[1] Numerous high-resolution (1 km or better) images from satellite remote sensing platforms, i.e., space shuttle, Sea-viewing Wide Field-of-view Sensor, and the Moderate Resolution Imaging Spectroradiometer, show dust plumes at the scale of 100 km originate from the merging of a multitude of point source plumes. These point source plumes stem from numerous point sources measuring 1-10s km across. Capitalizing on the Naval Research Laboratory's recently developed satellite derived 1-km Dust Enhancement Product (DEP) imagery we can readily distinguish elevated dust over land from other components of the scene and identify the many small, eroding point sources that form the heads of point source plumes. On the basis of this approach, a high-resolution (1-km) dust source database (DSD) is created using 5 years (2001)(2002)(2003)(2004)(2005) of DEP imagery for southwest Asia. The performance of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) using the high-resolution DSD is evaluated via a case study of a major dust event over Afghanistan, Iran, and Pakistan in October 2001. The results from our case study show that the improved specification of erodible land surfaces by use of a high-resolution DSD allows COAMPS to accurately model the evolution of individual dust plumes and better forecast the onset and end of dust storm occurrence (i.e., low-visibility conditions). Statistical analyses of the visibility predictions and dust storm occurrence show simulations using the high-resolution DSD have the lowest false alarm rates and the highest total prediction skill among the other DSDs that were considered. This work contributes to the growing base of knowledge concerning the global dust cycle by identifying and mapping point sources in one of the world's foremost dust-producing regions.