The development of a digital twin of the Earth that can harness more data than ever before to increase the accuracy of climate models and make them more useful for communities and other stakeholders.

Anthropogenic climate change will reshape our world, but we lack sufficiently accurate and useful projections of how. The goal of this grand challenge is to provide accurate and actionable scientific information to decision-makers to inform the most effective mitigation and adaptation strategies. We envision a novel platform that leapfrogs existing climate decision support tools by leveraging advances in computational and data sciences to improve the accuracy of climate models, quantify their uncertainty, and addresses the trade-off between performance and computation time with attention to industry and government stakeholder needs. First, we will develop a digital twin of the Earth that harnesses more data than ever before to reduce and quantify uncertainties in climate projections. To serve the needs of stakeholders, we will develop emulators of the digital twin tailored to maintain the highest possible accuracy in predicting specific variables, like droughts, floods, or heat waves, while still being easy and fast to run.

Leadership: Rafaele Ferrari, Noelle Selin

MIT Joint Program-affiliated contributors: Noelle Selin, C. Adam Schlosser, Arlene Fiore, Christopher Knittel, John Marshall 

Project Website