Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 µg m-3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies

The financial support of the ACTRIS Re- search Infrastructure Project supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254 is gratefully acknowledged. This project has also received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 289923 – ITaRS. S. Basart and J. M. Baldasano acknowledge the CICYT project (CGL2010-19652 and CGL2013-46736) and Severo Ochoa (SEV-2011-00067) programme of the Spanish Government. This program has received funding from the Ministry of Education and Science of the Republic of Serbia through project III43007. BSC-DREAM8b and NMMB/BSC-Dust simulations were performed on the Mare Nostrum supercomputer hosted by Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS). We thank the AERONET PI’s and their staff for establishing and main-taining the 10 sites used in this investigation. The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model used in this publication. The authors would like to acknowledge the use of Google maps for the images used for realizing Fig. 2. We would also like to thank Slobodan Nickovic for his support and comments during the preparation of this manuscript. We would like to thank the editor and the reviewers for their contribution to the final version of this manuscript.