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Publication Date
28 December 2014

The Bright Side of Arctic Clouds

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For the first time, modeling research led by Pacific Northwest National Laboratory found that atmospheric particles can brighten cold clouds in the Arctic. Using simulations, they showed that low clouds over the Arctic may be brightened by deliberately injecting small particles known as aerosols. It's already well known that injecting aerosols into low clouds over the warm ocean can, in some circumstances, reduce the amount of sunlight that reaches the surface. The concept, untested in modeling over the Arctic until now, is called marine cloud brightening, and it can also happen when ships send exhaust into the atmosphere.

The modeling simulations by PNNL and collaborators at the National Center for Atmospheric Research (NCAR) and the National Oceanic and Atmospheric Administration (NOAA) used computer modeling to show that Arctic cloud brightening could have considerable local climate effects, but likely would not substantially alter the global energy balance.


Pacific Northwest National Laboratory researchers and their collaborators used the Weather Research and Forecasting Model (WRF), a leading community atmospheric model that can resolve clouds and represent many of the complex microphysical interactions between clouds and aerosols. They ran eight cases, in clean to polluted atmospheres, and simulated injection of aerosol particles into the atmosphere. Their simulations showed the particle impacts in a wide variety of background conditions.


Propositions to shoot sea salt or other tiny particles into low clouds over the ocean have been tested in computer models over temperate regions. Brighter clouds reflect more of the sun's energy back into space, shading and cooling the surface. The concept would amp up a process that happens naturally when sea spray is lofted into the atmosphere from ocean waves. The research team wanted to know, would the same concept work over the Arctic? The answer could matter for the climate, if geoengineering techniques—proposed by some as a temporary way of reducing the climate effects of greenhouse gases while mitigation is in progress—are ever put into practice.

This is the first study to look at process modeling of marine cloud brightening in the Arctic.


Aerosol-cloud interactions, including aerosol indirect effects, are responsible for some of the largest sources of uncertainty in computing the global radiation budget. The first aerosol indirect effect, also called the cloud albedo effect, refers to the consequences of adding aerosols that act as cloud condensation nuclei (CCN) to clouds under an assumption of fixed liquid water path. For the first time, a team led by U.S. Department of Energy scientists at Pacific Northwest National Laboratory simulated the effectiveness of Arctic marine cloud brightening via injection of CCN. The research found that the injection of aerosols into the Arctic marine boundary layer, either deliberately (geoengineering) or due to other mechanisms that would increase CCN in the Arctic region, has the potential to brighten low clouds. Using a cloud-resolving model, they found liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. Injection of CCN into a relatively unpolluted environment results in greater albedo increases than injection into polluted environments, consistent with current knowledge about aerosol-cloud interactions. Process-modeling studies can be useful in determining some of the behaviors and underlying physical mechanisms behind natural and anthropogenic emissions of CCN into Arctic marine low clouds.

Point of Contact
Ben Kravitz
Pacific Northwest National Laboratory (PNNL)
Funding Program Area(s)

Sponsors: This research was supported by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research's Earth System Modeling program. Additional support was provided by the Fund for Innovative Climate and Energy Research (FICER). 

Research Team: Ben Kravitz, Hailong Wang, and Philip J. Rasch, PNNL; Hugh Morrison, NCAR; Amy B. Solomon, University of Colorado and NOAA.