Progress and Challenges for the Use of Deep Learning to Improve Weather Forecasts - insideHPC

In this video from the UK HPC Conference, Peter Dueben from ECMWF presents: Progress and Challenges for the Use of Deep Learning to Improve Weather Forecasts. I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will then talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future. Peter Dueben is a Royal Society University Research Fellow at the European Centre for Medium-Range Weather Forecasts (ECMWF). He is contributing to the development and optimization of weather and climate models for modern supercomputers.