Overview of the CondensNet physics-constrained AI framework integrated into a global climate model (IMAGE)

National University of Singapore College of Design and Engineering

Overview of the CondensNet physics-constrained AI framework integrated into a global climate model

Caption

Methodology of the CondensNet model. CondensNet is a physically constrained DL parametrisation coupled with a climate dynamics engine to support hybrid modelling. The network architecture mainly has two parts: BasicNet for learning the cloud representation and ConCorrNet for condensation physical constraint.

Credit

NUS College of Design and Engineering

Usage Restrictions

Credit must be given to the creator. Only noncommercial uses of the work are permitted. No derivatives or adaptations of the work are permitted.

License

CC BY-NC-ND

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.