Abstract: 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), developed by the Climate Modeling Alliance (CliMA). The talk will cover key new concepts, including how data assimilation (DA) and machine learning (ML) can inform physics-based models with heterogeneous and noisy data and how ML can be used to accelerate DA and uncertainty quantification algorithms by a factor 1000.