Overview of NVIDIA Earth-2 FourCastNet NIM

FourCastNet is a data-driven model that provides accurate short to medium-range global predictions at a time-step size of 6 hours with predictive stability for over a year of simulated time (1,460 steps), while retaining physically plausible dynamics.

Earth-2 FourCastNet NIM is an AI model from NVIDIA that’s a part of NVIDIA Earth-2, a set of services and software for weather and climate research.

References

• Spherical Fourier Neural Operator Paper
  

• FourCastNet Paper
  

• NVIDIA Modulus
  

• NVIDIA Earth2Studio
  

Advantages of NIMs

NIMs offer a simple and easy-to-deploy route for self-hosted AI applications. Two major advantages that NIMs offer for system administrators and developers are:

• Increased productivity — NIMs allow developers to build generative AI applications quickly, in minutes rather than weeks, by providing a standardized way to add AI capabilities to their applications.

• Simplified deployment — NIMs provide containers that can be easily deployed on various platforms, including clouds, data centers, or workstations, making it convenient for developers to test, deploy and scale their applications.

The FourCastNet NIM provides a fast, accurate model behind a consistent API for producing medium range global forecasts. As part of the broader NVIDIA NIM Ecosystem, FourCastNet can be used in conjunction with other NIMs to build pipelines that allows acceleration of weather and climate predictions at local and global scales.

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