Artificial Intelligence, and in particular machine learning, is becoming an essential tool for climate modelling. Earth observation data such as satellite observation contribute to a growing record of climate change and weather events, which can be used to build or improve climate models. Deep learning in particular has been widely used in weather forecasting and climate event prediction, such as ENSO. However, other forms of machine learning offer benefits such as interpretability and the integration of physical knowledge from existing climate models. In this Special Session, we invite works on the use of AI for Climate Science; works on climate model parameter optimization, machine learning for climate science, and automated analysis of climate data are welcome.
The AI for Climate Science Special Session will be held as a part of the WCCI in Yokohama, Japan from June 30 to July 5, 2024. Details about submission and important dates can be found on their website. Please note that the Special Session may be indicated as “AI for Climate Models” in the submission system.
Scope
We invite submissions that present recent developments in AI for Climate Science. The interdisciplinary scope of the Special Session includes the use of AI in the following topics:
- climate models
- climate forecasting
- Earth observation
- ecosystem monitoring
- hybrid data and physics models
- weather forecasting
- extreme weather events
- oceans and marine systems
All AI techniques are welcome, from evolutionary computation to deep learning. Submissions should focus on the impact of AI to climate science and highlight the relationship to climate change. We encourage submissions to make their data and code publicly available.
Organizers
Dennis G. Wilson
email
ISAE-Supaero, University of Toulouse, France
https://pagespro.isae-supaero.fr/dennis-wilson
Dennis Wilson is Associate Professor of AI and Data Science at ISAE-Supaero, University of Toulouse. He began his research career at CSAIL, MIT and obtained his PhD at IRIT, University of Toulouse. His research interests involve evolutionary computation and deep learning and the use of these methods in environmental applications.
Swadhin Behera
JAMSTEC
https://www.jamstec.go.jp/apl/j/members/behera/
Swadhin K. Behera is a leading scientist in global ocean and climate research, especially he is known for discoveries of several modes of tropical and extratropical climate variations such as IOD and IOSD. After obtaining a Ph. D. degree from India and working for about 10 years in Indian Institute of Tropical Meteorology, he moved to JAMSTEC in 1998. Since then he has been associated with various centers and programs of JAMSTEC and currently heads the Application Laboratory.