Severe dust outbreaks and high dust loading over Eastern Africa and the Red Sea are frequently detected in the summer season. Observations suggest that small-scale dynamic and orographic effects, from both the Arabian and African sides, strongly contribute to dust plume formation. To better understand these processes, we present here the first high resolution modeling study of a dust outbreak in June 2012 developed over East Africa, the Red Sea, and the Arabian Peninsula. Using the Weather Research and Forecasting model coupled with Chemistry component (WRF-Chem), we identified several dust generating dynamical processes that range from convective to synoptic scales, including synoptic cyclones, nocturnal low-level jets, and cold pools of mesoscale convective systems. The simulations reveal an eastward transport of African dust across the Red Sea. Over the northern part of the Red Sea, most of the dust transport occurs above 2 km height, whereas across the central and southern parts of the sea, dust is mostly transported below 2 km height. Dust is the dominant contributor (87%) to the aerosol optical depth, producing a domain average cooling effect of -12.1 W m-2 at the surface, a warming of 7.1 W m-2 in the atmosphere, and a residual cooling of -4.9 W m-2 at the top of the atmosphere. Both dry and wet deposition processes contribute significantly to dust removal from the atmosphere. Model results compare well with available ground-based and satellite observations, but generally underestimate the observed maximum values of aerosol optical depth. The satellite-retrieved mean optical depth at some locations are underestimated by a factor of two. A sensitive experiment suggests that these large local differences may result from poor characterization of dust emissions in some areas of the modeled domain. In this case study we successfully simulate the major fine-scale dust generating dynamical processes, explicitly resolving convection and haboob formation. The future development of this novel approach will be beneficial for dust research, assuming steady growth of available computational power.