This was part of Assessing the Economic and Environmental Consequences of Climate Change

Towards Digital Twins for NVIDIA’s Earth-2 Initiative: Pushing the Limits of Deep Learning for Earth System Emulation

Karthik Kashinath, NVIDIA

Saturday, April 1, 2023


NVIDIA is committed to helping the scientific community address climate change and the energy transition. In Nov. 2021, our CEO announced the Earth-2 initiative, which aims to build digital twins of the Earth. Two central goals of this initiative are: (i) Computational: enable high-resolution hybrid climate-ML predictions with credible cloud physics via NVIDIA Modulus; and (ii) Societal: nimbly serve interactive, high-fidelity, high-resolution climate predictions via NVIDIA Omniverse. Next-generation km-scale climate simulations are the most credible ground truth envisioned for future climate change, but such simulations are prohibitively expensive, account for sizable carbon production into the atmosphere, and generate unmanageable amounts of output given that hundreds of diverse climate trajectories are needed to sample the long tails of risk. Therefore, the above-mentioned goals depend on achieving orders-of-magnitude speedup and data compression via a combination of advances in AI and computing technologies. 


NVIDIA sees potential to accelerate this work through collaborations with the climate science community and by bringing to bear its deep learning and data engineering expertise and HPC system deployments. Professional ML engineering pipelines – like those behind NVIDIA’s Modulus and Omniverse – have not been widely exploited in hybrid physics-ML climate simulation and Earth system emulation. For weather, the potential is already clear: AI-driven weather emulators show remarkably skillful data-driven high-resolution global weather predictions. Eventually the goal is for similar, high-fidelity digital twins of future Earth system processes to allow climate scientists, and non-expert users to interact more easily with the wealth of information in km-scale climate simulations and ML model predictions, facilitating planning and decision-making in climate monitoring, modeling, mitigation, and adaptation. We conclude with a roadmap of Earth-2 and its climate goals, and the engineering innovations required for the breakthroughs that building digital twins of the Earth demands.