Climate Action Programme lecture AI for Climate

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"Machine-learning for understanding atmospheric physics" by Geet George and Jing Sun

The talk will highlight multiple ways in which machine learning tools have been applied on top of traditional methods, with the goal of understanding the physics of the climate system. We will go through a couple of case-studies and end on some of the flagship’s research ideas for applying AI to climate science.

Dr. Geet George is an Assistant Professor at the Geoscience and Remote Sensing department in the Faculty of Civil Engineering and Geosciences. He studies the interactions between tropical clouds and atmospheric circulation across different scales. Commonly termed as “clouds-circulation coupling”, this is a large gap in our knowledge of climate physics, which is apparent in the uncertainties it brings into current climate projections. To demystify the interactions between clouds and circulations, Geet mainly uses measurements from satellites and from field-campaign platforms like aircraft and ships.

Dr. Jing Sun, an Assistant Professor in the Intelligent Systems Department at the Faculty of Electrical Engineering, Mathematics, and Computer Science, focuses her research on developing reliable AI with physics or domain knowledge informed to tackle climate research challenges and address geophysical problems. With a research background in analyzing various types of geophysical data, including seismic, magnetic, and electromagnetic—key to understanding the Earth's subsurface structures and physical properties—she is expanding her expertise to include leveraging satellite data for understanding the surface, atmosphere, and oceans of the Earth.