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Atmospheric Sciences & Global Change Division
Research Highlights

July 2011

Looking for Aerosol in All the Right Places

Climate models must account for small-scale aerosol variability

ClimateGrid
High-resolution simulation for Mexico City (top), shows a more detailed and accurate picture of aerosol pollution compared to representations of a global climate model (bottom). The deep red to light green shows representations of high to low concentrations of aerosol pollution. Enlarge Image

Results: Neglecting small details can have a large effect. Atmospheric scientists at Pacific Northwest National Laboratory (PNNL) found that overlooking the small-scale effects of aerosols, those tiny particles of dust or pollution in the atmosphere, can have a negative impact on global climate predictions. The researchers found the difference between their detailed aerosol modeling and the coarse modeling used in modern global climate models was as high as 30 percent during a 2-week period over Mexico City. The study was published in the Journal of Geophysical Research-Atmospheres.

Why it matters: Global climate models calculate atmospheric processes at scales close to 100 by 100 kilometers (62 miles across). Aerosol particles act on much smaller scales and can vary according to local atmospheric or geographic features. In global climate models, the climate effects of these features are often averaged out over the large-scale grid, distorting the actual effects of the processes. Aerosols, which scatter and absorb sunlight, are known to tip the energy balance scales toward heating or cooling, depending on the type of particle and its elevation above the Earth's surface. This study gives climate scientists a more accurate account of aerosols on the small scale, to help predict global climate changes.

Methods: PNNL scientists set out to understand the impact of regional aerosol variability not accounted for in current global climate models. These models assume that aerosol particles are uniformly distributed within each column of the climate model's grid. In reality, there is a lot of regional variability in aerosol characteristics that the models cannot resolve.

The researchers identified small-scale processes that can lead to larger, accumulated errors over time. Using a detailed, high-resolution atmospheric meteorology and aerosol model, combined with extensive observations of aerosol and the surrounding environment, they found that certain kinds of aerosol emissions are likely to cause error due to small-scale fluctuations in atmospheric conditions.

To demonstrate the error from neglected small scales, the team used the change in net flux of sunlight across the top of the atmosphere due to the aerosol, also known as aerosol direct radiative forcing. For a given amount of sunlight entering the atmosphere, aerosol particles reflect a portion of sunlight back to space, absorb some, and allow the remaining light to reach the ground.

"This net flux quantity is important because it directly relates to changes in the atmosphere's energy balance, and therefore the potential impact of the aerosol on atmospheric temperatures and climate," said climate researcher Bill Gustafson, principal author of the study.

The team found that this amount, the aerosol direct radiative forcing for portions of Mexico, differed by over 30 percent when models neglect the small-scale processes affecting aerosol.

This study used several tools developed at PNNL in combination with data from the MILAGRO field campaign to test and validate the models. The Weather and Research Forecasting (WRF-Chem) model is a meteorology model that contains an aerosol module called Model for Simulating Aerosol Interactions and Chemistry (MOSAIC), which was developed at PNNL and contributed to the scientific community in the WRF-Chem model. The model simulations were verified against observations using the Aerosol Modeling Testbed toolkit, which was developed at PNNL under a Laboratory Directed Research and Development program called the Aerosol Climate Initiative.

What's next: Based on these findings and additional work that will further pinpoint the causes of the error identified in this study, the researchers will develop techniques to reduce the error in the climate models.

Acknowledgments: This research was funded by the U.S. Department of Energy Atmospheric System Research Program. A portion of Dr. Gustafson's support was provided through an award from the DOE Early Career Research Program. Computational resources were provided by the National Energy Research Scientific Computing Center, a national scientific user facility located at Lawrence Berkeley National Laboratory. A portion of the research was performed using the Environmental Molecular Sciences Laboratory, a U.S. Department of Energy national scientific user facility located at PNNL. The work was performed by Drs. William I. Gustafson, Jr., Yun Qian, and Jerome D. Fast of PNNL.

Reference: Gustafson Jr. WI, Y Qian, and JD Fast. "Downscaling Aerosols and the Impact of Neglected Subgrid Processes on Direct Aerosol Radiative Forcing for a Representative GCM Grid Spacing." Journal of Geophysical Research-Atmospheres, 116, D13303, 28 PP., 2011. DOI:10.1029/2010JD015480.


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