Peter Dueben: The digital revolution of Earth system modelling

This talk will outline three revolutions that happened in Earth system modelling in the past decades. 

The quiet revolution has leveraged better observations and more compute power to allow for constant improvements of prediction quality of the last decades, the digital revolution has enabled us to perform km-scale simulations on modern supercomputers that further increase the quality of our models, and the machine learning revolution has now shown that machine-learned weather models are competitive with physics based weather models for many forecast scores while being easier, smaller and cheaper. 

This talk will summarize the past developments, explain current challenges and opportunities, and outline how the future of Earth system modelling will look like. In particular, regarding machine-learned foundation models in a physical domain such as Earth system modelling.

Peter is the Head of the Earth System Modelling Section at the European Centre for Medium Range Weather Forecasts (ECMWF) developing one of the world’s leading global weather forecast models — The Integrated Forecasting System (IFS). He is also a Honorary Professor at the University of Cologne.

Before, he was AI and Machine Learning Coordinator at ECMWF and University Research Fellow of the Royal Society performing research towards the use of machine learning, high-performance computing, and reduced numerical precision in weather and climate simulations. Peter is coordinator of the WeatherGenerator Horizon Europe project that aims to build a machine-learned foundation model for weather and climate applications and has been the coordinator of the MAELSTROM EuroHPC-Joint Undertaking project.