Deep Learning Model Development in Weather and Climate Studies
Event description
Join NCI experts to discover how deep learning is reshaping weather and climate science, and gain the skills you need to start exploring these powerful approaches in your own work. This online workshop includes a public webinar, followed by optional on-demand hands-on sessions (see "Format" section for details).
The webinar session will provide an overview of recent developments in the field, showcasing several state-of-the-art weather and climate models and the resources available at NCI to support the Australian research community in advancing deep learning applications and scientific understanding.
Participants will also be introduced to the NCI Inference Server, which enables skill comparisons across models and performance benchmarking. The session offers an opportunity to provide feedback on example models, suggest improvements, and share your needs for future support. We also invite you to tell us which models or algorithms you are currently using or interested in exploring.
The hands-on sessions (prerequisites apply) will take a deeper dive to the technical details using Jupyter notebooks. Tailored for environmental data, these sessions will explore example network architectures, training and inference strategies used in example models.
Format
You can choose to attend the webinar only.
You must attend the webinar in order to get the most out of the hands-on workshop.
30 October 2025 | 1 pm - 4 pm (AEDT) | Webinar | All welcome |
6 November 2025 | 1 pm - 3:30 pm (AEDT) | Hands-On Session | Check prerequisites below |
Who Should Attend
Webinar
The webinar content is developed with weather and climate researchers in mind but anyone who is curious about the topic is welcome.
Hands-on Sessions
People using or interested in training, fine-tuning or using deep learning models for weather and climate problems, including but not limited to:
Weather and climate researchers and practitioners
Research software engineers
Higher Degree Research students
Prerequisites
Basic background in climate and weather science.
Familiar with deep learning concepts.
Have Python programming for scientific data analysis experience.
Attended the webinar session
Agenda
Thursday 30 October 2025, AEDT | Webinar | |
1:05 pm - 1:10 pm | Dr. Rui Yang | Opening |
1:10 pm - 1:30 pm | Dr. Yue Sun | A Gentle Introduction to Deep Learning Models |
1:30 pm - 2:00 pm | Dr. Maruf Ahmed (Hands-on session available for these models) | AIFS-single AIFS-CRPS GenCast FourCastNet3 |
2:00 pm - 2:15 pm | Dr. Edison Guo | BARRADiff |
2:15 pm - 2:30 pm | Tea Break | |
2:30 pm - 3:00 pm | Dr. Yue Sun (Hands-on session available for these models) | LUCIE: a lightweight uncoupled climate emulator costs <500SU to train. Aardvark Weather: an end-to-end model which takes in observations from satellites, weather stations and weather balloons, and produces a ten-day global forecast. |
3:00 pm - 3:30 pm | Dr. Rui Yang | More NCI Support
|
3:30 pm - 4:00 pm | Dr. Yue Sun | Discussions
|
Thursday 6 November 2025, AEDT | Hands-On Session | |
1 pm - 1:30 pm | Zhuochen Wu | Cluster access setup using ARE |
1:30 pm - 3 pm | Dr. Yue Sun |
|
3 pm - 3:30 pm | Dr. Maruf Ahmed | AIFS-Single-v1.1 Demo |
Recordings
This event will NOT be recorded.
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