The Frontiers of Deep Learning for Earth System Modelling
This talk gives an overview of cutting-edge artificial intelligence applications and techniques for the earth-system sciences. We survey the most important recent contributions in areas including extreme weather, physics emulation, nowcasting, medium-range forecasting, uncertainty quantification, bias-correction, generative adversarial networks, data in-painting, network-HPC coupling, physics-informed neural nets, and geoengineering, amongst others. Then, we describe recent AI breakthroughs that have the potential to be of greatest benefit to the geosciences. We also discuss major open challenges in AI for science and their potential solutions. This talk is a living document, in that it is updated frequently, in order to accurately relect this rapidly changing field.
How to cite: Hall, D.: The Frontiers of Deep Learning for Earth System Modelling , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12541, https://doi.org/10.5194/egusphere-egu21-12541, 2021.
Corresponding presentation materials formerly uploaded have been withdrawn.