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Aerosol clouds cool earth.

Atmospheric scientists have developed simple, physics-based equations that address some of the limitations of current methods for representing cloud formation in global climate models--important because of increased aerosol pollution that gives clouds more cooling power and affects precipitation. These researchers--led by the Georgia Institute of Technology, Atlanta, National Science Foundation, National Oceanic and Atmospheric Administration, and NASA--also have developed a new instrument for measuring the conditions and time needed for a particle to become a cloud droplet. This will help scientists determine how various types of emissions affect cloud formation.

Clouds play a critical role in climate, notes Athanasios Nenes, a professor in Georgia Tech's School of Earth and Atmospheric Sciences and the School of Chemical and Biomolecular Engineering. Low, thick ones cool the Earth by reflecting solar radiation whereas high, thin clouds have warming properties by trapping infrared radiation emitted by the Earth.

Scientists have learned that human activities influence cloud formation. Airborne particles released by smokestacks, charcoal grills, and car exhausts restrict the growth of cloud droplets, causing condensing water to spread out among a larger number of smaller droplets. Known as the "indirect aerosol effect" this gives clouds more surface area and reflectivity, which translates into greater cooling power. The clouds also may have less chance of forming rain, which allows them to remain longer for cooling.

"Of all the components of climate change, the indirect aerosol effect has the greatest potential cooling effect, yet quantitative estimates are highly uncertain" Nenes notes. "We need to get more rigorous and accurate representation of how particles modify cloud properties. Until the indirect aerosol effect is well understood, society is incapable of assessing its impact on future climate."

Current computer climate models cannot predict cloud formation accurately, which, in turn, hinders their ability to forecast climate change from human activities. "Because of their coarse resolution, computer models produce values on large spatial scales [hundreds of kilometers] and can only represent large cloud systems."

Aerosol particles, however, are extremely small and are measured in micrometers. This means predictive models must address processes taking place on a very broad range of scale. "Equations that describe cloud formation simply cannot be implemented in climate models," Nenes points out. "We don't have enough computing power--and probably won't for another 50 years. Yet, somehow we still need to describe cloud formation accurately if we want to understand how humans are affecting climate."

Scientists have tried to predict cloud formation through empirical "parameterization"--techniques that rely on empirical information or correlations, such as comparing the number of particles in the atmosphere with the number of cloud droplets. "Yet, there's no real physical link, no causality between those two numbers" Nenes relates.

To address the lack of computer power and shortcomings of existing parameterization, Nenes and his research team have developed simple, physics-based equations that link aerosol particles and cloud droplets. Then these offline equations can be scaled up to a global level, providing accurate predictions literally thousands of times faster than more detailed models. For example, by determining an algebraic equation for maximum supersaturation (the point in a cloud where all droplets that could form, have formed), it becomes possible to calculate how many cloud droplets can form. That droplet number reveals the optical (reflective) property of a cloud, as well as its potential for forming rain.

Another key challenge in predicting climate change is to understand how aerosols' chemistry affects cloud formation. Each particle has a different potential for forming a cloud drop, which depends on its composition, location, and how long it has been in the atmosphere. Up until now, meteorologists have measured and averaged properties over long periods of time. "Yet, particles are mixing and changing quickly," Nenes explains. "If you don't factor in the chemical aging of the aerosol, you can easily have a large error when predicting cloud droplet number."

Working with Gregory Roberts at the Scripps Institution of Oceanography, Nenes developed a new type of cloud condensation nuclei (CCN) counter. This instrument exposes different aerosol particles to a supersaturation, which enables researchers to determine how many droplets form and how long they take to form. The CCN counter can be used on the ground or in aircraft. "It gives us a much needed link for determining how different types of emissions will affect cloud formation," Nenes reports.

The new modeling method and CCN instrument have far-reaching applications for predicting climate change and precipitation patterns. The indirect aerosol effect is counteracting greenhouse warming right now, but this will stop at some point. "One of our goals as scientists is to figure out how long we'll have this cooling effect so that we can respond to changes," Nenes concludes. "Being able to predict climate change can help countries with sustainability--from agricultural planning to global emission policies."
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Title Annotation:Meteorology
Publication:USA Today (Magazine)
Geographic Code:1USA
Date:Jun 1, 2005
Words:794
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