Christopher Irrgang - Towards neural Earth system modelling by integrating artificial intelligence in Earth system science

Event type: 
Seminar
Date: 
29 September 2021
Time: 
2.00pm - 3.00pm
Location: 

Online

Presenter: 
Dr. Christopher Irrgang
Helmholtz Centre Potsdam, German Research Centre for Geosciences GFZ, Potsdam, Germany
Host: 
Climate Change Research Centre

Earth system models (ESMs) are our main tools for quantifying the physical state of the Earth and predicting how it might change in the future under ongoing anthropogenic forcing. In recent years, however, artificial intelligence (AI) methods have been increasingly used to augment or even replace classical ESM tasks, raising hopes that AI could solve some of the grand challenges of climate science. In this perspective, we survey the recent achievements and limitations of both process-based models and AI in Earth system and climate research, and propose a methodological transformation in which deep neural networks and ESMs are dismantled as individual approaches and reassembled as learning, self-validating and interpretable ESM–network hybrids. Following this path, we coin the term neural Earth system modelling. We examine the concurrent potential and pitfalls of neural Earth system modelling and discuss the open question of whether AI can bolster ESMs or even ultimately render them obsolete.

Speaker Biography:Christopher obtained his PhD from the Free University of Berlin in 2017. His PhD thesis was titled ‘Characterization of oceanic signatures in the Earth’s magnetic field in view of their applicability as ocean model constraints’. After completing his PhD, he started a postdoc position at Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences where he started working on the application and integration of machine learning in Earth System Modelling. Now, he increasingly focuses on a generalized development of self-validating, physically consistent, and interpretable hybrids of neural networks and different Earth system models.