Predictions of particulate properties and their effect on meteorological conditions via direct (scattering and absorption of radiation) and indirect (cloud-aerosol interactions) radiative forcing still contain large uncertainties. To address this issue, we have developed an Aerosol Modeling Testbed that streamlines the process of testing and evaluating aerosol process modules over a wide range of spatial and temporal scales. The Aerosol Modeling Testbed consists of the WRF-chem model and a suite of tools to evaluate the performance of aerosol process modules via comparison with a wide range of field measurements. In this study, we examine the advantages and disadvantages of aerosol models that employ either the modal or sectional approaches in representing the aerosol size distribution. Modal aerosol models are computationally more efficient than sectional models because of the smaller number of required variables; however, sectional models are thought to be more accurate. Simulations are performed for the MILAGRO field campaign period in which extensive surface, aircraft, and satellite measurements were made in the vicinity and downwind of Mexico City. The modal and sectional model simulations employ identical emissions, initial and boundary conditions, and meteorology, so that the differences are due solely to the treatment of aerosol processes. We examine the performance of each model in simulating particulate mass, composition, and size distribution over and downwind of Mexico City. Since WRF-Chem also includes consistent treatments for aerosol radiative forcing for the modal and sectional approaches, we also assess the impacts of differences in predicted particulate properties on aerosol optical depth, single scattering albedo, and aerosol radiative forcing associated with anthropogenic pollutants. The implications of the choice of aerosol model on determining the influence of urban pollutants on regional climate will be discussed.
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