AI4Science
RealPDEBench
RealPDEBench
RealPDEBench is a benchmark of paired real-world measurements and matched numerical simulations for complex physical systems. It is designed for spatiotemporal forecasting and sim-to-real transfer evaluation on real data.
This Hub repository (AI4Science-WestlakeU/RealPDEBench) is the release repo for RealPDEBench.
Website & documentation: realpdebench.github.io
Raw HDF5 distribution: realpdebench.westlake.edu.cn
Benchmark codebase:… See the full description on the dataset page: https://huggingface.co/datasets/AI4Science-WestlakeU/RealPDEBench.Sombench-Ice-Prospectivity-Regression
SomBench Benchmark: Polar Ice Prospectivity Regression
Science theme: Polar volatiles
Task: Regression
Dataset Summary
A polar, multi-layer benchmark for predicting near-surface water-ice
prospectivity within ~10° latitude of each pole at 240 m/pixel. Following
the ice-prospectivity workflow of Coyan et al. (2025), the dataset includes a
group of physically motivated evidential layers (thermophysical,
illumination, and terrain) alongside a continuous prospectivity… See the full description on the dataset page: https://huggingface.co/datasets/nasa-ibm-ai4science/Sombench-Ice-Prospectivity-Regression.core-sdo
ML-Ready Multi-Modal Image Dataset from SDO
Overview
This dataset provides machine learning (ML)-ready solar data curated from NASA’s Solar Dynamics Observatory (SDO), covering observations from May 13, 2010, to Dec 31, 2024. It includes Level-1.5 processed data from: Atmospheric Imaging Assembly (AIA)
and Helioseismic and Magnetic Imager (HMI).
The dataset is designed to facilitate large-scale learning applications in heliophysics, such as space weather forecasting… See the full description on the dataset page: https://huggingface.co/datasets/nasa-ibm-ai4science/core-sdo.Sombench-WAC-Crater-Detection
SomBench Benchmark: Robbins Crater Detection, WAC
Science theme: Impact processes
Task: Object detection
Dataset Summary
An impact-crater object-detection benchmark built from the
Robbins (2019) global lunar crater
catalog, a manually compiled, near-complete census of
lunar impact craters (≥ ~1–2 km). Catalog crater centers and diameters are
converted to bounding boxes and packaged over LROC WAC visible tiles drawn
from the pre-training corpus test split, in COCO… See the full description on the dataset page: https://huggingface.co/datasets/nasa-ibm-ai4science/Sombench-WAC-Crater-Detection.Surya-1.0_validation_data
Validation data for Surya 1.0
This dataset comprises imagery from NASA's Solar Dynamics Observatory (SDO). The data can and should be used to validate a local installation of the Surya Foundation Model for Heliophysics. The data is compressed; you should use the hdf5plugin to read it directly.
Sombench-pretraining-data
SomBench Pre-training Corpus: Multimodal Lunar Tiles
Dataset Summary
This includes a small sample from SomBench: a corpus of co-registered, multimodal lunar image tiles built for
large-scale self-supervised (foundation-model) pre-training. It contains a subset of modalities from the
low-resolution (WAC-anchored) and high-resolution (NAC-anchored) tracks specifically used in pretraining.
Tiles are anchored to individual LROC Experiment Data Record (EDR) image… See the full description on the dataset page: https://huggingface.co/datasets/nasa-ibm-ai4science/Sombench-pretraining-data.