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jirvin16/ClimateSuite

ClimateSuite If you use ClimateSuite, please ❤️ like this dataset and ⭐ star the SPF GitHub repository for updates. ClimateSuite is a large collection of Earth system model simulations for climate emulation. It was curated for Spatiotemporal Pyramid Flow Matching for Climate Emulation, which introduces Spatiotemporal Pyramid Flows (SPF) for efficient probabilistic climate emulation across temporal and spatial scales. This repository stores ClimateSuite as archive-sharded Zarr… See the full description on the dataset page: https://huggingface.co/datasets/jirvin16/ClimateSuite.

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Dataset Card

ClimateSuite

<h5 align="center">If you use ClimateSuite, please ❤️ like this dataset and ⭐ star <a href="https://github.com/stanfordmlgroup/spf">the SPF GitHub repository</a> for updates.</h5>

ClimateSuite is a large collection of Earth system model simulations for climate emulation. It was curated for Spatiotemporal Pyramid Flow Matching for Climate Emulation, which introduces Spatiotemporal Pyramid Flows (SPF) for efficient probabilistic climate emulation across temporal and spatial scales.

This repository stores ClimateSuite as archive-sharded Zarr data in the following format:

text
grid.nc
inputs/<timescale>/*.zarr
outputs/<climate_model>/<timescale>/*.zarr

The current release includes decadal, yearly, and monthly data for ten climate models: BCC-CSM2-MR, CESM2, CESM2-WACCM, CMCC-CM2-SR5, CMCC-ESM2, GFDL-ESM4, IPSL-CM6A-LR, MRI-ESM2-0, NorESM2-LM, and UKESM1-0-LL.

Downloading the data

The recommended path for SPF users is the repository helper, which downloads matching archive shards and extracts them automatically:

python
from emulator.src.data.huggingface import download_climate_dataset

cache_dir = "/path/to/fast/cache"

# Download and extract the full dataset.
data_dir = download_climate_dataset(
    "jirvin16/ClimateSuite",
    cache_dir=cache_dir,
)

# Download and extract a specific model/timescale subset.
data_dir = download_climate_dataset(
    "jirvin16/ClimateSuite",
    cache_dir=cache_dir,
    climate_models=["NorESM2-LM"],
    timescales=["yearly"],
)

You can also download raw archive shards directly with huggingface_hub:

python
from huggingface_hub import snapshot_download

cache_dir = "/path/to/fast/cache"

# Full archive download.
snapshot_download(
    repo_id="jirvin16/ClimateSuite",
    repo_type="dataset",
    cache_dir=cache_dir,
)

# Specific subset: shared yearly inputs and yearly NorESM2-LM outputs.
snapshot_download(
    repo_id="jirvin16/ClimateSuite",
    repo_type="dataset",
    cache_dir=cache_dir,
    allow_patterns=[
        "README.md",
        "manifest.json",
        "grid.nc",
        "inputs/yearly/*.zarr.tar.zst",
        "outputs/NorESM2-LM/yearly/*.zarr.tar.zst",
    ],
)

Relevant Links

  • —Paper: https://arxiv.org/abs/2512.02268
  • —Code: https://github.com/stanfordmlgroup/spf

Citation

bibtex
@inproceedings{irvin2026spatiotemporal,
  title={Spatiotemporal Pyramid Flow Matching for Climate Emulation},
  author={Irvin, Jeremy Andrew and Han, Jiaqi and Wang, Zikui and Alharbi, Abdulaziz and Zhao, Yufei and Bayarsaikhan, Nomin-Erdene and Visioni, Daniele and Ng, Andrew Y. and Watson-Parris, Duncan},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2026}
}

Contact

jirvin16@cs.stanford.edu