09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
21:00
22:00
9:00 - 10:30 (1h30)
Machine learning
Auditório Jacy Monteiro
› Modeling global surface dust deposition using physics-informed neural networks
- Elwin Van 't Wout, Institute for Mathematical and Computational Engineering, Pontificia Universidad Católica de Chile
09:00-09:30 (30min)
› Leveraging machine learning for improved numerical weather prediction through large-scale spectral nudging
- Syed Zahid Husain, Environment and Climate Change Canada
09:30-10:00 (30min)
› Hybrid Models for Extreme Meteorological Events
- Haroldo Campos Velho, National Institute for Space Research
10:00-10:30 (30min)
10:30 - 11:00 (30min)
Coffee break
Auditório Jacy Monteiro
11:00 - 12:30 (1h30)
Machine learning
Auditório Jacy Monteiro
› Satellite Data Assimilation by EnKF and Cellular Neural Network for Global models
- Cesar Magno Oliveira Junior, Universidade de São Paulo
11:00-11:30 (30min)
› Deep Learning for Super-Resolution in ICON-O
- Fabricio Rodrigues Lapolli, Max-Planck-Institut für Meteorologie
11:30-12:00 (30min)
› Foundational AI for Solving PDEs and Systems on the Sphere
- Christopher Pain, Applied Modelling and Computation Group, Imperial College London - Boyang Chen, Applied Modelling and Computation Group, Imperial College London (online)
12:00-12:30 (30min)
12:30 - 14:00 (1h30)
Lunch
Restaurants
14:00 - 15:30 (1h30)
Related Topics
Auditório Jacy Monteiro
› U-Net type convolutional neural network for data assimilation
- Gerônimo Lemos, Instituto Nacional de Pesquisas Espaciais
14:00-14:30 (30min)
› Poseidon: A Source-to-Source Compiler for Optimizing Ocean Simulation Models on Modern HPC Architectures
- Martin Schreiber, Université Grenoble Alpes
14:30-15:00 (30min)
15:30 - 16:00 (30min)
Coffee break
Auditório Jacy Monteiro
›16:00 (45min)
› Auditório Jacy Monteiro
16:00 - 16:45 (45min)
Future Perspectives of Machine Learning use in Weather, Ocean and Climate Models.
Auditório Jacy Monteiro
Discussion
›18:30 (3h30)
18:30 - 22:00 (3h30)
Dinner
