Engineering A high-res CLIMATE VISION

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NVIDIA Earth-2

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NVIDIA's Earth-2 is a digital twin cloud platform that combines the power of AI, physical simulations and computer graphics technologies to enable the next generation of climate tech applications that can simulate and visualize weather and climate predictions at a global scale with unprecedented accuracy and speed.

Simulating our weather and climate is critical for understanding, preparing, and planning to mitigate climate change.

  • Why this matters

    The idea of being able to limit the loss of life and capital by being better prepared for extreme events drives NVIDIA's work. Their hope is to enable greater access and agency to all stakeholders, to leverage GPU technology for enabling simulation, and AI to explore, understand, and address climate change.

  • What you can do

    Try the NVIDIA Earth-2 Interactive Visualization on Graphics Delivery Network (GDN) to see how the Earth-2 platform enables interactive exploration of high-resolution weather and climate simulation datasets. This demo can be easily explored from any device, bringing worldwide access to these high-resolution insights for science, outreach, and education.

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  • 12x higher resolution

    12x 

    Higher resolution

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    700,000X

    Accelerated analysis

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    1000X

    Less energy consumption  

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Accelerating Carbon Capture and Storage with Fourier Neural Operator and NVIDIA Modulus

By accelerating analysis 700,000X, NVIDIA Omniverse and Modulus can help engineers with planning and operating carbon capture and storage, ensuring safe operation and long-term storage and reducing the amount of carbon dioxide released into our atmosphere.
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Visualize AI-Augmented Weather Simulations

Researchers are using interactive visualization of AI weather forecasts, simulation data, and archived data to analyze extreme weather.
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Earth-2 Data - DKRZ/ MPI-M, ICON model

Built on NVIDIA Omniverse and the OpenUSD 3D framework, the NVIDIA Earth-2 platform enables aggregation and visualization of diverse, global-scale climate simulation and geospatial datasets.

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Predicting Extreme Weather Events Three Weeks in Advance With FourCastNet

By running FourCastNet in NVIDIA Modulus, we were able to generate 21-day weather trajectories of 1,000 ensemble members in a tenth of the time it previously took to do a single ensemble—and with 1,000X less energy consumption.
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