Chris Bretherton is an atmospheric scientist who studies cloud formation and turbulence and improves how they are simulated in global climate and weather forecast models. His group at UW helped lead field experiments and observational analyses. He pioneered new frontiers in three-dimensional modeling of fluid flow in and around fields of clouds, including understanding how clouds will respond to and feed back on climate change. Computer code developed by his research group for simulating cloud formation by atmospheric turbulence is used in the two leading US climate models. Since 2016, he has developed machine learning strategies for parameterization of cloud processes in climate models, and he has applied global cloud-resolving modeling to improve the representation of clouds, aerosol and precipitation processes both through ML and conventional parameterization evaluation and improvement.
He has now retired from UW (while still advising selected research initiatives) to co-lead a philanthropically-supported initiative to use machine learning to improve the simulation of regional precipitation trends and extremes in climate models. This initiative was started in 2019 at Vulcan Inc. and (since 9/2021) is continuing at AI2 in Seattle, in collaboration with NOAA GFDL.
He was a lead author of the Intergovernmental Panel on Climate Change Fifth Assessment Report in 2013, Chair of a 2012 National Academy report entitled A National Strategy for Advancing Climate Modeling, and a former director of the University of Washington Program on Climate Change. In 2012, he received the Jule G. Charney Award, one of the two highest career awards of the American Meteorological Society, and he was the 2019 AMS Haurwitz Lecturer. He is a Fellow of the AMS and AGU, and a member of the National Academy of Sciences and Washington State Academy of Sciences.