Weather, climate and machines that learn
The term “artificial intelligence” may not immediately conjure associations with the warming of Earth’s atmosphere. But now more than ever, climate researchers are turning to trainable, data-nimble computer programs as tools for improving climate models, weather forecasting and more.
Nowhere is this truer than in the lab of Elizabeth (Libby) Barnes, associate professor in the Colorado State University Department of Atmospheric Science. Barnes is a climate scientist who studies global atmospheric dynamics and variability, in part for making skillful, accurate predictions of weather weeks in advance.
These days, Barnes is just as quick to call herself a data scientist. She believes climate science is well positioned to harness machine learning methods to uncover new knowledge about how the global climate functions, how it’s changing, and why.
Read the full Source article, “Atmospheric science, meet data science.”
Photo at top: Imme Ebert-Uphoff and Libby Barnes at the atmospheric science campus. Photo by Bill Cotton