Introduction to Deep Learning for Climate Scientists

Session

Day 2

23 Sept 2026, 09:00

Room 034 (DKRZ Main Building)

17. Introduction to PyTorch: Application to climate data | Hands-on 💻

Etienne Plésiat (DKRZ)

23/09/2026, 09:00

• Definition of the task
• Creation of the training, validation and test datasets
• Building the model
• Training the model
• Testing the model

21. Introduction to PyTorch: Application to climate data | Hands-on 💻

Etienne Plésiat (DKRZ)

23/09/2026, 11:00

• Improving the model

13. Introduction to Pytorch Lightning | Hands-on 💻

Caroline Arnold (HEREON)

23/09/2026, 13:30

• Learn the basics of the deep learning framework Pytorch Lightning
• Write deep learning code that is flexible and performant

7. Advanced Deep Learning use-case: Reconstructing missing climate data | Hands-on 💻

Johannes Meuer (DKRZ)

23/09/2026, 14:30

• Design and implement inpainting CNN for reconstructing climate data

14. Advanced Deep Learning use-case: Reconstructing missing climate data | Hands-on 💻

Johannes Meuer (DKRZ)

23/09/2026, 15:30

• Train the model with different configurations
• Validate the model on test data

20. Advanced Deep Learning Use Case: AI Weather Prediction | Lecture 🎓

Caroline Arnold (Hereon), Paul Keil (DKRZ / HEREON)

23/09/2026, 16:30

• Learn about AI weather models that can take it up with numerical weather prediction