CURC User Success Story- Understanding how clouds influence temperature and energy in the atmosphere

Leah’s path into atmospheric science began with a broad interest in physics. As an undergraduate at a liberal arts college, she studied physics but did not initially have opportunities to conduct atmospheric science research. Still, she was motivated by questions about Earth’s changing climate and wanted to contribute to understanding what is happening to the planet and its future. That interest led her to a summer research experience in glaciology, which helped guide her toward atmospheric science and eventually to studying climate processes in the Arctic. 

Today, Leah’s research examines the role clouds play in Arctic climate change. The Arctic has warmed significantly over the past several decades, but scientists are still working to fully understand how clouds contribute to that warming. Clouds can both trap heat and reflect sunlight, meaning they can either warm or cool the Earth depending on the conditions. This dual role makes them one of the largest sources of uncertainty in climate projections. 

To explore this question, Leah analyzes long-term observations collected at a research observatory in Alaska operated by the Atmospheric Radiation Measurement program of the U.S. Department of Energy. The site has been collecting detailed atmospheric measurements since the late 1990s, providing a rare record of how Arctic conditions have changed over time. Because the region has warmed substantially during that period, the dataset offers an opportunity to examine how clouds have behaved during decades of climate change. 

Many studies of Arctic clouds rely on satellite observations or large climate models. Leah’s work takes a complementary approach by focusing on the detailed measurements gathered at this single long-running observatory. By carefully analyzing these observations, she hopes to clarify how clouds influence the Arctic’s changing climate and provide new insights that can help improve climate predictions. 

Working with long-term atmospheric data also requires significant computational resources. Through CURC, Leah uses Alpine to process large observational datasets and analyze measurements from multiple instruments. She ran single-node jobs with parallelization across cores using the subprocess library in Python to efficiently handle large analyses. High-performance computing allows her to organize complex records, test different methods, and identify patterns across decades of data that would be difficult to examine on a standard computer. 

Ultimately, Leah’s goal is to reduce uncertainty about the role of clouds in Arctic warming. By using long-term observational data, her research helps provide clearer constraints for climate models and improves scientists’ understanding of how the Arctic climate is evolving. As the region continues to change rapidly, studies like Leah’s play an important role in helping researchers better understand what those changes mean for the future of the planet.