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Mineral dust aerosols are, for example, relevant for the radiative transfer in Earth's atmosphere. An important source of information on this aerosol type is provided by remote sensing using lidar systems and sun/sky photometers. We investigate the sensitivity of lidar and photometer observations to the microphysical aerosol properties in a numerical study. Knowledge of this sensitivity is required for the development of microphysical retrieval algorithms. Until recently, such retrieval algorithms were applied only to lidar or photometer observations. Quite different sensitivities for lidar and photometer are found in our study, suggesting that synergistic effects can be expected from combining the observations from both techniques. Furthermore, we compare the modeled aerosol properties to observations of Saharan mineral dust aerosols performed during the SAMUM field campaign. We determined aerosol ensembles that are consistent with the lidar as well as the photometer observations, confirming the feasibility of combining the observations from both techniques. The consistent aerosol ensembles are based on the desert mixture from the OPAC aerosol dataset, and were improved by considering mixing of absorbing and non-absorbing irregularly shaped particles.