NVIDIA Earth-2 Platform for Climate Change Modeling

Platform for developing accelerated, AI-augmented, high-resolution climate and weather solutions with interactive visualization.

NVIDIA Earth-2 combines the power of AI, GPU acceleration, physical simulations, and computer graphics to develop applications that can simulate and visualize weather and climate predictions at a global scale with unprecedented accuracy and speed. The platform consists of development tools, microservices, and reference implementations for AI, visualization, and simulation. NVIDIA NIM™ microservices for Earth-2 allow users to leverage AI-accelerated models to optimize and simulate real-world outcomes for climate and weather.

With Earth-2’s AI tools and microservices, climate and weather application developers can leverage reference AI inference pipelines using pretrained models and training pipelines and NVIDIA PhysicsNeMo for fine-tuning with custom data. Earth-2 offers a portfolio of community models. These models are transformational in their ability to efficiently generate large ensembles or high-resolution predictions by downscaling.

Interactive visualization microservices enable large-scale weather and climate data to be visualized and analyzed. NVIDIA Omniverse™ Blueprint for Earth-2 weather analytics showcases how developers can use the Omniverse SDK and microservices to build NVIDIA RTX™-powered visualization pipelines for rendering geospatial and weather data. The blueprint also provides a template for partners to integrate their data platforms into AI pipelines.

Simulation microservices will make it possible to encapsulate, orchestrate, and accelerate numerical weather prediction (NWP) models on NVIDIA GPU platforms.

Python-based GPU-accelerated package designed to quickly get users up and running with experimenting and prototyping with various state-of-the-art AI weather and climate models.

Enables generative AI downscaling 500x faster with 10,000x improvement in energy efficiency. This augments current applications and workflows, allowing enterprises—now available in the U.S.—to generate more datasets to get better probabilistic distributions for weather events.

Accelerates AI-based global weather forecasting, enabling enterprises to develop solutions using datasets that are up to 20x larger to capture extreme weather events while accelerating and maintaining energy efficiency.

Physics AI training framework used to train the NIM microservices at scale on petabyte-size datasets like ERA5, HRRR, etc. Developers can use the training pipelines to customize AI weather models on custom data.

By accelerating analysis 700,000X, NVIDIA Omniverse and PhysicsNeMo 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.

This first-of-its-kind AI model is set to transform climate modeling and analytics to better predict, understand, and respond to climate change.

Platform for developing accelerated, AI-augmented, high-resolution climate and weather solutions with interactive visualization.

NVIDIA Earth-2 combines the power of AI, GPU acceleration, physical simulations, and computer graphics to develop applications that can simulate and visualize weather and climate predictions at a global scale with unprecedented accuracy and speed. The platform consists of development tools, microservices, and reference implementations for AI, visualization, and simulation. NVIDIA NIM™ microservices for Earth-2 allow users to leverage AI-accelerated models to optimize and simulate real-world outcomes for climate and weather.

With Earth-2’s AI tools and microservices, climate and weather application developers can leverage reference AI inference pipelines using pretrained models and training pipelines and NVIDIA PhysicsNeMo for fine-tuning with custom data. Earth-2 offers a portfolio of community models. These models are transformational in their ability to efficiently generate large ensembles or high-resolution predictions by downscaling.

Interactive visualization microservices enable large-scale weather and climate data to be visualized and analyzed. NVIDIA Omniverse™ Blueprint for Earth-2 weather analytics showcases how developers can use the Omniverse SDK and microservices to build NVIDIA RTX™-powered visualization pipelines for rendering geospatial and weather data. The blueprint also provides a template for partners to integrate their data platforms into AI pipelines.

Simulation microservices will make it possible to encapsulate, orchestrate, and accelerate numerical weather prediction (NWP) models on NVIDIA GPU platforms.

Python-based GPU-accelerated package designed to quickly get users up and running with experimenting and prototyping with various state-of-the-art AI weather and climate models.

Enables generative AI downscaling 500x faster with 10,000x improvement in energy efficiency. This augments current applications and workflows, allowing enterprises—now available in the U.S.—to generate more datasets to get better probabilistic distributions for weather events.

Accelerates AI-based global weather forecasting, enabling enterprises to develop solutions using datasets that are up to 20x larger to capture extreme weather events while accelerating and maintaining energy efficiency.

Physics AI training framework used to train the NIM microservices at scale on petabyte-size datasets like ERA5, HRRR, etc. Developers can use the training pipelines to customize AI weather models on custom data.

By accelerating analysis 700,000X, NVIDIA Omniverse and PhysicsNeMo 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.

This first-of-its-kind AI model is set to transform climate modeling and analytics to better predict, understand, and respond to climate change.