Description:

The field of weather & climate science has seen a tremendous rise in the use of AI techniques for modeling and simulation. The integration of AI with characterization and prediction frameworks for weather and climate has led to myriad advances in accurate and computationally cheap modeling efforts. Nonetheless, along with these advantages, there is a pressing need for stable, robust, and interpretable use of AI techniques in order to establish trustworthiness of such models amongst climate scientists. This is critical for augmenting such modeling efforts with production level modeling and simulation tools.

Recent trends in AI-based modeling of earth, atmosphere, and ocean systems have seen application of robust modeling techniques which are physically interpretable as well. Quantifying the uncertainty of the models has also motivated an increase in the confidence of the AI models. These efforts, combined with trends in AI research and hardware tools for AI workflows, are bound to pave the way for significant advances in modeling and simulation of weather and climate.

This session will serve as a platform to discuss the latest trends in modeling efforts in the field of weather and climate science using AI. The various topics discussed in this session will explore the current and future direction of research for this field. Moreover, we aim to provide an avenue to foster collaborations to advance the state of research in AI-based modeling of weather and climate.