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The Asian dust forecasting model, Mongolian Asian Dust Aerosol Model (MGLADAM), has been operated by the National Agency for Meteorology and Environmental Monitoring of Mongolia since 2010, for the forecast of Asian dust storms. In order to evaluate the performance of the dust prediction model, we simulated Asian dust events for the period of spring 2011. Simulated features were compared with observations from two sites in the dust source region of the Gobi desert in Mongolia, and in the downstream region in Korea. It was found that the simulated wind speed and friction velocity showed a good correlation with observations at the Erdene site (one of the sites in the Gobi desert). The results show that the model is proficient in the simulation of dust concentrations that are within the same order of magnitude and have similar start and end times, compared with PM10 observed at two monitoring sites in the Gobi regions. Root Mean Square Error (RMSE) of the dust simulation ranges up to 200 mu g m(-3) because of the high concentrations in source regions, which is three times higher than that in the downstream region. However, the spatial pattern of dust concentration matches well with dust reports from synoptic observation. In the downwind regions, it was found that the model simluated all reported dust cases successfully. It was also found that the RMSE in the downwind region increased when the model integration time increased, but that in the source regions did not show consistent change. It suggests that MGLADAM has the potential to be used as an operational dust forecasting model for predicting major dust events over the dust source regions as well as predicting transported dust concentrations over the downstream region. However, it is thought that further improvement in the emission estimation is necessary, including accurate predictions in surface and boundary layer meteorology. In the downwind regions, background PM10 concentration is considerably affected by other aerosol species, suggesting that a consideration of anthropogenic pollutants will be required for accurate dust forecasting.