In the quest to better understand and address climate change, machine learning (ML) can help researchers investigate massive Earth observation data sets, build predictive models, and better understand how the world around us is impacted by increasing temperatures. Clouds play an intricate role in Earth’s climate, and they are changing due to human behavior. To better understand these changes and their effects, the team chatted with Dr. Philip Stier, professor and head of atmospheric, oceanic, and planetary physics in the department of physics at the University of Oxford, and Dr. Duncan Watson-Parris, a postdoctoral researcher on Dr. Stier’s team. The duo shared how they use ML to track patterns in our clouds and scale their research using Amazon Web Services (AWS). Next, the team checked in with Dr. David John Gagne, an ML scientist at the National Center for Atmospheric Research. David John discusses how ML can help researchers study extreme weather patterns to help decision makers predict and prepare for natural disasters.