13 April 2016

Sea Salt and Dust Emissions in the Community Atmosphere Model

Testing and quantifying the impact of sub-grid surface wind variability for model improvement.


Inside a global climate model grid box, wind speeds can have large spatial variability, but such variability is often neglected when calculating wind-driven aerosol particle emissions. There is a need to assess the consequences, and design remedies when this omission leads to the model having large deviations from the true value.


Scientists developed a new method to represent the effects of small-scale wind variability on natural aerosol particle emissions in global climate models, and with a negligible increase in computational cost. The new method provides an opportunity to improve the realism of simulated aerosol particle emissions.


Department of Energy scientists at Pacific Northwest National Laboratory analyzed high-resolution global and regional near-surface wind speed model results to find out how large the unresolved variability is in model grid cells that are about 200 km in size. Using these results, they developed a computationally efficient method to estimate the magnitude of sub-grid (smaller than 200 km) wind variability caused by different physical mechanisms, and to take into account such variability when calculating sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). They found that the impact of sub-grid wind variability on sea salt emission is negligible. In contrast. small-scale air motions associated with localized surface heating or complex topography can cause substantial increases in dust emissions. When these effects are accounted for, the model will either predict a 50% increase in the global and annual mean dust emissions, or predict the same total amount but with more contributions from weaker wind events and fewer contributions from stronger wind events, all depending on how other uncertain parameters in the model are adjusted. The new method of representing wind variability provides the basis for future work on further improving the realism of the simulated, wind-driven aerosol emissions.

Steven J. Ghan
Pacific Northwest National Laboratory (PNNL)
Zhang, K, C Zhao, H Wan, Y Qian, RC Easter, SJ Ghan, K Sakaguchi, and X Liu.  2016.  "Quantifying the Impact of Sub-Grid Surface Wind Variability on Sea Salt and Dust Emissions in CAM5."  Geoscientific Model Development 9: 607-632, doi:10.5194/gmd-9-607-2016.