Abstract. In this study we aim at optimizing the WRF-Chem model performance for the purpose of operational forecasting of dust transport over the eastern Mediterranean. For this reason, we compare the model output to observations in order to assess its capacity to realistically reproduce the aerosol optical depth (AOD), focusing on three key regions: North Africa, the Arabian Peninsula and the eastern Mediterranean. Three sets of four simulations each have been performed for the six-month period of spring and summer 2011. Each simulation set uses a different dust emission parametrisation and for each parametrisation, the dust emissions are multiplied with various coefficients in order to tune the model performance. Our approach is based on the model assessment across spatial and temporal scales by comparing its outputs to AOD observations from satellites and ground-based stations, as well as airborne measurements of aerosol extinction coefficients over the Sahara.

Tuning the model performance by applying a coefficient to dust emissions may reduce the model AOD bias over a region, but may increase it in other regions. Concerning dust transport over the eastern Mediterranean, the model was shown to realistically reproduce the major transport events, however failing to capture the regional background AOD. Model assessment over the entire domain and simulation period shows that the model presents temporal and spatial variability similar to observed AODs, regardless of the applied dust emission parametrisation. However, when focusing on specific regions, the model’s skill may vary significantly. Further comparison of the model simulations to airborne measurements of the vertical profiles of extinction coefficients over North Africa suggests that the model may realistically reproduce the total atmospheric column AOD. Finally, we show that the inclusion of a finer dust mode (less than 1 μm) in the model presents the advantage of relaxing unrealistically large atmospheric dust loads and yet reproducing realistic AOD values.