Overview of NVIDIA Earth-2 Correction Diffusion NIM

Correction Diffusion (CorrDiff) is a neural network model that downscales surface and atmospheric variables to improve the accuracy and resolution of weather data. CorrDiff is a two-step approach, where the mean machine learning model is corrected by another diffusion model. CorrDiff exhibits skillful deterministic and probabilistic predictions, and faithfully recovers spectra and distributions for extremes.

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

References

• CorrDiff Publication
  

• 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 CorrDiff NIM provides a fast, accurate model behind a consistent API for producing ensembled, downsampled forecasts over the United States. As part of the broader NVIDIA NIM ecosystem, CorrDiff can be used in conjunction with other NIMs to build pipelines that allow acceleration of weather and climate predictions at local and global scales.

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