Title: "Regional predictions of extreme precipitation under climate change: a role for both dynamical understanding and machine learning"
Abstract: Extreme precipitation is predicted to increase in intensity with global warming, but the rate of increase varies widely across different regions of the world. For example, global climate models predict a markedly weak response in summer for North America but a strong response over India. In this talk I will first discuss efforts to understand the dynamical factors contributing to changes in extreme precipitation. I will then describe new approaches using machine learning that have the potential to improve the simulation of extreme precipitation and other aspects of the climate system.
Short bio: Paul O'Gorman is a Professor of Atmospheric Science at MIT. His research interests are in the dynamics of the atmosphere, the hydrological cycle, and climate change. Recent work has focused on the response of precipitation to climate change, the behavior of extratropical storm in warm and moist atmospheres, and the potential of machine learning in climate modeling.