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controlled by a multitude of processes such as cloud microphysics and particle growth, radiative transfer, atmospheric dynamics on a variety of space and time scales, and inhomogeneities of the earth’s surface, all of which have to be properly represented in a GCM. It is well known that unless the GCM output is corrected for biases, results from a forced hydrological simulation will be unrealistic and of little use ( Sharma et al. 2007 ; Hansen et al. 2006 ). Such a bias correction should correct more
controlled by a multitude of processes such as cloud microphysics and particle growth, radiative transfer, atmospheric dynamics on a variety of space and time scales, and inhomogeneities of the earth’s surface, all of which have to be properly represented in a GCM. It is well known that unless the GCM output is corrected for biases, results from a forced hydrological simulation will be unrealistic and of little use ( Sharma et al. 2007 ; Hansen et al. 2006 ). Such a bias correction should correct more
variations in atmospheric aerosol loading on downward shortwave radiation fluxes ( Uppala et al. 2005 ), although long-term changes in aerosol loading can significantly influence downward shortwave radiation fluxes (e.g., Wild et al. 2008 ). A correction was therefore made for the effects of tropospheric and stratospheric aerosols on downward surface fluxes of shortwave radiation using twentieth-century aerosol optical depths (AODs) taken from a GCM combined with lookup tables of radiative transfer
variations in atmospheric aerosol loading on downward shortwave radiation fluxes ( Uppala et al. 2005 ), although long-term changes in aerosol loading can significantly influence downward shortwave radiation fluxes (e.g., Wild et al. 2008 ). A correction was therefore made for the effects of tropospheric and stratospheric aerosols on downward surface fluxes of shortwave radiation using twentieth-century aerosol optical depths (AODs) taken from a GCM combined with lookup tables of radiative transfer
