Earth System Modeling 2.0: Toward Data-Informed Climate Models With Quantified Uncertainties

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Dr. Tapio Schneider

Theodore Y. Wu Professor of Environmental Science and Engineering

California Institute of Technology

Monday November 30, 2020, 2 PM



While climate change is certain, precisely how climate will change is less clear. But breakthroughs in the accuracy of climate projections and in the quantification of their uncertainties are now within reach, thanks to advances in the computational and data sciences and in the availability of Earth observations from space and from the ground. I will survey the design of a new Earth system model (ESM), under development by the Climate Modeling Alliance (CliMA) of Caltech, MIT, Jet Propulsion Laboratory, and the Naval Postgraduate School.  The talk will cover key new concepts in the ESM, including turbulence, convection, and cloud parameterizations and fast and efficient algorithms for assimilating data and quantifying uncertainties through a three-step process involving calibration, emulation, and sampling.


Tapio Schneider is a Professor at Caltech and a Senior Research Scientist at NASA’s Jet Propulsion Laboratory. With his collaborators, he has shown how rainfall extremes intensify as Earth warms, how clouds can change with climate, and how winds and weather on other planetary bodies (e.g., Jupiter and Titan) come about. He is currently leading the Climate Modeling Alliance (, whose mission is to build the first climate model that automatically learns from data, to produce accurate climate predictions.

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Nov 30 2020


UMD WebEx (11/30)


John Xun Yang