29 February 2016

An Improved Minimal Representation of Aerosols for Climate Models

Summary

Aerosol particles are complicated because they come in a variety of shapes, sizes, and compositions. Simplifications are necessary to represent them in climate models designed to simulate hundreds of years of climate change. A previous minimal representation of that complexity in a community climate model assumed all particles are spheres in three size modes each composed of mixtures of sulfate, organic carbon, black carbon, dust, and sea salt.  Simulated carbonaceous (carbon-containing) aerosol concentrations with that treatment had been vastly underestimated. It is important to get those concentrations right, because much of the carbonaceous aerosol is produced by human activities (primarily, burning fossil fuels) and can change the energy balance of the Earth.

To improve those representations, a team including researchers at the University of Wyoming and Department of Energy scientists at Pacific Northwest National Laboratory added a fourth mode to a popular representation of the aerosol. The fourth mode is assumed to be composed only of organic carbon and black carbon, but the fresh carbon can age by condensation of sulfuric acid and organic vapors and by coagulation with aged particles. Aging transfers carbonaceous aerosol from the fresh mode to the aged mode. The team compared aerosol concentrations simulated with the four-mode and the old three-mode treatments with measurements across the world. The new mode accounts for the fact that fresh smoke is composed almost entirely of organic carbon and black carbon, which are not washed out from the atmosphere quickly and hence can be transported much farther from sources to remote regions. The new treatment simulates the global distribution of carbonaceous aerosol much more realistically without adding much to the time running simulations. Because not all carbonaceous aerosols are alike, the team will next consider how to distinguish between organic carbon from fires and from vehicles.

Contact
Steven J. Ghan
Pacific Northwest National Laboratory
Acknowledgments

This work was supported by the U.S. Department of Energy, Office of Biological and Environmental Research, Earth System Modeling Program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. The National Center for Atmospheric Research is funded by the National Science Foundation.