How Generative AI is Empowering Climate Tech with NVIDIA Earth-2
Table of Contents
- Introduction to NVIDIA Earth-2 and Climate Tech
- Predicting Fine-Scale Weather Details with CorrDiff
- NVIDIA Earth-2 Software Toolkits for AI Weather Models
Introduction to NVIDIA Earth-2 and Climate Tech
NVIDIA Earth-2 is a crucial platform for climate tech, providing actionable insights to tackle extreme weather impacts exacerbated by climate change. The suite of tools focuses on AI model training and inference, with a special emphasis on downscaling using generative AI techniques.
Predicting Fine-Scale Weather Details with CorrDiff
CorrDiff, developed by NVIDIA research and developer technology teams, introduces a corrector diffusion model approach for km-scale weather predictions. It leverages generative learning to predict fine-scale details of extreme weather phenomena with high accuracy and efficiency. By combining regression and diffusion steps, CorrDiff utilizes coarse-resolution forecasts to generate more accurate and detailed predictions at finer resolutions, particularly for regions like Taiwan.
NVIDIA Earth-2 Software Toolkits for AI Weather Models
NVIDIA Earth-2 offers powerful tools like NVIDIA Modulus and Earth2Studio for training and inference of AI weather models. NVIDIA Modulus, an open-source physics-informed machine learning platform, allows training of global AI weather forecasting models and downscaling with CorrDiff. Modulus provides trainable architectures for different models and diagnostic tools for additional variables. Earth2Studio includes pretrained models like FourCastNet and Pangu-Weather for easy integration into custom workflows for forecasting and diagnostic models. The platform aims to streamline the process of building and deploying AI weather models for various use cases.