Abstract

The African Monsoon Multidisciplinary Analysis (AMMA) is a major international campaign investigating far‐reaching aspects of the African monsoon, climate and the hydrological cycle. A special observing period was established for the dry season (SOP0) with a focus on aerosol and radiation measurements. SOP0 took place during January and February 2006 and involved several ground‐based measurement sites across west Africa. These were augmented by aircraft measurements made by the Facility for Airborne Atmospheric Measurements (FAAM) aircraft during the Dust and Biomass‐burning Experiment (DABEX), measurements from an ultralight aircraft, and dedicated modeling efforts. We provide an overview of these measurement and modeling studies together with an analysis of the meteorological conditions that determined the aerosol transport and link the results together to provide a balanced synthesis. The biomass burning aerosol was significantly more absorbing than that measured in other areas and, unlike industrial areas, the ratio of excess carbon monoxide to organic carbon was invariant, which may be owing to interaction between the organic carbon and mineral dust aerosol. The mineral dust aerosol in situ filter measurements close to Niamey reveals very little absorption, while other measurements and remote sensing inversions suggest significantly more absorption. The influence of both mineral dust and biomass burning aerosol on the radiation budget is significant throughout the period, implying that meteorological models should include their radiative effects for accurate weather forecasts and climate simulations. Generally, the operational meteorological models that simulate the production and transport of mineral dust show skill at lead times of 5 days or more. Climate models that need to accurately simulate the vertical profiles of both anthropogenic and natural aerosols to accurately represent the direct and indirect effects of aerosols appear to do a reasonable job, although the magnitude of the aerosol scattering is strongly dependent upon the emission data set.