A030-08
Grid-independent High Resolution Dust Emissions for Chemical Transport Models: Application to GEOS-Chem

Tuesday, 8 December 2020: 04:28
Virtual
Jun Meng, Dalhousie University, Dept Physics & Atmospheric Sci, Halifax, NS, Canada, Randall Martin, Washington University in St. Louis, Energy, Environmental & Chemical Engineering, St. Louis, MO, United States, Paul A Ginoux, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, Melanie Sarah Hammer, Washington University in St. Louis, Energy, Environmental & Chemical Engineering, St. Louis, United States, David Andrew Ridley, California Air Resources Board, Monitoring and Laboratory Division, Sacramento, United States and Aaron van Donkelaar, Dalhousie University, Dept Physics & Atmospheric Science, Halifax, NS, Canada
Abstract:
The nonlinear dependence of the dust saltation process on wind speed poses a challenge for models of varying resolutions. This challenge is of particular relevance for the next generation of chemical transport models with nimble capability for multiple resolutions. We develop and apply a method to harmonize dust emissions across simulations of different resolutions by generating offline grid independent dust emissions driven by native high resolution meteorological fields. We implement into the GEOS-Chem chemical transport model a high resolution dust source function to generate updated offline dust emissions. The updated offline dust emissions based on high resolution meteorological fields can better resolve weak dust source regions, such as southern South America, southern Africa and the southwestern United States. Identification of an appropriate dust emission strength is facilitated by the resolution independence of offline emissions. We find that the performance of simulated aerosol optical depth (AOD) versus measurements from the AERONET network and satellite remote sensing improves significantly when using the updated offline dust emissions with the total global annual dust emission strength of 2,000 Tg yr-1. The offline high resolution dust emissions are easily implemented in chemical transport models, with potential to promote module model development and evaluation.