In the year 2006, the DREAM-8b (Dust Regional Atmospheric Model) with a detailed set of 8 dust particle size classes between 0.1 and 7 microns (0.15, 0.25, 0.45, 0.78, 1.3, 2.2, 3.8, and 7.1 microns) was put in operational use at Tel-Aviv University [Nickovic et al., 2001, Kishcha et al., 2007, 2008, Carnevale et al., 2012]. The dust prediction system produces daily forecasts of 3-D distribution of dust concentration over different model domains including the Mediterranean, North Africa, Europe, and the Atlantic Ocean (http://wind.tau.ac.il/dust8/dust.html). Over the main model domain (20W - 45E, 15N - 50N), the grid spacing of dust forecast is 0.3 degrees.
DREAM is driven by the Eta meteorological model coupled with the module describing the dust cycle [Nickovic et al., 2001]. It includes all major process which dust particles are involved in, such as dust production from sources, vertical turbulent transport and vertical advection, horizontal transport and wet and dry deposition. DREAM is initialized with the NCEP analysis and the lateral boundary data are updated every 6h by the global NCEP GFS model from USA.
The emissions of mineral dust depend on friction velocity and on surface conditions. DREAM calculates wind friction velocity based on the surface roughness and soil moisture. Friction velocity is the velocity of airflow in the lowest several meters of the boundary layer. Dust is entrained into the atmosphere when the friction velocity exceeds the threshold of ~(0.4 - 1.2 m/s). (This threshold friction velocity corresponds to horizontal wind velocity of approximately 6 - 15 m/s). Surface conditions for dust emissions are controlled mainly by the following factors: type of soil, type of vegetation cover, soil moisture content, and surface atmospheric turbulence. To this end, DREAM uses 30-sec resolution US Geological Survey (USGS) topography and land use data, in combination with the Olson World Ecosystem Data classification of 10-min resolution [Nickovic et al., 2001]. DREAM includes dust sources in the Western, Central, and Eastern Sahara, as well as in the Arabian Peninsula. Dry deposition of dust particles: the dry deposition scheme in DREAM is based on Georgi .
Carnevale, C., Finzi, G., Pisoni, E., Volta, M., Kishcha, P., and Alpert, P. (2012). Integrating Saharan dust forecasts into a regional chemical transport model: a case study over Northern Italy. Science of the Total Environment, Vol. 417-418, 224-231.
Georgi, F. (1986). A particle dry-deposition parameterization sceme for use in tracer transport models. J, . Geophys. Res.,91, 9794-9806
Kishcha, P., Alpert, P., Shtivelman, A., Krichak, S., Joseph, J., Kallos, G., Spyrou, C., Gobbi, G.P., Barnaba, F., Nickovic, S., Perez, C., and J.M. Baldasano (2007). Forecast errors in dust vertical distributions over Rome (Italy): Multiple particle size representation and cloud contributions. J. Geophys. Res., 112, D15205, doi:10.1029/2006JD007427.
Kishcha, P., Nickovic, S., Ganor, E., Kordova, L., Alpert, P. (2008). Saharan dust over the Eastern Mediterranean: Model sensitivity. Air pollution modelling and its application XIX. Chapter 4.2, Springer, ISSN: 1874-6519, DOI:10.1007/978-1-4020-8453-9_39, 358-366.
Nickovic, S., Kallos, G., Papadopoulos, A., and Kakaliagou, O. (2001): A model for prediction of desert dust cycle in the atmosphere, J. Geophys. Res., 106, 18113-18130, doi: 10.1029/2000JD900794.