Abstract
The synoptic characteristics of dusty spring days in central and eastern Saudi Arabia were analyzed using the aerosol index (AI) from the TOMS satellite and meteorological parameters from the NCEP/NCAR reanalysis dataset. The AI distributions were used to detect and classify dusty spring days into three classes (narrow, moderate, and wide spread). The synoptic features of the cases and classes demonstrated the common synoptic characteristics that represented the dusty spring cases. The strength of these common synoptic characteristics was found to increase with increasing dust severity. Specifically, as the following factors occurred, the cyclone located over the southern Arabian Peninsula deepened, the maximum wind at 250 hPa weakened and shifted northward, the instability over the northern Arabian Peninsula increased, the northerly wind generated, and the gradient of the 850-hPa potential temperature west of the cyclone increased; the severity of the dust class increased. The results were confirmed by examining three specific cases representing weak, moderate, and severe dust events.