Dr Philipp Hess

My work focuses on combining machine learning methods with process-based weather and climate models. I am particularly interested in applications of generative machine learning methods for improving weather prediction and long-term climate simulations, such as dynamical emulation, downscaling, bias correction, and subgrid-scale parameterization.