. Alpert, A. Shtivelman, S. O. Krichak, and J. H. Joseph (2005), Vertical distribution of Saharan dust over Rome (Italy): Comparison between 3-year model predictions and lidar soundings, J. Geophys. Res.-Atmos., 110(D6).

Menut, L., C. Schmechtig, and B. Marticorena (2005), Sensitivity of the sandblasting flux calculations to the soil size distribution accuracy, Journal of Atmospheric and Oceanic Technology, 22(12), 1875-1884.

Pérez C., S. Nickovic, G. Pejanovic, J.M. Baldasano and E. Ozsoy (2006), Interactive Dust-radiation Modeling: A Step to improve Weather Forecast, J.  Geophys. Res., 111, D16206, doi:10.1029/2005JD006717.

Rodriguez, S., X. Querol, A. Alastuey, G. Kallos, and O. Kakaliagou (2001), Saharan dust contributions to PM10 and TSP levels in Southern and Eastern Spain, Atmos. Environ., 35(14), 2433-2447.

Textor, C., M. Schulz, S. Guibert, S. Kinne, Y. Balkanski, S. Bauer, T. Berntsen, T. Berglen, O. Boucher, M. Chin, F. Dentener, T. Diehl, R. Easter, H. Feichter, D. Fillmore, S. Ghan, P. Ginoux, S. Gong, J. E. Kristjansson, M. Krol, A. Lauer, J. F. Lamarque, X. Liu, V. Montanaro, G. Myhre, J. Penner, G. Pitari, S. Reddy, O. Seland, P. Stier, T. Takemura, and X. Tie (2006), Analysis and quantification of the diversities of aerosol life cycles within AeroCom, Atmos. Chem. Phys., 6, 1777-1813.