NVIDIA Launches Earth-2 Family of Open Models — the World’s First Fully Open, Accelerated Set of Models and Tools for AI Weather

AI weather and climate prediction is more accessible than ever for scientists, startups, developers, enterprises and government agencies worldwide.

At the American Meteorological Society’s Annual Meeting, NVIDIA today unveiled a new NVIDIA Earth-2 family of open models, libraries and frameworks for weather and climate AI, offering the world’s first fully open, accelerated weather AI software stack.

These open technologies — including pretrained models, frameworks, customization recipes and inference libraries — accelerate all forecasting stages, from processing initial observation data to generating 15-day global forecasts or local storm forecasts.

Historically, weather forecasting has relied on powerful supercomputers running physics-based models. AI-powered weather forecasting saves significant computational time and costs, allowing more nations, weather enterprises and businesses to run application-specific forecasting systems.

Making production-ready weather AI fully accessible for organizations to run, fine-tune and deploy on their own infrastructure, NVIDIA Earth-2 is the first open, accelerated set of models and tools that enables developers to bring disparate weather and climate AI capabilities together.  

It’s pioneering work to speed weather prediction, enhance forecasting accuracy, foster collaboration and advance scientists’ overall understanding of the planet’s atmospheric conditions.

Developers across industries are tapping into Earth-2 to predict weather and harness actionable insights. This includes AI weather tool provider Brightband; weather forecasters the Israel Meteorological Service, Taiwan’s Central Weather Administration, The Weather Company and the U.S. National Weather Service (NWS); energy forecasting and grid operations companies TotalEnergies, Eni, GCL and Southwest Powerpool in collaboration with Hitachi; energy trading solutions providers Jua and Metdesk; and financial risk and intelligence firms AXA, JBA Risk Management (The Flood People) and S&P Global Energy.

The new Earth-2 open weather models announced today are:

• Earth-2 Medium Range, powered by a new model architecture called Atlas, which enables high-accuracy weather prediction for medium-range forecasts — or forecasts of up to 15 days in advance — across 70+ weather variables including temperature, pressure, wind and humidity. On standard benchmarks, it outperforms leading open models on the most common forecasting variables measured by the industry. Read the research paper.

• Earth-2 Nowcasting, powered by a new model architecture called StormScope, which uses generative AI to make country-scale forecasts into kilometer‑resolution, zero- to six-hour predictions of local storms and hazardous weather in just minutes. Earth-2 Nowcasting is the first to outperform traditional, physics-based weather-prediction models on short-term precipitation forecasting by simulating storm dynamics directly. It harnesses AI to directly predict satellite and radar imagery. Read the research paper.

• Earth-2 Global Data Assimilation, powered by a new model architecture called HealDA, which produces initial conditions for weather prediction — snapshots of the current atmosphere, including the temperature, wind speed, humidity and air pressure, at thousands of locations around the globe. Earth-2 Global Data Assimilation can generate initial conditions in seconds on GPUs instead of hours on supercomputers. When coupled with Earth-2 Medium Range, this results in the most skillful forecasting predictions produced by an open, entirely AI pipeline. Read the research paper.

These join existing open weather models in the NVIDIA Earth-2 stack: 

• Earth-2 CorrDiff, which uses a generative AI architecture called CorrDiff to downscale coarse-resolution, continental-scale predictions to high-resolution, regional-scale weather fields — providing the fine-grain resolution needed for local forecasting up to 500x faster than traditional methods. 
• Earth-2 FourCastNet3, which delivers high forecasting accuracy for various weather variables, such as wind, temperature and humidity, surpassing leading conventional ensemble models and rivaling top diffusion-based methods while producing forecasts up to 60x faster than these approaches.

Earth-2 also integrates open models from the European Centre for Medium-Range Weather Forecasts (ECMWF), Microsoft, Google and others. In addition, Earth-2 models can be trained and fine-tuned using NVIDIA PhysicsNeMo, an open-source Python framework for developing AI-physics models at scale.

Accurate weather forecasting helps save lives and protect environments — and is a cornerstone of decision-making in agriculture, energy, public health and other industries. 

