Downscaling aerosols and the impact of neglected subgrid processes on direct aerosol radiative forcing for a representative global climate model grid spacing

Abstract

[1] Recent improvements to many global climate models include detailed, prognostic aerosol calculations intended to better reproduce the observed climate. However, the trace gas and aerosol fields are treated at the grid cell scale with no attempt to account for subgrid impacts on the aerosol fields. This paper begins to quantify the error introduced by the neglected subgrid variability for the shortwave direct aerosol radiative forcing for a representative climate model grid spacing of 75 km. An analysis of the value added in downscaling aerosol fields is also presented to give context to the WRF-Chem simulations used for the subgrid analysis. We found that the impact of neglected subgrid variability on the direct aerosol radiative forcing is strongest in regions of complex topography and complicated flow patterns. Evidence also suggests that scale-induced differences in emissions, particularly for emissions calculated online, such as dust, contribute strongly to the impact of neglected subgrid processes on the aerosol radiative forcing. The two of these effects together, when simulated at 75 km versus 3 km in WRF-Chem, result in an average daytime mean bias of over 30% error in top-of-atmosphere shortwave direct aerosol radiative forcing for a large percentage of central Mexico during the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign and an average mean bias of 10% when averaged over the entire analysis region and 17 day period.