Dale Durran’s research spans several areas in atmospheric science including predictability, sub-seasonal forecasting using machine learning, mountain meteorology, atmospheric waves, and numerical methods for the simulation of atmospheric flows. Most recently he has been exploring how deep learning can change our current paradigm for numerical weather prediction.  He is a fellow of the American Meteorological Society and has written numerous scientific publications, a textbook and “perspective” articles for the Washington Post.