Empowering weather and climate forecast
This workshop started with an overview on the MAELSTROM project and continued with invited talks by experts from the three domains of machine learning, high-performance computing, and Earth sciences to summarise and disseminate the latest research and developments towards highly efficient, scalable machine learning tools that improve weather and climate predictions. The workshop was hybrid with the ability to join virtually from everywhere in the world and to follow the talks in person at ECMWF in Reading, UK.
We were honored to welcome 200 online participants and 36 in person.
The MAELSTROM Dissemination Workshop was organised back-to-back with the second MAELSTROM Boot Camp.
| 7 November 2023 | ||
|---|---|---|
| MAELSTROM | ||
| 09:00 to 09:30 | An introduction to MAELSTROM Presentation slides |
Peter Düben (ECMWF) |
| 09:30 to 10:00 | Performance models for machine learning Presentation slides |
Karthick Panner Selvam (University of Luxembourg) |
| 10:00 to 10:30 | Experiences with W&C ML Apps on AMD Instinct GPUs Presentation slides |
Stepan Nassyr (Jülich Supercomputing Center) |
| 10:30 to 11:00 | A machine learned weather forecast for Norway Presentation slides |
Thomas Nipen (Norwegian Meteorological Institute) |
| 11:00 to 11:15 | Coffee break | |
| Partner EuroHPC Projects | ||
| 11:15 to 11:45 | SEA-Projects: towards a European heterogeneous system and SW architecture for Exascale and beyond | Hans-Christian Hoppe (Jülich Supercomputing Center) |
| 11:45 to 12:15 | SparCity for Sparse Tensors: Study on Feature Extraction and Smart Tensor Generation Presentation slides |
Tugba Torun (Koç University) |
| 12:15 to 12:45 | Some recent improvements of parallel-in-time algorithm Presentation slides |
Daniel Ruprecht (Hamburg University of Technology) |
| 12:45 to 14:00 | Lunch break | |
| Invited external speakers | ||
| 14:00 to 14:30 | Radiative transfer emulation: results so far and why we should move on to 3D Presentation slides |
Peter Ukkonen (DMI) |
| 14:30 to 15:00 | Deep Learning for regional ensemble forecasting : first results Presentation slides |
Laure Raynaud (Météo-France) |
| 15:00 to 15:30 | AIFS Presentation slides |
Simon Lang (ECMWF) |
| 15:30 to 16:00 | Coffee break | |
| 16:00 to 16:30 | AtmoRep: Large-Scale Representation Learning of Atmospheric Dynamics Presentation slides |
Christian Lessig (ECMWF) |
| 16:30 to 17:00 | Physics-Constrained Deep Learning for Downscaling and Emulation Presentation slides |
Paula Harder (Fraunhofer Institute ITWM) |
| 17:00 to 17:30 | Towards km-scale AI emulation for weather and climate applications Presentation slides |
Karthik Kashinath (NVIDIA) |
| Drinks reception | ||
| 18:00 to 19:30 | Drinks reception in the Weather Room | |
