CSU-led team receives $600,000 grant to uncover mysteries of cloud formation

Understanding the behavior of clouds is central to improving weather analysis and better assessing the impact of climate change and air pollution. However, we still know very little about how clouds react to changes in the atmospheric boundary layer, the lowest part of the atmosphere, making predictive modeling complicated at best. Thijs Heus, an assistant professor of physics at Cleveland State University, has received a $600,000 grant from the U.S. Department of Energy to address this challenge. The project seeks to better model cloud size and enhance understanding of how small and large clouds impact solar reflectivity, vertical transport of heat and moisture, as well as precipitation.

“Clouds are one of the biggest mysteries in earth science and our lack of knowledge is a central hindrance to better weather predication and climate modeling,” Heus says. “By studying how clouds, of all sizes, act in the real world we hope to make predictions more accurate and informative to scientists, environmentalists and policy makers.”

Heus notes that most weather and climate models have resolutions in the kilometers, making a good representation of smaller clouds difficult. Heus is working with the Ohio Supercomputing Center to perform incredibly realistic, large eddy simulations which have resolutions of about 10 meters, allowing the team to model fluctuations in temperature, humidity and barometric pressure over different areas simultaneously. At the same time, Heus and his partners at the University of Cologne in Germany will use observations using LIDAR and radiometer data to better assess how clouds actually move and develop.

The team will use the combined data collected to create a much more accurate mathematical model of cloud formation and change. Heus hopes the model can ultimately be incorporated into climate prediction processes, greatly improving analysis of how weather patterns are changing due to the warming of the planet.

“Simply stated, better data will lead to better climate prediction,” Heus adds.

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