thainamhoang/era5-climate-learn

ERA5 ClimateLearn Benchmark Dataset

Preprocessed ERA5 data using ClimateLearn benchmark method, designed for climate downscaling and weather prediction research. ERA5 Reanalysis is maintained by the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA5 combines diverse observational data with forecasts from the state-of-the-art Integrated Forecasting System (IFS) to provide estimates of atmospheric and land-surface variables at any given time. Original NetCDF dataset can be found in WeatherBench ERA5 Dataset.

Original ERA5 Specifications

• Temporal resolution: Hourly
• Spatial resolution: 0.25° global grid (~31 km)
• Temporal coverage: 1979 to present
• Variables: 37 pressure levels + surface conditions
• Format: NetCDF (.nc)

License & Attribution

This dataset is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Citation

When using this dataset, please cite both the original ERA5 data and the ClimateLearn benchmark:

@article{https://doi.org/10.1029/2020MS002203,
  author = {Rasp, Stephan and Dueben, Peter D. and Scher, Sebastian and Weyn, Jonathan A. and Mouatadid, Soukayna and Thuerey, Nils},
  title = {WeatherBench: A Benchmark Data Set for Data-Driven Weather Forecasting},
  journal = {Journal of Advances in Modeling Earth Systems},
  volume = {12},
  number = {11},
  pages = {e2020MS002203},
  doi = {https://doi.org/10.1029/2020MS002203},
  year = {2020}
}


@nisc{nguyen2023climatelearnbenchmarkingmachinelearning,
  title={ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling}, 
  author={Tung Nguyen and Jason Jewik and Hritik Bansal and Prakhar Sharma and Aditya Grover},
  year={2023},
  eprint={2307.01909},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2307.01909},
}