Researchers, weather agencies, climate-tech innovators and enterprises are already running, fine-tuning and building on these state-of-the-art models to unlock scientific breakthroughs using their own local AI infrastructure.

Weather Forecasting

AI weather tool provider Brightband — a member of the NVIDIA Inception program’s Sustainable Futures initiative — is running Earth-2 Medium Range to issue real-world global forecasts daily. 

“The revolution of new AI weather tools for forecasting is very exciting and continues to gather speed with new models like NVIDIA Earth-2 Medium Range,” said Julian Green, cofounder and CEO of Brightband. “Brightband is among the first to run Earth-2 Medium Range operationally, and the model being open source speeds up innovation, allowing easier comparison and improvements by other members of the weather enterprise.”

The Israel Meteorological Service is using Earth-2 CorrDiff in operation — and plans to use Earth-2 Nowcasting — to generate high-resolution forecasts up to eight times daily, enabling decision-makers to respond more effectively to extreme weather while reducing computational costs.

“NVIDIA Earth-2 models give us a 90% reduction in compute time at 2.5-kilometer resolution compared with running a classic numerical weather prediction model without AI on a CPU cluster,” said Amir Givati, director of the Israel Meteorological Service. “After a recent rainstorm, our AI model trained with CorrDiff was the best of all our operational models for a six-hour verification of accumulated precipitation.”

The Weather Company is evaluating Earth-2 Nowcasting for localized severe-weather applications, and NWS is evaluating the new models to enhance its operational workflows. 

Energy Forecasting and Grid Operations

TotalEnergies is evaluating Earth-2 Nowcasting to improve short-term risk awareness and decision-making.

“NVIDIA Earth-2 represents a major step forward in how advanced weather intelligence can be operationalized at scale,” said Emmanuel Le Borgne, climate and weather forecast product manager at TotalEnergies. “Models like Earth-2 Nowcasting are groundbreaking for our business because they improve short-term risk awareness and decision-making in energy systems where minutes and local impacts matter.”

Eni is intensively testing Earth-2 models, including FourCastNet and CorrDiff, for semi-operational downscaling of predictions to produce probabilistic, high-resolution forecasts of weather and gas demand weeks ahead.

GCL, one of China’s largest solar material producers and a global integrated energy operator, is running NVIDIA Earth-2 models in operation for its photovoltaic prediction system. Compared with traditional numerical weather prediction, Earth-2 provides more accurate prediction data at a lower cost, significantly improving the accuracy of GCL’s photovoltaic power generation prediction.

Southwest Power Pool, in collaboration with Hitachi, is using Earth-2 Nowcasting and FourCastNet3 to improve intraday and day-ahead wind forecasting. This effort supports Southwest Power Pool’s commitment to enhancing grid reliability and enabling more informed operational decisions across the SPP footprint.

Financial Impact Assessment

S&P Global Energy is harnessing NVIDIA Earth-2 CorrDiff to turn climate data into local insights for risk assessment. Global insurance group AXA is using FourCastNet to generate thousands of hypothetical hurricane scenarios as part of its R&D program in model evaluation, methodological development and benchmarking on existing techniques.  

With Earth-2, NVIDIA is delivering state-of-the-art open models, data and tools to the developers and scientists innovating in weather AI, similar to how the NVIDIA Nemotron, NVIDIA Cosmos, NVIDIA Isaac GR00T, NVIDIA Alpamayo and NVIDIA Clara model families provide open foundations for innovation in agentic AI, physical AI, humanoid robotics, autonomous vehicles and biomedical AI, respectively.

Learn how to get started with NVIDIA Earth-2 open models by reading this technical blog and watching this tutorial:

Earth-2 Medium Range and Nowcasting are now openly available via NVIDIA Earth2Studio, as well as on Hugging Face and GitHub. Earth-2 Global Data Assimilation is expected to be released later this year.

Learn more about AI-aided engineering and NVIDIA Earth-2 at AMS, running through Thursday, Jan. 29, in Houston.

See notice regarding software product information.