Community Research Earth Digital Intelligence Twin: a scalable framework for AI-driven Earth System Modeling

AI NWP models outperform state-of-the-art conventional NWP models like the European Center for Medium Range Weather Forecasting’s (ECMWF) Integrated Forecasting System (IFS) on several global metrics while requiring orders of magnitude fewer computational resources. However, existing AI NWP models still face limitations due to training datasets and dynamic timestep choices, often leading to artifacts that affect performance.

To begin to address these challenges, we introduce the Community Research Earth Digital Intelligence Twin (CREDIT) framework, developed at the NSF National Center for Atmospheric Research (NCAR). CREDIT is a flexible, scalable, foundational research platform for training and deploying AI NWP models, providing an end-to-end pipeline for data preprocessing, model training, and evaluation. The CREDIT framework supports both existing architectures and the development of new models.