Online simulations of global aerosol distributions in the NASA GEOS‐4 model...

Colarco, P. R., A. da Silva, M. Chin, and T. Diehl (2010), Online simulations of global aerosol distributions in the NASA GEOS‐4 model and comparisons to satellite and ground‐based aerosol optical depth, J. Geophys. Res., 115, D14207, doi:10.1029/2009JD012820.

We have implemented a module for tropospheric aerosols (GOCART) online in the NASA Goddard Earth Observing System version 4 model and simulated global aerosol distributions for the period 2000–2006. The new online system offers several advantages over the previous offline version, providing a platform for aerosol data assimilation, aerosol‐chemistry‐climate interaction studies, and short‐range chemical weather forecasting and climate prediction. We introduce as well a methodology for sampling model output consistently with satellite aerosol optical thickness (AOT) retrievals to facilitate model‐satellite comparison. Our results are similar to the offline GOCART model and to the models participating in the AeroCom intercomparison. The simulated AOT has similar seasonal and regional variability and magnitude to Aerosol Robotic Network (AERONET), Moderate Resolution Imaging Spectroradiometer, and Multiangle Imaging Spectroradiometer observations. The model AOT and Angstrom parameter are consistently low relative to AERONET in biomass‐burning‐dominated regions, where emissions appear to be underestimated, consistent with the results of the offline GOCART model. In contrast, the model AOT is biased high in sulfate‐dominated regions of North America and Europe. Our model‐satellite comparison methodology shows that diurnal variability in aerosol loading is unimportant compared to sampling the model where the satellite has cloud‐free observations, particularly in sulfate‐dominated regions. Simulated sea salt burden and optical thickness are high by a factor of 2–3 relative to other models, and agreement between model and satellite over‐ocean AOT is improved by reducing the model sea salt burden by a factor of 2. The best agreement in both AOT magnitude and variability occurs immediately downwind of the Saharan dust plume.

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Modeling Analysis and Prediction Program (MAP)