Karen McKinnon studies large-scale climate variability and change, with a particular focus on connections to high-impact weather events. Her most recent work is modeling and understanding internal variability in surface temperature and precipitation, the predictability of extreme events, and the joint behavior of temperature and humidity in a changing climate. She is interested in developing novel statistical and computational methods to optimally gain insight from historical observations, climate model simulations, and the paleo proxy record, as well as linking climate science insights to actionable changes.
Before joining UCLA in November of 2018, Karen was an Applied Scientist at Descartes Labs, and an Advanced Study Program post-doctoral fellow at the National Center for Atmospheric Research. She received her PhD in 2015 from Harvard, working with Peter Huybers.