ORBIT-2 Dataset for Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling

Dataset · Mon Sep 01 04:00:00 EDT 2025

DOI:https://doi.org/10.13139/OLCF/2589526· OSTI ID:3002026

Lu, Dan ^[1]; Wang, Xiao ^[1]; Choi, Jong Youl ^[1]; Tsaris, Aristeidis (aris) ^[1]; Ashfaq, Moetasim ^[1]

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1. ORNL

We release the dataset used in ORBIT-2, an exascale vision foundation model for weather and climate downscaling. The dataset was constructed by preprocessing raw data into paired low-resolution and high-resolution samples for model training and evaluation. Downscaling was performed using bilinear regridding following the WeatherBench2 methodology (https://weatherbench2.readthedocs.io). The dataset integrates four publicly available, open-source sources: ERA5, PRISM, DAYMET, and IMERG, obtained respectively from: • ERA5: https://weatherbench2.readthedocs.io • PRISM: https://prism.oregonstate.edu • DAYMET: https://daymet.ornl.gov • IMERG: https://gpm.nasa.gov/data/imerg Further details on the dataset construction and usage are provided in: Wang, Xiao, et al. “ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling.” arXiv preprint arXiv:2505.04802 (2025).

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 3002026
• Country of Publication: United States
• Language: English