Development and validation of a simple mineral dust source inventory suitable for modelling in North Central China

The quantitatively most important sources of desert dust are mainly located in North Africa (Sahara and Sahel), in the Middle East (Saudi Arabia, Iran, Iraq) and in continental Asia. This paper presents the buildup of a desert dust source database valid for dust models over China and Mongolia. Our method is based upon the use of a mesoscale model—the RAMS model (Colorado State University, USA)—coupled with a DPM (Dust Production Model) already developed (LISA laboratory, France) and qualified for African and Middle-East areas. As the DPM needs surface data not completely available in this area, our approach is based on an iterative method: successive model runs are compared with observations, and the surface mapping of DPM properties is modified so as to get acceptable model results. After this step, a simple but efficient surface inventory of emissive properties of dust by soils is built. To validate it, we simulate a dust storm in April 2002, which was observed and measured in particular by a surface station near Yulin city (600 km East of Beijing). In this event, we compare the model issues with measured concentrations and particle size distribution. Our model successive fittings allow us to retrieve the mass concentration and size distribution (at least for radii r<1μm) in good agreement with observations. Moreover, this latter simulation agrees with the importance of the “northern high dust sources” often mentioned in literature, i.e. confirms the importance of the Alxa plateau as a main regional source. During the second event, an amount of about 4.1 Mt of dust is raised in a 6-day period, with a peak of 0.2 Mt in 6 h over only 10 000 km2. To sum up, our results allow us to outline an easy built mineral dust source database—not needing too sharp pedological “on field” data—including erodibility fraction, soil types, land cover and snow cover, contributing to the development of the “Asian dust databank”.